USCIS uses AI: Claude, ELIS, ATLAS, and FOIA requests

This is an analysis of the official DHS AI Use Case Inventory (DHS - Department of Homeland Security, the parent organization of USCIS), Privacy Impact Assessments (mandatory public documents from USCIS regarding the handling of personal data), FOIA lawsuit texts (Freedom of Information Act - a law that allows requesting internal documents from government agencies), and publications from major immigration firms. All quotes are sourced.

Note. If you don't have time to read the entire article - the essence is in seven points

The main news right away. This is not a conspiracy theory

When someone writes in immigration Telegram channels and forums that "USCIS runs petitions through AI," the usual reaction is to roll their eyes. It sounds like a conspiracy theory. In reality, USCIS has publicly disclosed this because it is required by law.

In 2022, the U.S. Congress passed the Advancing American AI Act. Under this law, every federal agency is required to publish a list of its AI systems. DHS does this on a separate page dhs.gov/ai/use-case-inventory/uscis. The latest update was on January 28, 2026.

As of January 2026, there are 29 USCIS AI use cases on this list. These are not leaked documents or the result of journalistic investigations. This is a self-disclosure by USCIS itself.

As of January 28, 2026, the DHS AI Use Case Inventory lists 29 USCIS AI use cases. According to DHS CIO Eric Hysen (December 16, 2024): "158 active use cases [across DHS], compared to 67 total use cases in 2023... We identified 39 safety- and/or rights-impacting use cases."

A screenshot from the official page of the U.S. Department of Homeland Security: "United States Citizenship and Immigration Services - AI Use Cases." Here, USCIS publicly lists which AI systems it uses. The address is: dhs.gov/ai/use-case-inventory/uscis. On the left, you can see navigation through all DHS components (USCIS, USCG, CBP, CISA, FEMA, ICE, USSS, TSA), which shows that this is part of a federal system for disclosing AI - a requirement of the Advancing American AI Act 2022.

📋 PROVEN - a direct quote from an official DHS or USCIS document with a source link. USCIS has publicly acknowledged this.
⚠️ LOGICALLY FOLLOWS - my conclusion which is not a direct quote. USCIS did not say this, but it follows from other confirmed facts.
🔴 NOT PROVEN or REFUTED - rumor, hypothesis without confirmation, or something that has a direct refutation from DHS.

Anthropic Claude officially operates within USCIS. Direct quote from DHS

If I were to write a clickbait headline, I would say: "USCIS uses the same AI you use at home." And that would be true. A direct quote from the official DHS AI Use Case Inventory, use case DHS-2598 "PDF Intake (PDFI) for myUSCIS", status Deployed (operating in production right now):

DHS AI Use Case Inventory, USCIS, case DHS-2598, annual update January 28, 2026

"PDF Intake (PDFI) is a new form intake channel that allows applicants and attorneys to upload completed PDF forms online. Scanned PDFs submitted through MyUSCIS must be validated against form-specific business rules related to both the overall document and the contents of specific fields. The service can process a scanned input document and return all information pertinent to these validation rules in a consistent structure (JSON) to a user-facing ELIS microservice. The GenAI powered library utilizes Amazon Bedrock – Anthropic Claude 3.7 Sonnet V1 Foundation Model to extract data from PDF forms."
Translation: PDF Intake is a new form intake channel that allows applicants and attorneys to upload completed PDF forms online. Scanned PDFs submitted through MyUSCIS must be validated against form-specific business rules. The service can process a scanned input document and return all information pertinent to these validation rules in a consistent structure (JSON) for the ELIS microservice. The GenAI library utilizes Amazon Bedrock - Anthropic Claude 3.7 Sonnet V1 Foundation Model to extract data from PDF forms.

What this means in simple terms. When you submit a form online through the myUSCIS website - it is processed by Anthropic Claude. This is the same company that makes Claude.ai (a competitor to ChatGPT from OpenAI). Claude 3.7 Sonnet is a specific version of the model. AWS Bedrock is Amazon's language model store through which government agencies can safely use LLM (Large Language Model, a large language model like ChatGPT or Claude) in a secure cloud.

Claude reads your PDF and rewrites all the data into a structured format (JSON - a data structure in the form of "key-value" that computer systems read), which is understood by the internal USCIS system called ELIS (Electronic Immigration System - the internal USCIS system where documents are stored and officers work). After that, the officer sees your application in a regular format in their interface.

Microsoft Azure translates your foreign documents

If you are submitting an EB-1A or O-1 with evidence in Russian, Chinese, Korean, or any other language - the officer may run them through the Microsoft Azure machine translator. A quote from the use case DHS-2305 "USCIS Document Translation Service" (status Pre-deployment - being implemented, not fully operational yet, marked as High-Impact - DHS officially recognizes that the system affects people's rights):

DHS AI Use Case Inventory, USCIS, case DHS-2305

"The USCIS Document Translation Service provides the ability for an immigration officer to upload an evidence document written in another language and request a nearly instantaneous English translation. Within a matter of minutes, the service delivers an image-to-image translation that is displayed side by side with the original in the ELIS Digital Evidence Viewer. The service integrates Global and ELIS services with the Microsoft Azure AI Translator Service. Evidence documents include passports, national identifications, birth certificates, and more complex documents such as police reports." Translation: The USCIS Document Translation Service gives an immigration officer the ability to upload an evidence document written in another language and request a nearly instantaneous English translation. Within minutes, the service provides an image-to-image translation that is displayed next to the original in the ELIS Digital Evidence Viewer. The service integrates Global and ELIS services with the Microsoft Azure AI Translator Service.

What is Microsoft Azure AI Translator in simple terms. It is a cloud-based machine translation service from Microsoft. Similar to Google Translate, but for businesses in a secure Azure environment. The quality is better than regular Google Translate, but it is still machine-generated.

All systems related to your EB-1A / O-1 / NIW petition

Below is an analysis of the main systems from the DHS AI Use Case Inventory that logically relate to talent visa petitions. For each, I provide a direct quote from DHS, a simple explanation, and a clear distinction between "what DHS said" and "what I conclude."

ELIS Evidence Classifier (DHS-16). The program decides what the officer sees first

When you upload an EB-1A petition with dozens or hundreds of pages of evidence (recommendation letters, diplomas, patents, citation reports from Google Scholar) - the officer physically cannot read everything. Therefore, USCIS has implemented a program that automatically labels each page.

DHS AI Use Case Inventory, USCIS, case DHS-16, status Deployed

"The Evidence Classifier Service is a machine learning (ML) solution that reduces the time spent by adjudicators and contractors sifting through digital evidence. The solution systematically tags and surfaces critical evidence types for the adjudicators in Electronic Immigration System (ELIS)... When a user opens a case with potentially hundreds of pages of evidence documents they have clickable bookmarks from these tags that will jump directly to the corresponding page." Translation: The Evidence Classifier is an ML solution that reduces the time adjudicators and contractors spend reviewing digital evidence. The solution systematically tags and highlights critical types of evidence for adjudicators in ELIS... When a user opens a case with potentially hundreds of pages of evidence, they receive clickable bookmarks from these tags that jump directly to the corresponding page.

In simple terms. The program looks at each page of your PDF and labels it: "this is a passport", "this is a recommendation letter", "this is a diploma". The officer opens the case - and sees a list of labels like bookmarks in a book. Clicks on the label - goes to the right page.

Figures from DHS itself: over 8 months (September 28, 2021 - May 20, 2022), the system saved ~24 million page flips and 13,348 hours of officer work.

ATLAS. What it actually does and what it DOES NOT do

First, something important about the name. ATLAS is not an acronym. USCIS has never published a breakdown. In the official document DHS/USCIS/PIA-084 (Privacy Impact Assessment - a mandatory public document on the system's operation with personal data, July 2021), the system is simply called "ATLAS" - it is an internal code name, like Apollo, Phoenix, or Liberty.

The title page of the official document Privacy Impact Assessment for the ATLAS, DHS Reference No. DHS/USCIS/PIA-084, October 30, 2020 (last updated July 2021). 31 pages of technical description of the internal USCIS automated screening system. This is the primary source for all statements about the operation of ATLAS - the original is available on dhs.gov as a formal privacy disclosure.

Now to the essence. ATLAS is not a neural network, not an LLM, not machine learning in the strict sense. It is a rule-based system (a system that operates according to strictly defined "if-then" rules, without learning from data), which automatically checks each USCIS petition against external databases. It is deployed within FDNS-DS (Fraud Detection and National Security Data System - an internal USCIS system for investigating fraud and security threat cases).

DHS/USCIS/PIA-084 ATLAS, July 2021

"ATLAS is used as both an automated check service platform and rule-based screening platform for USCIS... ATLAS rules are designed to identify potential fraud, public safety, and national security concerns. ATLAS applies rules against the biometric and biographic data of USCIS applicants, petitioners, beneficiaries, sponsors, and preparers..."
Translation: ATLAS is used as an automated check service platform and a rule-based screening platform for USCIS... ATLAS rules are designed to identify potential fraud, public safety, and national security concerns. ATLAS applies rules to the biometric and biographic data of applicants, petitioners, beneficiaries, sponsors, and preparers.

What are biometric and biographic data. Biometrics are fingerprints, facial photographs. Biography includes name, date of birth, addresses, employers, phone numbers, passport numbers, A-Number (Alien Registration Number - your unique immigration number assigned by USCIS to each applicant).

What ATLAS actually checks

• Biometric matches with IDENT (the main DHS biometric database), HART (the new successor database to IDENT - Homeland Advanced Recognition Technology), ABIS (Automated Biometric Identification System - the U.S. Department of Defense system) - whether you have used another identity before, whether you have applied under another name;
• Names and DOB (Date of Birth) through FBI Name Check, TECS (Treasury Enforcement Communications System - a law enforcement database with information about individuals who have made it onto a watchlist) - whether you are on the watchlist, whether there are any criminal records;
• Connections between people (one petitioner - the one filing the petition, sponsor - the sponsor, preparer - the document preparer, on multiple cases) - whether one lawyer is filing a mass of suspiciously similar cases;
• Addresses, phone numbers, employers - whether a shell company or known fraud address is being used;
• Source country flags - countries with a high risk of fraud require additional checks.

Statistics from the 2019 USCIS press release: ATLAS processed 16 million screenings and generated 124,000 SGN (System Generated Notification - an automatic notification created by ATLAS when a rule is triggered) for manual review by a FDNS officer (FDNS - Fraud Detection and National Security Directorate, the USCIS division combating fraud).

These checks are performed by a human officer. If they suspect fraud substantively, they send the case to FDNS (Fraud Detection and National Security Directorate) for manual investigation. ATLAS only highlights cases related to identity and connections between people.

Is ATLAS applied to I-140 (EB-1A) and I-129 (O-1)?

PIA-084 ATLAS, footnote #1

"the term immigration request includes all benefit requests (as that term is defined in Title 8, C.F.R. Part 1.2)."
Translation: the term "immigration request" includes all benefit requests (any applications for immigration benefits - petitions, green card applications, citizenship, etc.), as that term is defined in Title 8 C.F.R. Part 1.2 (section 8 of the Code of Federal Regulations of the United States, which regulates immigration).

PAiTH Legal Persona. Internal "ChatGPT for USCIS officers"

This is the most important system for understanding how AI can enter the text of your RFE. Direct quote from DHS:

DHS AI Use Case Inventory, USCIS, case DHS-2599, status Pre-deployment

"PAiTH (Private AI Tech Hub) will serve as USCIS's internal AI workforce assistant... The system will provide role-specific AI assistance to USCIS staff across six functional areas: contracts/acquisition, legal research, language translation, software development, security compliance, and financial operations... Legal Persona: Legal research summaries, statute and regulation citations (INA, CFR), case law analysis, draft legal memoranda outlines, document summaries with legal issue identification... accompanying policy will require human review before being used in any official decision-making, formal communications, and/or reporting."
Translation: PAiTH will serve as an internal AI assistant for USCIS employees... The system will provide role-specific AI assistance in six functional areas. Legal Persona: summaries of legal research, citations of statutes and regulations (INA, CFR), analysis of case law, drafts of legal memoranda, summaries of documents with identification of legal issues... accompanying policy will require human review before use in any official decision-making.

In simple terms. A USCIS legal officer reviewing your EB-1A can enter the chat interface of PAiTH (Private AI Tech Hub - the internal AI hub of USCIS) and ask a question like "what are the case laws regarding the criterion of original contributions of major significance" or "make a summary of the recommendation letters in this petition." The AI will provide:

• Legal research summary - overview of legal literature
• Statute and regulation citations - references to sections of INA (Immigration and Nationality Act, the main federal law of the United States on immigration) and CFR (Code of Federal Regulations, where the rules for the application of laws by agencies are outlined)
• Case law analysis - analysis of case law
• Draft legal memoranda outlines - drafts of legal memoranda (internal analytical notes of the officer)
• Document summaries - summaries of your documents

What DHS itself says about AI in the inventory. A direct refutation of panic

When people panic and write "USCIS now decides everything with AI", there is a direct primary source that refutes this. This is not a press release or a quote from a speaker, but the DHS AI Use Case Inventory itself - an official database where USCIS describes its AI systems. Regarding the Text Analytics Data Science Sentence Similarity Model (DHS-130, the very ATA), DHS writes:

DHS AI Use Case Inventory, USCIS, description of Text Analytics

"Text Analytics does not make any determinations or decisions but is instead utilized as a research tool by staff in the course of their duties."
Translation: Text Analytics does not make any determinations or decisions, but is used by staff as a research tool in the course of their work.

This formula is repeated in the description of each AI system at USCIS in the inventory: "decision support tool", "research tool", "human review required". American Immigration Council in the analysis "Invisible Gatekeepers" confirms that the official position of DHS is: "humans make decisions about detention, deportation, and eligibility, with AI tools playing a supporting role only".

This is a direct public promise from DHS. That AI is used as:

• Decision-support (support for the officer's decisions)
• Training augmentation (assistance in training officers)

And not as autonomous adjudication (autonomous decision-making).

If a leak emerges in the future that shows the opposite - it will be a scandal and grounds for lawsuits. So far, there is no such leak. This is the strongest official position against the thesis "AI decides my case".

Positioning of camps by evidential strength

Unlike the AOS memorandum topic, there is no division of "critics vs defenders" regarding AI in USCIS. Everyone agrees that AI is used. The dispute is about evidential strength: where is the fact, where are the indirect signs, where is the rumor. Therefore, I divide not by "views", but by the level of sources.

Level 1. PROVEN - direct quotes from DHS

Everything discussed above: ELIS Evidence Classifier, PDF Intake via Claude, Document Translation via Azure, ATLAS, PCIS, PAiTH, DHSChat. Source - official DHS AI Use Case Inventory + PIA documents.

Also included:

• Eric Hysen, CIO DHS, December 16, 2024: "158 active use cases, compared to 67 total use cases in 2023. We identified 39 safety- and/or rights-impacting use cases." DHS Source.
• DHS OIG-25-10 audit (OIG - Office of Inspector General, internal independent auditor of the department; January 2025): the internal auditor of DHS stated that they lack control over their own AI.
• USCIS-Palantir VOWS Contract (Palantir - a large American company working with big data for government agencies; VOWS - Vetting Of Wedding-based Schemes, verification of sham marriages), October 2025,

Cozen O'Connor, "Growing Use of AI in Immigration Adjudications"
"USCIS has not published any error-rate data, and practitioners report RFEs for documents that were in fact submitted, consistent with classifier mis-tagging."
Translation: USCIS does not publish any data on error rates, and practitioners report RFEs for documents that were actually submitted, which is consistent with mis-tagging by the classifier. Source.

Cozen O'Connor - one of the largest law firms in the U.S., represents corporate clients. They list four specific patterns. I will analyze each separately: what happens, what it looks like when you receive an RFE, and how to protect yourself.

The title of the Cozen O'Connor publication from April 27, 2026: "Growing Use of Artificial Intelligence in U.S. Immigration Adjudications Is Driving Higher RFE and Denial Rates". Authors: Scott Bettridge (Chair, Immigration Practice) and David S. Adams (Member). The first section of the article is directly titled "USCIS IS NOW USING AI THROUGHOUT THE ADJUDICATION PROCESS". This is not a blog post by an anonymous lawyer - it is a formal client alert from partners of one of the largest law firms in the U.S. (Top 100 by revenue) published on the firm's official website. Source.

Pattern 1. Mis-tagged evidence. RFE on documents you definitely submitted

When you upload a petition through myUSCIS, the ELIS Evidence Classifier (that same ML program from the DHS Inventory) automatically scans each page and labels it: "this is a passport", "this is a recommendation letter", "this is a diploma", "this is a publication in a journal". The officer opens your case and sees a ready-made list of labels-bookmarks. They work based on these bookmarks.

The problem is that the ML classifier sometimes makes mistakes. Suppose you submitted 8 recommendation letters. The classifier correctly tagged six as "Recommendation Letter". But two were mistakenly categorized as "Other Document" - for example, because one letter had unusual formatting, and the other was a scan with shadows.

The officer opens the "Recommendation Letters" criterion, sees 6 letters instead of 8, and writes in the RFE: "petitioner submitted only 6 recommendation letters". You open your copy of the petition - see all 8 in place. This creates a strange situation: you are factually correct, and at the same time, the officer is correct according to their logic - they indeed saw only 6 because the classifier did not show the others.

To reduce the risk of such loss: give files clear names indicating the type of document (Recommendation_Letter_Prof_Smith_Stanford.pdf instead of the faceless RecLetter1.pdf), do not combine several different pieces of evidence into one large 200-page PDF, attach a cover letter with a clear correspondence table: "Exhibit A-1 - Letter from X - pages 47-50". If the RFE claims that documents are missing, the response should explicitly indicate where exactly in the original petition these documents are located, with references to Exhibit, page, and paragraph.

Pattern 2. Cross-document mismatch. When one letter triggers an RFE

USCIS has a Verification Match Model. It compares data across all your documents and highlights discrepancies. If in the DS-160 (B-1 visa application) you wrote "Senior Software Engineer", in the I-129 (current O-1 petition) - "Principal Software Engineer", and in the recommendation letter - "Lead Engineer", the program sees three different titles and flags it. From a human perspective, this is obviously the same position with slight variations. From an automation perspective, these are three different entries.

A specific example from the practice of SG Legal Group: their client received an RFE for "date inconsistencies". Upon investigation, it turned out that in one Russian document the date was written according to GOST (15.03.2023), in the English translation - in American format (03/15/2023), and in the third document - in European format (15/03/2023). This is the same date written in three ways. AI saw three different strings and flagged it as a contradiction. The lawyer in their analysis explicitly states that there were no other logical grounds for this flag in the case - meaning it was set by the machine, not a human.

Pattern 3. Ghost text. What you don't see, AI reads

Modern PDFs can contain an invisible text layer. You open the file, see your text, everything looks neat. But the program that reads the PDF machine-wise (for example, AI USCIS) sees both what is visible to the eyes and what is hidden in the concealed layer. Where does this hidden layer come from:

• You scanned and passed it through OCR - an invisible OCR layer was created over the image
• You converted Word to PDF - hidden comments, tracked changes, metadata remained
• You copied text from ChatGPT or Claude and pasted it into Word - invisible service tags could remain
• You took a template from the internet and rewrote it for yourself - old template text may remain in the file invisibly

In practice, it looks like this: you wrote a recommendation letter from scratch, exported it to PDF. You see your text with your eyes. AI USCIS reads both the visible and the hidden. If a phrase from a previous template like "Dear Hiring Manager" remained in the hidden layer - AI flags your letter as "boilerplate detected". The worst case: if phrases characteristic of AI generation remain in the hidden layer - typical phrases from ChatGPT - AI USCIS may mark your letter as generated by artificial intelligence. And this is despite the fact that you wrote it yourself.

Checking your PDFs for ghost text is not difficult. Open the PDF in Adobe Acrobat or in the standard Preview on Mac, press Ctrl+A or Cmd+A (select all text). If more is highlighted than you see with your eyes - then there is a hidden layer. An alternative method through the command line: pdftotext your_file.pdf - will show all the text in the file. If ghost text is found and there is a lot of it, the most reliable solution is to print the critical document, scan it again, and save it as a clean PDF. This eliminates all inherited hidden layers.

Pattern 4. AI-generated boilerplate RFEs. The template generated a template

If the previous three patterns are about AI reading your documents, this one is about AI writing the officer's response documents. The internal AI assistant of USCIS (PAiTH Legal Persona or similar) generates a draft RFE for the officer. The officer quickly reviews it, corrects one or two phrases, and sends it. When the workload on officers is high, this mode of operation becomes widespread.

The attorneys at Reddy Neumann Brown accurately describe such an RFE: "it looks official, but reads as if no one actually reviewed the case." They provide specific signs by which such RFEs can be identified.

Identical wording for each criterion - like "This criterion has not been met because..." is repeated ten times in a row without variations. Citing court cases that have nothing to do with immigration - for example, Silverman v. Eastrich is a case about a $10 million loan default, and APWU v. Potter is about an anthrax investigation in post offices, but both appear massively in EB-1A RFEs as justification for the high threshold.

Long paragraphs copied verbatim from the USCIS Policy Manual without any analysis of your specific petition. Mentioning an employer or field of activity that does not apply to you - a real case from Reddit: a person received an RFE mentioning "FAANG" even though they had never worked for any of those companies. Specific words characteristic of language models: "opine", "juxtapose", "comprehensive examination", "robust analysis" - attorney Ksenia Maiorova calls them "AI tells".

If you received such an RFE, the response strategy is as follows. For each assertion of "lack of evidence," provide an exact reference to the original petition: which Exhibit, which page, which paragraph. This forces the officer to acknowledge that evidence was presented. If the RFE cites case law that is not related to immigration, clearly state that this is the case and request relevant precedent.

If there is a factual error in the RFE (an employer not mentioned, names mixed up, incorrect country) - clearly document this as a factual error that requires explanation from USCIS. It makes sense to keep the full text of the RFE and anonymously publish it in the community (Trackitt, AILA member forums, relevant subreddits) - this creates a body of evidence for patterns for future legal challenges.

Numbers that show the scale

Cozen O'Connor provides data: the denial rate for EB-2 NIW has risen to about 40%, EB-1A is under heightened scrutiny.

To understand the scale, compare with historical USCIS figures. EB-2 NIW has traditionally been approved in 70-75% of cases, meaning denials occurred in 25-30%. An increase to a 40% denial rate means that almost half of the increase in denials happened in just the last year. EB-1A has historically been approved in 75-80% of cases. As of Q3 of fiscal year 2025, this figure has dropped to 66.6% - the lowest in 3 years, indicating an increase in denials from about 20% to 33%. O-1 for contrast: 93.8% approval and the category remains stable, with virtually no changes.

This contrast between categories reveals an important pattern. EB-1A and NIW require discretionary evaluation - the officer must qualitatively determine whether the applicant's achievements meet the standard of "extraordinary ability" or "national importance." This qualitative judgment is complex for AI. O-1 requires a more formal check of criteria - have you received specific awards, published a certain number of articles. This is checklist work, which AI handles better. The drop in approvals specifically in discretionary categories while remaining stable in checklist categories is a characteristic signature that AI is being applied specifically to the discretionary part and is failing there.

Reddy Neumann Brown PC, January 2026

Reddy Neumann Brown PC, "RFE Trends January 2026" "disorganized, boilerplate recitations of USCIS Policy Manual provisions, field adjudicator guidance, or regulatory language, often copied verbatim and presented without analysis, explanation, or reference to the specific evidence already submitted in the petition... looks official but reads as though no human being meaningfully reviewed the filing" Translation: disorganized boilerplate recitations of USCIS Policy Manual provisions, copied verbatim and presented without analysis... looks official but reads as though no human being meaningfully reviewed the petition. Source.

The firm directly compares it to AI hallucination (AI hallucination - when the model confidently produces incorrect facts) and refused to recommend premium processing for EB-1A and NIW (premium processing - a paid USCIS service for expedited petition review: $2,805 as of January 2026, $2,965 since March 1, 2026 - with a guaranteed response in 15-45 days). Premium has become a "fast track to RFE," not to approval.

The Seltzer Firm. Documented misquoting of case law in RFE for EB-1/O-1

Systematically misquoted cases:

• Silverman v. Eastrich Multiple Investor Fund (actually a case about a $10 million loan default, not related to immigration) and APWU v. Potter (about the investigation of anthrax mailings in post offices) - are cited to define "original contributions of major significance," although they are not related to immigration;
• Visinscaia v. Beers (the case of a Moldovan ballerina, denial in EB-1A) - is mischaracterized (the meaning of the court decision is distorted);
• Matter of Caron International - is selectively quoted without restrictive context (i.e., only the necessary part is quoted, without the caveats that were in the case itself);
• Templates change the regulatory "in the field" to the rigid "to the field…dramatic impact."

Source: The Seltzer Firm.

BMD Law, "Invisible Algorithms". Fair Disclaimer

BMD Law, "Invisible Algorithms" "Some practitioners have reported receiving RFEs that contain language or structure consistent with AI-assisted drafting. This has not been confirmed by USCIS, and there is currently no public evidence that AI is being used to generate adjudication decisions or official correspondence." Translation: Some practitioners have reported receiving RFEs that contain language or structure consistent with AI-assisted drafting. This has not been confirmed by USCIS, and there is currently no public evidence that AI is being used to generate adjudication decisions or official correspondence. Source.

OCR errors (OCR - Optical Character Recognition; academic proof exists - scientific article "Framework to Improve NLP Accuracy over OCR Documents") Common agency templates that USCIS has been using for decades Human copy-paste practice Real AI assistance in drafting

Without leaked prompts, screenshots, or FOIA releases, we cannot distinguish "AI wrote RFE" from "the officer copied from the template and made a mistake."

Are there any leaked prompts from USCIS? As of May 2026 - no. I checked through several channels:

Open search engines - no results for "USCIS leaked prompt" / "ELIS screenshot" / "USCIS officer interface" 404 Media (known for leaks on Mobile Fortify) - no publications on USCIS prompts WikiLeaks / DDoSecrets - no USCIS-relevant documents with prompts FOIA releases on Pangea v. USCIS and Refugees International v. USCIS - about 1,677 pages have been issued but without prompts or system instructions GitHub repositories of USCIS - empty

So we know that AI is used (DHS itself confirmed), we know which systems, which vendor (Anthropic), on which infrastructure (AWS Bedrock) - but the specific text of instructions that the officer or the system itself gives to Claude has not appeared publicly anywhere. If the situation changes, it will be one of two paths: (1) a court on FOIA requests will order USCIS to release more specific records on the use of AI (potentially including prompts if they exist as standalone documents), (2) an internal leak through 404 Media or similar. Mobile Fortify revealed it this way - leaked emails in June 2025, six months before the official acknowledgment.

Level 4. DISPROVEN or NOT CONFIRMED

• "AI makes final decisions on EB-1/O-1" → direct refutation in DHS AI Use Case Inventory: each system is marked as "decision support tool" or "research tool";
• "USCIS leaked prompts" → do not exist publicly;
• "Screenshots of internal adjudicator interfaces" → have not been published;
• "USCIS partnership with OpenAI" → not confirmed. With Anthropic - yes, through AWS Bedrock in PDF Intake;
• "Matter Helper" internal AI of USCIS → rumor, likely confusion with the commercial tool "Matter" for lawyers;
• "Babel Street processes USCIS petitions" → Amnesty International (July 2025) did not confirm the USCIS-Babel contract. Used in State Dept / CBP, but not USCIS;
• r/USCIS_Officers - such a subreddit does not exist.

FOIA Lawsuits. What Plaintiffs Want to Know and What the Coming Year Will Show

As of May 2026, two lawsuits could change the landscape. Both are filed in D.D.C. (District Court for the District of Columbia).

Pangea Legal Services v. USCIS, No. 1:24-cv-02809-ACR (D.D.C., October 3, 2024)

Plaintiffs: Pangea Legal Services, Mijente Support Committee, Just Futures Law (the latter acts both as a plaintiff and as counsel). All data below is taken directly from PACER (Public Access to Court Electronic Records - the official database of federal courts in the USA) as of May 25, 2026.

Screenshot of an actual docket from the CM/ECF system (Case Management / Electronic Case Files - the official electronic system of federal courts in the USA). It shows: filing date 03/10/2024, COMPLAINT against DHS/ICE/USCIS, filed by Pangea Legal Services + Just Futures Law + Mijente Support Committee, Filing fee $405, case assigned to Judge Ana C. Reyes on 07/10/2024. Counsel for the plaintiffs - Sejal Zota (Just Futures Law). All 22 attachments (16 exhibits + civil cover sheet + 5 summonses) are attached to the Complaint. This access is paid (PACER charges for each page) - meaning the article relies on purchased primary sources, not on retellings.

Judge: Ana C. Reyes. Biden-appointed, sworn in February 2023, previously a partner at Williams & Connolly. Known for her strong positions on transparency and FOIA.

Critical Detail: Judge Reyes is handling both key FOIA lawsuits against USCIS regarding AI - both Pangea and Refugees International (see below). PACER has formally marked them as Related Cases. This is not a coincidence: D.D.C. often groups similar cases under one judge. Her decision in one case will almost certainly influence the other.

Counsel for Plaintiffs (as of May 2026):

• Sejal Zota (Just Futures Law) - active since October 2024
• Yihong Mao (Just Futures Law) - joined January 2026
• Dinesh McCoy (Asian American Legal Defense Fund) - left August 27, 2025
• Daniel Werner (Just Futures Law) - left December 17, 2025

Counsel for Defendants: Esther You (DOJ-USAO) - currently lead, replaced Kartik Venguswamy (ArentFox Schiff) on March 26, 2026. DOJ has taken the case - this signals that the federal government considers the case a priority and does not want to leave it to outside attorneys.

The lawsuit demands from USCIS 16 categories of records for each key AI system:

• Lists of AI tools;
• Training data for models (what the AI was trained on);
• Policies and training materials for officers;
• Contracts with third parties (who developed them);
• Records on "Pangea Text" (this is the internal name for Asylum Text Analytics);
• AI for analyzing behavior, emotions, social networks;
• Sharing AI-generated info with other agencies;
• PIA and AIA (Algorithmic Impact Assessments);
• Waivers - exemptions from AI Act requirements;
• Consultations with affected communities;
• Redress procedures (how to appeal an AI decision);
• Bias monitoring and testing;
• Audits, validation, accuracy metrics (actual error statistics);
• Notice policies (whether applicants are informed about the use of AI);
• Opt-out policies (whether one can refuse AI);
• "Rights-impacting" determinations.

Actual production figures as of March 31, 2026 (from Joint Status Report Doc #29, signed by Esther You from DOJ and Yihong Mao from Just Futures Law):

• USCIS: production fully completed on June 30, 2025. The exact number of pages in the JSR is not specified. The plaintiffs are currently reviewing the documents and both parties "intend to work together in good faith to address any remaining issues."
• ICE: production fully completed on April 24, 2025. The plaintiffs challenged the adequacy of search on September 22 and October 7, 2025. On February 13, 2026, ICE issued an additional 7 pages and a response. The plaintiffs disagree again and raised issues regarding the search and exemptions.
• DHS: identified ~3,500 pages based on a narrowed request. As of March 31, 2026, only: 3 pages (December 30, 2025) + 127 pages (January 28, 2026) + 29 pages (February 13, 2026) = ~159 out of 3,500. The rest was sent for consultation with Other Governmental Agencies on January 30, 2026. DHS has deviated from the promised 500 pages/month.

🚨 Government shutdown since February 14, 2026. From the JSR: "DHS, which includes ICE, is currently experiencing a lapse in appropriations which began February 14, 2026. DHS FOIA employees are furloughed and have not been excepted to work on FOIA litigation." This means that as of late May 2026 DHS FOIA employees had been on unpaid leave for about 3.5 months, and production was frozen. The plaintiffs directly challenged the legality of halting releases during the shutdown in the JSR - "Plaintiff raises and preserves the legal issue of whether DHS and its subagencies can release productions related to FOIA requests during a lapse in appropriations."

Counsel for the defendant - United States Attorney Jeanine Ferris Pirro. This is a political signal: Pirro is a former Fox News host, appointed U.S. Attorney for D.D.C. under the Trump administration in 2025. Her signature on the latest JSR indicates that the DOJ is handling the case personally, rather than through outside counsel.

The next checkpoint was the Joint Status Report of May 29, 2026 - 4 days after the date of this article. It was to show whether the shutdown had ended, whether production had resumed, and whether the plaintiffs had moved to compel; its outcome is not reflected in this article.

What is NOT in the docket as of May 2026: Motion for Summary Judgment, Vaughn Index, ruling by Judge Reyes on the merits. This means that despite 18 months of production and 29 docket entries - there has not yet been a judicial ruling that would disclose AI prompts from USCIS. This means that leaks of prompts through Pangea can be expected no earlier than 2027, and realistically - 2028.

Documents directly from the plaintiffs:

• Just Futures Law - DHS AI FOIA filings page - case page with key filings and updates
• Just Futures Law - "Reining in AI Surveillance" - continuously updated section of the site about DHS AI tools
• Automating Deportation: The Artificial Intelligence Behind The Department of Homeland Security's Immigration Enforcement Regime (PDF, June 2024) - primary detailed report from Just Futures Law + Mijente on which the entire Pangea lawsuit is based. If you read only one document on the topic of AI in DHS - this is it. It specifically names commercial AI tools that DHS is purchasing (for example, LexisNexis Accurint - available to 11,000+ ICE agents for automating vetting/screening/targeting).

Filing a FOIA request. Any organization or individual can request internal documents from a government agency. The agency is legally required to respond within 20 business days.
If the agency remains silent or denies the request, the plaintiff can file a lawsuit in federal court demanding the release of documents. This is what Pangea + Mijente + Just Futures did in October 2024.
Production. This is the longest part. The agency searches for responsive records (documents that correspond to the request), decides what to release in full, what to release with redactions, and what to withhold entirely. It sends this in batches (rolling production).
Joint Status Report - both parties report to the court every 60-90 days on what has been released, what remains, and whether there are disputes. If the dispute is serious, the plaintiffs file a motion to compel or the defendant files a motion for summary judgment.
Vaughn Index - a formal list of all documents that the agency refused to release, with justification for each refusal. In FOIA cases, this is a critical document - it is based on this that plaintiffs can challenge withholdings. If the Vaughn Index is not released, it means the case is still far from a substantive decision.
Court ruling - the judge decides what must be released. In FOIA, this takes years.

In the Pangea case, it has already been 18 months, 8 Joint Status Reports have passed, thousands of pages have been released - but the most sensitive documents remain under consultation or have been withheld. The Vaughn Index has not been released. Judge Reyes has not yet issued a substantive ruling. And then a shutdown occurred.

Do not expect a quick disclosure of USCIS prompts through the court. Previously, I wrote that Pangea and Refugees International might disclose prompts in the "next 12-24 months." This was overly optimistic. The real timeline: a ruling on the merits no earlier than 2027, a realistic moment for the disclosure of materials that will show how USCIS AI systems actually work - 2028-2029. Filing a petition in 2026 goes without knowledge of AI details.

USCIS has already released records to the plaintiffs, but we do not see them. USCIS production was completed on June 30, 2025. Just Futures Law has already received and reviewed some documents. If they publish significant findings on their website justfutureslaw.org/aitech or in a new report, it will become available to the Russian-speaking audience. It is worth subscribing to their newsletter or monitoring their blog.

The government shutdown is a new risk factor for all immigration cases. FOIA staff at DHS have been on unpaid leave since February 14, 2026. But the shutdown affects not only FOIA - regular USCIS adjudication officers are also working in a reduced capacity. This explains why RFEs in early 2026 may be even more boilerplate than before: officers are overwhelmed, templates (or AI assistance) are the only way to continue working.

Plaintiff activity is increasing. The fact that on September 22 and October 7, 2025, the plaintiffs directly challenged the adequacy of the search by ICE means they are moving from polite negotiations to real pressure. Had the plaintiffs filed a motion to compel by the May 29, 2026 JSR, it would have been the first serious court conflict; check the docket for what happened next.

An alternative route is individual FOIA requests. Pangea requested the system as a whole. But any EB-1A/O-1/NIW applicant can submit their personal FOIA request for their A-file (their personal folder in USCIS) specifying "including all AI-generated summaries, classifications, flags, and alerts in my case." USCIS usually releases A-files within 30-90 days. This will provide your specific documents faster than the overall Pangea case will provide systemic ones.

Prepare your petition for the 2026-2028 horizon without hope for disclosure. Practical recommendations in the next section work regardless of whether USCIS prompts are disclosed at all or not. This is basic protection: clear file names, OCR layer, certified translations, name variation memorandum, consistency between documents.

If you receive a denial for EB-1A/O-1/NIW in 2026, the Mukherji v. Miller path may be possible. Remember that Mukherji won in the federal district court of Nebraska (January 2026) based on Loper Bright - courts are no longer required to listen to USCIS interpretation. This provides a real legal basis for challenging opaque AI conclusions through an APA challenge, without waiting for Pangea to disclose the prompts. Detailed information about the case status and strategy: my post "Mukherji v. Miller three months later" and "The case that could remove Final Merits for everyone".

Refugees International v. USCIS, No. 1:24-cv-03559 (D.D.C., December 20, 2024, Judge Ana C. Reyes)

Counsel: Harvard Immigration & Refugee Clinical Program (Sabrineh Ardalan, Jessenia Class, Martha Ball) + Jenner & Block LLP.

The lawsuit demands:

• Internal guidelines on the use of ATA (Asylum Text Analytics - USCIS's internal system for analyzing asylum application texts) when assessing asylum
• Training materials, including "lines of questioning and RFE based on ATA findings"
• Sample redacted Pangaea Text report, Statement of Findings, RFE
• 20 categories of statistics: how many cases were reviewed, flagged, by nationality, by office, denials, deportations

Letter from 142 organizations to Mayorkas, September 4, 2024

A coalition of 142 organizations (as confirmed by Just Futures Law), including EFF (Electronic Frontier Foundation), EPIC (Electronic Privacy Information Center), AILA (American Immigration Lawyers Association), Mijente - sent a letter to DHS Secretary Alejandro Mayorkas titled "Cancel DHS Use of AI Technologies for Immigration Enforcement and Adjudication by December 1, 2024".

Demand: suspend AI tools that do not comply with OMB Memorandum M-24-10 (OMB - Office of Management and Budget; memorandum M-24-10 - mandatory rules for all federal agencies regarding AI). The categories "rights-impacting" and "safety-impacting" are formal classifications of AI systems by risk level. Source: Just Futures Law, confirmed by FedScoop as "more than 140 groups".

Diagnostic Silence. What those expected to analyze are not saying

This is a diagnostic observation. As of May 25, 2026, an entire category of sources is silent.

Former top DOJ lawyers are silent

In January 2026, Sarah Lake Vuong (former Assistant Director DOJ Office of Immigration Litigation) and Jess Ariela Dawgert (former Associate Deputy Attorney General DOJ) opened a firm in Denver, Ariela Lake Law & Consulting. These individuals have written and defended U.S. immigration policy in courts for the last 15 years. There have been no public comments from them on the AI topic so far.

Out of 15 major think tanks, 14 are silent

Only Cato Institute (David Bier) has released its own analysis. A think tank is a research center that publishes studies on political topics. Migration Policy Institute, NFAP (National Foundation for American Policy), American Immigration Council, Niskanen Center, AEI (American Enterprise Institute), Heritage Foundation, Brookings, Center for American Progress, FAIR (Federation for American Immigration Reform), CIS (Center for Immigration Studies), EPI (Economic Policy Institute), Bipartisan Policy Center, R Street, Manhattan Institute, Hoover - are silent.

Especially interesting is the silence of anti-immigration think tanks (Heritage, FAIR, CIS), which usually quickly release defensive texts in support of restrictive policies. Andrew Arthur (CIS) typically responds within the first 24-48 hours to any news. On the AI topic - silence.

AILA publishes but does not file its own lawsuit

AILA has not filed a specialized FOIA or lawsuit specifically regarding USCIS AI. AILA actively monitors Executive Orders, publishes practice alerts for attorney members. However, AILA has not released its own lawsuit or serious policy brief on the AI topic.

The topic is perceived as a technical rebranding, not requiring defense or criticism
They are waiting for court challenges (Pangea and Refugees International) before speaking out
They are preparing a non-public litigation strategy for specific clients, where open comments would be detrimental

What the community and attorneys are saying publicly. Direct quotes from Reddit and LinkedIn

The most valuable stories are not press releases from firms, but specific individuals describing what they saw in their RFE. Below are verbatim quotes from Reddit and LinkedIn, collected through direct research of threads (searching through Google for Reddit since 2024 has been severely weakened, had to use direct Reddit API). All quotes include the source URL, date, and number of upvotes.

The main smoking gun. RFE with the name of an employer the person has never worked for

u/LegalMagazine1793, r/eb_1a, December 11, 2025, 5 upvotes, 16 comments
"What concerns me is that the RFE does not mention a single exhibit, achievement, or employer document I included. It is extremely general and even contains an employer name that has nothing to do with me… To assist in determining that the beneficiary has performed in a leading or critical role for FAANG, the petitioner may submit… For clarity: I have never worked for FAANG (the company named in the RFE)."
Translation: I am concerned that the RFE does not mention a single one of my exhibits, achievements, or employer documents. It is extremely general and even contains the name of an employer that has nothing to do with me... I have never worked for FAANG (FAANG is slang for top IT companies: Facebook (Meta), Apple, Amazon, Netflix, Google; the company mentioned in the RFE). Source Reddit.

In the comments of this thread, other users directly suggested AI processing:

u/Competitive_Yam_1942, comment in the same thread
"They ran it through ai and they just shared result, I guess. Based on your profile, the tool took it you are from faang."
Translation: They ran it through AI and just published the result. Based on your profile, the tool decided you are from FAANG.

u/Guilty-Leather-6662, comment in the same thread
"My thoughts exactly. Also you can tell by the same 'This criterion has not been met because ...' for each criterion. What an interesting time we are living in."
Translation: My thoughts exactly. This is evident from the same wording 'This criterion has not been met because...' for each criterion. What an interesting time we are living in.

In another thread "USCIS AI agent review" (u/Any-Bed8987, April 30, 2026) there was a direct suspicion of a specific model:

u/Elegant-Past7936, comment to the thread u/Any-Bed8987
"do you think they use Claude?"
Translation: Do you think they use Claude?

This is the first public mention of Anthropic Claude from an ordinary EB-1A applicant. There is no direct confirmation in the thread, but the mere fact that the audience is already asking such a question shows where the discussion is located.

Immigration attorney AILA publicly confirms the pattern

u/JoeAdamsESQ (immigration attorney), r/O1VisasEB1Greencards, April 29, 2026
"USCIS misattributing submitted evidence to the wrong O-1 criteria - here my colleague suspected AI used by USCIS was hallucinating that the petition claimed criteria that they hadn't actually claimed."
Translation: USCIS is misattributing submitted evidence to the wrong O-1 criteria - here my colleague suspected that the AI used by USCIS was hallucinating and attributing criteria to the petition that it had not actually claimed. Source Reddit.

EB-5 firm received an RFE that looks like machine generation

u/KyoMeetch, r/EB5_Immigration, March 13, 2026, 11 upvotes
"Several months ago, my firm received an RFE on an I-526e that heavily deviated from the typical RFE format. While we commonly see similar formats with a straightforward summary of the requested documents, on this occasion we saw a large conglomerate of patched together complaints with misspellings, incorrectly named entities, and dubious legal citations. It's possible some USCIS adjudicators may be incorrectly relying on unofficial AI software to do their work for them."
Translation: our firm received an RFE on I-526e that significantly deviated from the typical format. It was a large conglomerate of patched together complaints with misspellings, incorrectly named entities, and dubious legal citations. It is possible that some USCIS officers are improperly relying on unofficial AI software. Source Reddit.

ELIS Evidence Classifier mis-tagging. A specific case with missed criteria

u/Embarrassed_Cry_1167, r/eb_1a, February 4, 2026, 7 upvotes, 40 comments
"I submitted evidence for 6 criteria, but the RFE only addresses 4 of them. The other 2 aren't mentioned at all - not approved, not denied, just completely ignored as if I never submitted them."
Translation: I submitted evidence for 6 criteria, but the RFE only addresses 4 of them. The other 2 aren't mentioned at all - not approved, not denied, just completely ignored as if I never submitted them. Source Reddit.

In the comments to this thread, a user provides an explanation from their attorney, directly pointing to the work of the classifier:

u/cocacola335ml, comment to thread u/Embarrassed_Cry_1167
"This happened to me, it's really frustrating, my attorney says they have been having the same issue with many cases, it seems like when they scan the case when it arrives they don't scan the whole thing."
Translation: this happened to me, very frustrating, my attorney says they have the same problem with many cases, it seems that when they scan the case upon arrival, they don't scan everything. - This is the exact description of the ELIS Evidence Classifier that we discussed at the beginning of the article.

In the same thread, another telling quote:

u/Available-Scale-3880, comment to thread u/Embarrassed_Cry_1167
"For my authorship criteria they said I submitted 'LinkedIn websites', whereas I never published anything on LinkedIn and never used that as proof (and what even does 'LinkedIn websites' mean?!)"
Translation: for authorship criteria they said that I submitted 'LinkedIn websites', whereas I never published anything on LinkedIn and never used that as proof (and what even does 'LinkedIn websites' mean?!)

Template generator. 5 pages out of 6 - a copy of the Policy Manual

u/baka_sensie, r/EB2_NIW, April 25, 2026, 18 upvotes, 53 comments
"The denial letter is 6 pages, out of which 5 pages are a copy-paste of USCIS policy manual text. The denial letter only mentions my name and the first paragraph of my PE, and then it generally states that my PE has substantial merit but not national importance, without once mentioning any details regarding my PE or anything else from what I submitted in the RFE."
Translation: the denial letter is 6 pages, of which 5 are copy-paste text from the USCIS Policy Manual. The denial letter mentions only my name and the first paragraph of my proposed endeavor, and then generally states that my work has substantial merit but not national importance, without once mentioning any details of my proposed endeavor or anything from what I submitted in response to the RFE. Source Reddit.

Author profile: PhD Electrical Engineering, postdoc at an R1 university, US patent, 3 first-author publications in top-5 journals in the field. NSC officer 0399.

NOID after RFE response. The officer seems not to have opened the response

u/Com_org, r/eb_1a, April 30, 2026, 5 upvotes, 22 comments
"Got NOID on April 21, 2026… But the NOID's objections reference ONLY original petition evidence. Not a single RFE exhibit is mentioned. NOID says 'Wikipedia printouts for associations' → We submitted actual bylaws and selection criteria that USCIS asked for in the RFE. Still says Wikipedia."
Translation: received NOID on April 21, 2026. But the NOID's objections reference ONLY original petition evidence. Not a single exhibit from the response to the RFE is mentioned. NOID says "Wikipedia printouts for associations" → we submitted actual bylaws and selection criteria that USCIS requested in the RFE. NOID still says Wikipedia. Source Reddit.

Author profile: Database Engineering Principal-level at FAANG, ~20 years of experience, Guinness World Record, Fortune 500 technology adoption - none of these achievements are mentioned in the NOID.

Cluster of complaints about one officer. NSC 0592

In the thread "EB1-A RFE with 0/4" (r/USCIS) and related posts, a stream of identical complaints about one officer at the Nebraska Service Center with number 0592 has gathered:

• u/ExpressionHappy5136: "same officer and officer only approved 2/3. Responded to the RFE and recently got denial."
• u/iaskgpt: "Same officer. Got 1/6 during RFE."
• u/BUTAIMO: "Sorry to hear. I'm on the same boat with Nebraska Center officer 0592. Got an RFE this Friday claiming 0 of the criteria were met."
• u/Grief_2022: "I am in the same boat with Nebraska officer 0438 who granted 0 out of 6 criteria."

A cluster of identical harsh denials from one officer illustrates either AI clustering of cases "by complexity," or simply a human cluster denial pattern of one harsh officer. It is impossible to distinguish without FOIA on the specific officer.

Balancing voice. Former USCIS supervisor

This is a critically important source for an honest article. u/WatkinsImmigration - immigration attorney and former USCIS supervisor. His post "A Fresh Perspective on USCIS After 6 Months on the Outside" (April 12, 2026, 109 upvotes, 34 comments) confirms patterns of sloppy adjudication, but refutes the thesis of direct AI adjudication:

u/WatkinsImmigration, former USCIS supervisor, April 12, 2026, 109 upvotes
"Adjudication: Poor, sloppy decisions and work being sent out by officers. This has been maybe the biggest shock to me so far. Even with using templates for large portions of writing, officers are still regularly misstating facts, forgetting to include large portions of required analysis, citing incorrect case law, and even leaving template language."
Translation: adjudication - poor, sloppy decisions and work being sent out by officers. This has been maybe the biggest shock to me so far. Even using templates for large portions of writing, officers regularly misstate facts, forget to include large portions of required analysis, cite incorrect case law, and even leave template language.

u/WatkinsImmigration, the same post - about AI
"AI: No, USCIS is not using AI to adjudicate your case. No, officers are not using it to write poorly written RFE/NOID/Denials. USCIS publicly lists their AI usage [link to dhs.gov/ai/use-case-inventory/uscis] and to the best of my knowledge, this is and remains accurate. I would look for expanded AI usage in vetting and evidence collection areas and cannot see any widespread usage for adjudication anytime soon."
Translation: USCIS is not using AI to adjudicate your case. Officers are not using it to write poorly written RFE/NOID/Denial. USCIS publicly lists its AI usage, and to the best of my knowledge, this remains the case. I would expect expanded AI in the areas of vetting and evidence collection, but I do not see widespread usage for adjudication in the foreseeable future.

This source is important because the person worked inside and is currently not bound by DHS gag rules. Their position: the patterns of RFE are explained not by AI, but by the sloppy work of human officers with templates and lack of training. This is an alternative explanation that the article must consider.

At the same time, the same source provides a detail about training inequality:

u/WatkinsImmigration, the same post - about training
"The NBC adjudication guide and training PowerPoint for new officers working the I-765 (c)(11) parole-based EAD category were over 100 pages and 200 slides long respectively. The I-140 EB-1A PowerPoint is 83 slides and new officers get a basic, 3 page long adjudication table."
Translation: The NBC (National Benefits Center - the national center of USCIS processing forms like I-765) adjudication guide and training PowerPoint for new officers working with I-765 (c)(11) (this is the form for work authorization, EAD - Employment Authorization Document) is over 100 pages and 200 slides long respectively. The PowerPoint for I-140 EB-1A is 83 slides, and new officers receive a basic adjudication table that is 3 pages long.

This means that the officer reviewing your EB-1A petition has 30 times less training material than the officer for EAD (Employment Authorization Document - work authorization). This is the best non-AI explanation of the "AI-pattern RFE" patterns.

LinkedIn of lawyers. The strongest posts

Ksenia Maiorova. Direct statistics of AI citations

Ksenia Maiorova, Green & Spiegel (Orlando), LinkedIn, February 2026, 138 likes
"AI can summarize a decision. A lawyer understands what part of it is binding law. About ninety percent of cited cases do not actually support the proposition claimed. Once a case receives an RFE, approvals fall to roughly 30%. When the government misapplies the law, you need someone who knows how to challenge it."
Translation: AI can summarize a decision. A lawyer understands which part is binding law. About 90% of cited cases do not actually support the claimed proposition. Once a case receives an RFE, approvals drop to about 30%. Source LinkedIn.

In the discussions of this post, Maiorova describes LLM markers in RFE: "opine", "juxtapose", "flowery language", "aggressive wording" - atypical for USCIS officers, but characteristic of language models. She claims that her firm's internal statistics, when the law is applied correctly, are about 92% (twice the public 46% of USCIS).

Dobrina Ustun. Ready headline

Dobrina M. Ustun, immigration attorney, LinkedIn, March 2026, 63 reactions
"EB-1A and NIW approval rates have dropped below 50%. Let that sink in for a second. Half of these petitions are failing. We are at an absurd moment in immigration law - AI-generated petitions being reviewed by AI-generated RFEs, with a real human's life and career caught in the middle."
Translation: EB-1A and NIW approvals have dropped below 50%. Half of these petitions are failing. We are at an absurd moment in immigration law - AI-generated petitions are being reviewed by AI-generated RFEs, with a real person’s life and career caught in the middle. Source LinkedIn.

Ryan Wilck (Reddy Neumann Brown). January 2025 as a Turning Point

Ryan A. Wilck, Reddy Neumann Brown PC, January 2026
"AI hallucination occurs when an artificial intelligence system generates output that appears authoritative but is factually incorrect, internally inconsistent, or untethered from the actual input data... premium processing for discretionary petitions, particularly EB-1A and EB-2 NIW... has increasingly become a fast track not to approval, but to RFEs... paying $2,805 for an RFE that will not be substantively considered."
Translation: AI hallucination is when AI generates output that seems authoritative but is factually incorrect, internally inconsistent, or detached from the input data. Premium processing for discretionary petitions, especially EB-1A and EB-2 NIW, is increasingly becoming a fast track not to approval, but to RFEs. $2,805 for an RFE that will not be substantively considered. Source Reddy Neumann Brown.

Wilck calls January 2025 a turning point - coinciding with EO 14179 Trump (January 23, 2025, "Removing Barriers to American Leadership in AI") and OMB M-25-21 (April 3, 2025, replaced the stricter Biden rules M-24-10).

Oleg Gherasimov (SG Legal). What AI Does Not Do

Oleg Gherasimov, SG Legal Group, April 2026
"USCIS artificial intelligence is operational today. The systems described in the DHS inventory are not in testing. Human adjudicators retain final decision-making authority. AI systems do not grant or deny immigration benefits. These systems identify deviations from expected patterns. They do not evaluate your explanation."
Translation: USCIS AI is operational today. The systems described in the DHS inventory are not in testing. The final decision remains with the human adjudicator. AI does not grant or deny immigration benefits. These systems identify deviations from expected patterns. They do not evaluate your explanation. Source SG Legal.

Former USCIS Asylum Officer. Direct Description of Workflow

The most valuable insider publication is the article Joshua Perez Garcia on ILW.com (an online publication for immigration lawyers, May 11, 2026). The author's bio is confirmed verbatim in the article: "Joshua Perez Garcia served six years as a federal adjudicator with U.S. Citizenship and Immigration Services as an Asylum Officer, Humanitarian Parole Officer, and Senior Refugee Officer."

That is, 6 years in USCIS in three roles: asylum officer, humanitarian parole officer, and senior refugee officer. Trained in the RAIO Combined Training Program (Refugee, Asylum and International Operations - a unified training program for USCIS officers working with refugees, asylum, and international affairs). After leaving, he founded BiyteLüm - expert witness (expert testimonies in court) and AI compliance advisory (consulting on AI compliance requirements). Not a lawyer.

Joshua Perez Garcia, former USCIS Asylum Officer (6 years), ILW.com, May 11, 2026
"The flag does not announce itself as AI. There is no banner identifying the alert as the output of a machine-learning model."
Translation: the flag does not announce itself as AI. There is no banner identifying the alert as the output of a machine-learning model. According to Perez Garcia's description in the same article, the alert is presented to the officer as a regular notification from the Asylum Text Analytics system with highlighted matching text passages - meaning the officer does not see an explicit label "this was said by AI." Source ILW.com.

Joshua Perez Garcia - on the cognitive effect on the officer
"an alert created a bigger possibility of fraud, even where fraud might not be present, and that shifted the questions the officer was more likely to ask"
Translation: the alert created a greater possibility of fraud, even where fraud might not be present. The alert shifted the baseline... which shifted the questions that the officer was more likely to ask. What the flag changes operationally is the focus of the investigation. - This is the first public description of automation bias (a cognitive error where a person overly trusts automated systems to the detriment of their own judgment) from a verified former USCIS adjudicator.

Joshua Perez Garcia - about the opacity for the applicant
"The officer has seen what the system surfaced; the applicant and attorney have not. The NOID does not disclose it. The denial letter does not disclose it. The administrative record may not disclose it."
Translation: the officer has seen what the system highlighted; the applicant and attorney have not. The NOID does not disclose this. The denial letter does not disclose this.

The second verified voice - Morgan Bailey, former USCIS, in the Mayer Brown podcast (December 2025):

Morgan Bailey, former USCIS, Mayer Brown podcast, December 2025
"The system is beginning to rely more on automation to organize information and detect patterns to support decision making by immigration officers, and AI is increasingly influencing what information reaches them and how that information is presented."
Translation: the system is increasingly relying on automation to organize information and detect patterns to support decision-making by immigration officers, and AI is increasingly influencing what information reaches them and how it is presented. Source Mayer Brown.

The third insider. Robert Ratliff, former Immigration Judge

The third and highest-ranking insider voice. Robert Ratliff is a former Immigration Judge with over 25 years of experience in criminal defense and immigration law. He is currently a Member at the firm Brennan, Manna & Diamond. He published a detailed client alert "Invisible Algorithms: The Hidden Role of Artificial Intelligence in USCIS Immigration Processing" on February 10, 2026.

Title of the publication by Brennan, Manna & Diamond from February 10, 2026: "Invisible Algorithms: The Hidden Role of Artificial Intelligence in USCIS Immigration Processing". Author - Robert Ratliff, former Immigration Judge with over 25 years of experience. This is not a journalistic piece or an activist publication - it is a formal client alert from a law firm for business clients. The fact that a former judge publicly writes about "invisible algorithms" in USCIS is a strong signal that the issue is taken seriously from within the immigration system. Source BMD Law.

If Joshua Perez Garcia described the picture from the level of an asylum officer at USCIS, and Morgan Bailey from the level of USCIS staff, then Ratliff writes from the perspective of someone who has sat in the judge's chair for years and decided immigration cases. This is a position that sees the system from above and understands what automation means for due process.

Key theses from Ratliff that add to the picture:

Robert Ratliff, former Immigration Judge, BMD client alert, February 10, 2026
"Artificial intelligence can affect which files are reviewed first, which issues are highlighted, how evidence is grouped, or which elements of an application receive greater attention. In cognitive science, this is often described as shaping the decision environment. The order in which information is presented and the signals associated with that information can influence human judgment."
Translation: AI influences which cases are reviewed first, which issues are highlighted, how evidence is grouped, and which elements of a petition receive more attention. In cognitive science, this is called "shaping the decision environment." The order in which information is presented and the signals associated with that information influence human judgment. Source BMD Law.

This is the key mechanism of the problem. AI does not formally make decisions but creates an informational environment in which a person decides. And this environment is skewed in a certain direction.

Ratliff also provides a scale figure that explains the institutional pressure towards automation:

Robert Ratliff, BMD client alert, February 10, 2026
"As of Q3 FY2025 (April-June 2025), USCIS reported a pending application number of over 11 million cases across all application types."
Translation: as of the third quarter of fiscal year 2025, USCIS has over 11 million pending applications across all types. This scale explains why the agency is forced to implement automation even if governance has not yet matured.

And one more important reference that was not in our previous picture - the official position of AILA:

Robert Ratliff quotes AILA
"The American Immigration Lawyers Association (AILA) has documented patterns of inconsistent adjudication where reasoning in the record does not always align with submitted evidence."
Translation: AILA has documented patterns of inconsistent adjudication where the reasoning in the record does not always correspond to the submitted evidence. This is not just one or two lawyers; it is the official position of the professional association of immigration lawyers in the United States.

Ratliff also provides a specific case from practice that has not been mentioned before. One lawyer reported that the approval notice for his client was sent "to the address of a third party completely unrelated to the applicant." This is not an RFE pattern; this is already a level of administrative error in the issuance of the decision - it seems that the automated document-handling system directed the official approval notice to a completely unrelated person.

The full material is worth reading in its entirety - it also discusses the transparency paradox in administrative law (full disclosure of AI criteria will allow applicants to tailor documents, undermining fraud detection; minimal disclosure does not allow courts to assess decisions) and parallels with other failures of AI in government agencies (COMPAS in criminal justice, automated unemployment fraud systems in several states, healthcare authorization algorithms in Medicare Advantage).

Three insiders, one pattern

Let's summarize. We have three verified former employees of the immigration system who independently describe the same picture:

• Joshua Perez Garcia (former Asylum Officer USCIS, 6 years) describes at the level of a rank-and-file officer: the ATA alert "shifted the baseline," changing the types of questions the officer was prepared to ask. The algorithm did not order a denial - it shifted the cognitive focus.
• Morgan Bailey (former USCIS staff) describes at the organizational level: AI increasingly influences "what information reaches the officers and how it is presented."
• Robert Ratliff (former Immigration Judge, 25+ years) describes at the systemic level: AI shapes the "decision environment" - order, allocation, grouping, emphasis. This is the mechanism through which automation changes outcomes even when the final decision is formally made by a person.

These are not three separate complaints. This is the same phenomenon described from three different positions in the hierarchy. The coincidence of three independent insiders is stronger than any observations from the outside - by lawyers or activists.

Judicial precedent. Mukherji v. Miller

This is the latest and potentially most important finding. Mukherji v. Miller et al, No. 4:24-cv-03170 (D. Neb.) - the case of Indian journalist Anahita Mukherji regarding EB-1A in the U.S. District Court for the District of Nebraska, decision dated January 28, 2026. Presided over by Senior Judge Joseph F. Bataillon. Defendants: Loren K. Miller and Ur Mendoza Jaddou (USCIS officials in their official capacity, not personally):

Cyrus Mehta - emphasis on Loper Bright
Murthy Law Firm (January 29, 2026)
Fennemore Law - questions regarding the Kazarian framework
Full docket on PacerMonitor

What the cited USCIS cases say

It is worth noting the pattern of systematic misquoting of case law in RFEs for EB-1A/O-1. This has been documented by The Seltzer Firm. USCIS extensively cites the following cases in RFEs:

• Silverman v. Eastrich Multiple Investor Fund, L.P., 51 F.3d 28 (3d Cir. 1995) - this case is actually about default on a $10M loan and the Equal Credit Opportunity Act. It has no relation to "extraordinary ability" or immigration. USCIS cites it as justification for the high threshold of "original contributions of major significance" (detailed in my post "Original Contribution 2026: only 4% approvals - how to prove it").
• APWU v. Potter, 343 F.3d 619 (2d Cir. 2003) - this case is actually about the anthrax investigation in post offices. It is cited in EB-1A RFEs.
• Visinscaia v. Beers, 4 F.Supp.3d 126 (D.D.C. 2013) - about a Moldovan ballerina, denial. It is mischaracterized in the RFE: the cited holding was narrow, but in templates it turns into "influence on the field as a whole".
• Matter of Caron International, 19 I&N Dec. 791 (Comm. 1988) - selectively cited without the limiting context of Matter of Skirball.

This may be officer templates. It may be PAiTH hallucinations. It may be a combination. It is currently impossible to distinguish without leaked prompts.

Detailed analysis from Reddit. Specific RFE patterns in the AI field

I am systematizing what the Reddit community has written about AI petitions and AI RFEs. All URLs were checked through old.reddit.com on May 25, 2026 - these are real threads, not fabricated.

"Be Careful Using AI". Debates among former USCIS employees

In July 2025, u/WatkinsImmigration (the same former supervisor I quoted above) posted in r/eb_1a a screenshot from Bluesky from a former USCIS colleague who now works with EB-1 petitions. A quote from her Bluesky post:

Screenshot from Bluesky by a former USCIS employee, reposted by u/WatkinsImmigration, July 2025, 14 upvotes, 16 comments
"According to two attorneys and my employer's legal representative, USCIS is utilizing artificial intelligence to evaluate applications and issue Requests for Evidence (RFEs) as the premium processing period comes to a close."
Translation: according to two attorneys and my employer's legal representative, USCIS is using AI to evaluate applications and issue RFEs as the premium processing deadline approaches. Source Reddit.

Watkins himself provides a direct rebuttal in the same thread:

u/WatkinsImmigration, response in his own thread
"Well, unfortunately those attorneys are wrong. USCIS is required and does list all of their AI here: dhs.gov/ai/use-case-inventory/uscis"
Translation: unfortunately, those attorneys are wrong. USCIS is required and indeed lists all of its AI right here: link to DHS inventory.

This is the very discussion happening in the community: some believe that AI is writing RFEs right now, while others (including insiders) point to the official list where adjudication-AI is simply absent.

"AI Detection systems on your application". One documented case

Thread "USCIS will use AI Detection systems on your application", r/eb_1a, October 2025
"I have only seen one RFE complaining about 'possibly AI generated articles' but it can be refuted... I haven't observed USCIS formally identifying anyone for using AI-generated material, and to be honest, the reliability of AI detection tools is questionable at best."
Translation: I have only seen one RFE complaining about "possibly AI-generated articles," but this can be refuted. I have not observed USCIS formally identifying anyone for using AI-generated materials, and to be honest, the reliability of AI detection tools is questionable. Source Reddit.

So as of May 25, 2026, there is only one RFE with a direct accusation of "AI-generated articles" recorded in open discussions. And this one RFE, according to the user, was able to be refuted.

"RFE misclassification issue". USCIS classified AI as "Science"

This is one of the most valuable cases in terms of illustrating mis-tagging:

u/[author], r/eb_1a, January 2026, thread "RFE misclassification issue"
"USCIS misclassified my field as 'Science' instead of my actual field, Artificial Intelligence - which distorted their interpretation of citations."
Translation: USCIS misclassified my field as "Science" instead of my actual field - Artificial Intelligence - which distorted their interpretation of citations. Source Reddit.

What does "distorted the interpretation of citations" mean: benchmarks (citation norms) in the field of AI are completely different than in general "Science." What is in the top 3% of work in AI may look like an average result in general "Science." The ML classifier labeled it "Science," and the officer compared citation counts with an inappropriate norm.

"Split endeavor". Machine error due to commas

u/Any-Bed8987 (author of the previously discussed thread "USCIS AI agent review"), r/eb_1a, April 2026
"The endeavor had few connected fields but separated by comma and it took them as 3 different endeavours. So the main point was: 'any of your evidence cover all these 3 endeavours.'"
Translation: my proposed endeavor had several related fields, separated by commas, and they took this as 3 different endeavors. The main complaint in the RFE was: "none of your evidence covers all 3 endeavors." Source Reddit.

This resembles a typical parser error that reads text linearly: commas separate a list - therefore, these are different elements. A human would not think this way. ML will think.

r/EB2_NIW. Increase in denial rate since January 2025

In April 2025, a thread titled "What's going on with NIW recently?" appeared in r/EB2_NIW:

Thread "What's going on with NIW recently?", r/EB2_NIW, April 2025

"A PhD in Computer Science, employed at a FAANG company in a research role, with over 100 citations - still received a three-prong RFE." Translation: PhD in Computer Science, working at FAANG in a research role, over 100 citations - still received a three-prong RFE (RFE on all three prongs of the Dhanasar test, meaning USCIS objected to all three points at once). Source Reddit.

In August 2025, the thread "Denials and More Denials Happening" gives a stark figure:

Thread "Denials and More Denials Happening", r/EB2_NIW, August 2025

"EB-2 NIW denial rates hit 57% in 2025! USCIS officers have complete discretion to deny any case." Translation: the denial rate for EB-2 NIW reached 57% in 2025. USCIS officers have complete discretion to deny any case. Source Reddit.

An important contrast in the August thread "Are we seeing more RFEs and Denials":

Thread "Are we seeing more RFEs", r/EB2_NIW, August 2025

"Many self-petitioners are utilizing AI tools to draft their applications - this shift has led to a noticeable decline in the quality of submissions, with supporting evidence becoming less robust." Translation: many self-petitioners are using AI to prepare applications - this has led to a noticeable decline in the quality of submissions, with supporting evidence becoming less reliable. Source Reddit.

This quote provides an alternative explanation for the increase in denials: not "the AI of officers has gotten worse," but "AI-prepared petitions from self-petitioners have become weaker." In discussions, both explanations coexist.

Balancing Case. AI Petition Approved Without RFE

In March 2026, a thread "I140 Approved on 43rd Business day" appeared in r/EB2_NIW:

Thread "I140 Approved on 43rd Business day after PP, Industry and AI PE", r/EB2_NIW, March 2026

"Being in AI does NOT automatically mean RFE. A late decision in premium processing does NOT mean RFE." Translation: working in AI does NOT automatically mean RFE. A late decision in premium processing (on the 43rd business day) does NOT mean RFE. Source Reddit.

This is an important balancing voice: being in the AI field is not a death sentence. What matters is the quality of the argumentation, not the mere fact that you are in AI.

r/I130Suffering. A List of What AI USCIS Does

In December 2025, a detailed analysis "USCIS has ADMITTED to Using AI to Evaluate I-129F/I-130 Petitions" appeared in r/I130Suffering. This is about fiancé and family-based visas (not EB-1A), but the description of AI functions is applicable to all forms:

Thread "USCIS has ADMITTED to Using AI", r/I130Suffering, December 2025

"AI is notorious for generating false positives - a bad thing for applicants since this means false flags. Any submission that triggers an AI alert can create obstacles long before a human actually reviews your case." Translation: AI is notorious for generating false positives - for applicants, this means false flags. Any submission that triggers an AI alert can create obstacles long before a human actually reviews your case. Source Reddit.

The thread lists specific functions that AI USCIS performs:

• Document Categorization - automatic tagging of evidence;
• Pattern Detection - matching "scripted stories" between unrelated cases → flag fraud;
• Relationship Linkages - ML analysis of networks: address, employer, relatives;
• Inconsistency Flagging - cross-checking dates and facts with government databases → RFE.

What the Community Proposes. Visalytics - An Attempt to Use AAO Decisions

In April 2026, a post "I scraped 2,500+ EB-1A petition decisions from USCIS" appeared in r/eb_1a:

Thread "I scraped 2,500+ EB-1A petition decisions", r/eb_1a, April 2026
"I'm a data engineer working on my own immigration case. I scraped AAO appeal decisions from USCIS and thousands of approved case studies... It matches you to similar decided cases, demonstrating how different profiles yield different results."
Translation: I am a data engineer working on my immigration case. I scraped AAO decisions from USCIS and thousands of approved petition cases... The tool matches you to similar already decided cases and shows how different profiles yield different results. Source Reddit.

The tool is called Visalytics.com. This illustrates that the community is starting to build its own AI/ML tools to understand USCIS patterns - that is, AI against AI.

Summary Table of RFE Patterns in the AI Field

• Myth "AI field = automatic RFE" - disproven by real approval case studies (r/EB2_NIW, March 2026). The quality of argumentation actually matters.
• Misclassification of fields (AI → "Science") - documented in r/eb_1a (January 2026). Recipe: the first section of the RFE response should redefine the context of the field.
• Split endeavor due to commas - a typical parsing error, recorded in r/eb_1a (April 2026).
• "AI-generated articles" accusation - one RFE recorded, easily disproven (r/eb_1a, October 2025).
• National importance (proving 2 Dhanasar) - the main trigger for AI fields. Requirements: adoption by other companies, economic return, alignment with national AI initiatives.
• False positive from ELIS Classifier - legally documented (Cozen O'Connor). Remedy: clear document structure, explicit Table of Contents.
• Revocation of already approved cases - r/eb_1a, 2025. USCIS revoked EB-1A based on fraud. Remedy: do not use predatory journals and fake conferences.

What Reddit Clearly Shows

Q3 FY2025 Numbers. AI vs Discretionary Part of Adjudication

If we look at USCIS approval statistics for the third quarter of the 2025 fiscal year - there is a strange asymmetry that can only be explained through the hypothesis of AI intervention.

According to the aggregation of Manifest Law and Boundless USCIS data:
Q3 FY2025 (April-June 2025):
EB-1A approval rate: 66.6% - the lowest in 3 years, a drop of 8.4% for the quarter
EB-2 NIW approval rate: 54% - a drop of 13 points
O-1 approval rate: 93.8% - virtually unchanged (RFE rate 18.7% YTD vs 30% in 2020)
Q4 FY2025 (July-September 2025) - even worse (according to Manifest Law from USCIS performance data):
EB-1A: 53.4% (2,331 approved / 4,364 reviewed) - "the lowest quarterly approval rate for EB-1A in recent years"
EB-2 NIW: 35.7% (2,968 approved / 8,324 reviewed) - "more petitions were denied than approved for the first time in recent memory". This is the first time in modern NIW history: denials outnumber approvals.
NIW dynamics within FY2025: Q1 62.7% → Q4 35.7%. A drop from 95.7% in FY2022 to 55.2% for the full FY2025 - a nearly threefold collapse.

AI intervention. The hypothesis of this article. There is correlation, causality cannot be proven without FOIA.
NIW boom 2022-2024: an influx of weak self-petitions after the liberal interpretation of Dhanasar. "The pool of applicants has become weaker," not "USCIS has become worse."
Trump policy shift from January 2025: EO 14179. This is policy, not AI.
SCOPS centralization of EB-1A: transfer to Service Center Operations - lengthening of processing times, increase in denials, not related to AI.

Without FOIA, it is impossible to separate the contribution of each factor. AI tools exist, and the decline coincides with the expansion of their use - this is coincidence, not proof.

What is strange about these numbers. The EB-1A and EB-2 NIW categories require discretionary assessment - the officer must decide whether the applicant meets the "extraordinary ability" or "national importance" criteria based on the totality of evidence. This is not a mechanical checklist, it is a qualitative judgment. And it is precisely these two categories that have collapsed.

The O-1 category requires a more mechanistic check: whether formal criteria are met (has the applicant received any awards, published a certain number of articles, worked in a leading role). This can be checked almost by checklist. And it is precisely O-1 that maintains a 93.8% approval rate.

Specific AI patterns from legal practice. What lawyers are actually seeing

In addition to general complaints, lawyers document specific technical patterns that can only be explained by automation.

Same-day RFE. Technically impossible for manual review

Herman Legal Group in the review "USCIS artificial intelligence 2026":

Herman Legal Group, "USCIS artificial intelligence 2026"
"In several concurrent adjustment filings - including Form I-485, Form I-130, Form I-864, Form I-765 - we received receipt notices and RFEs issued the same day."
Translation: in several concurrent AOS cases (Adjustment of Status - changing status to a green card from within the US through forms I-485, I-130, I-864, I-765) we received receipt notices and RFEs issued on the same day. Source Herman Legal.

Herman Legal Group, the same material
"The emergence of same-day RFEs - issued effectively simultaneously with receipt generation - suggests something different: Automated intake screening may be parsing I-864 data immediately upon digitization."
Translation: the emergence of same-day RFEs - issued effectively simultaneously with receipt generation - suggests something different: automated intake screening may be parsing I-864 data immediately upon digitization.

What this means in simple terms. Receipt notice (notification "USCIS has received your petition") and RFE on the same day - this is technically impossible for manual processing. An officer physically cannot read the petition and write an RFE in a few hours. If this happened - it means the RFE was generated automatically during the digitization of documents, even before a person looked at them.

Officer codes as a community metric. Case XM2532

The Reddit community maintains informal lists of "bad officers" by their codes (XM-codes - this is the prefix for USCIS officer ID). This is useful because it shows: even if AI generates a draft RFE, different people approve it differently. A separate example - my detailed analysis of cases from officer 0413 (EB-1A) with 27 patterns and 6 real RFEs. A specific documented case - officer TSC XM2532:

WeGreened Law Group, success story on NIW
"On March 22, 2024, USCIS issued a Request for Evidence (RFE) signed by Officer XM2532, challenging all three prongs of the NIW test... The AAO returned the case to the original service center for reconsideration on April 4, 2025, effectively vacating the initial denial... the client got his I-140 NIW approval on July 9, 2025."
Translation: On March 22, 2024, USCIS issued an RFE signed by Officer XM2532 (TSC - Texas Service Center, one of the regional centers of USCIS), challenging all three prongs of the NIW test (Dhanasar). The AAO (Administrative Appeals Office - the internal appellate body of USCIS) returned the case back to the service center for reconsideration on April 4, 2025, effectively overturning the initial denial. The client received I-140 NIW approval on July 9, 2025. Source WeGreened.

Client Profile: postdoctoral researcher integrating deep learning and numerical modeling for predicting coastal hazards - that is, a direct AI/ML expert working on disaster mitigation. And still, Officer XM2532 denied all three prongs. The AAO returned the case for reconsideration after 13 months.

What this means at the article level. The Reddit community tracks patterns through officer codes because - if all officers applied standards equally - there wouldn't be such clusters of denials from one officer. This is either human bias of one person or an AI tool that this officer uses more than others. It is impossible to distinguish without a FOIA on a specific officer.

Greenberg Traurig. The shortest formulation of what is happening

Kate Kalmykov, Co-Chair Global Immigration & Compliance Practice, Greenberg Traurig, February 2026
"The future of U.S. immigration adjudications is not just digital - it is algorithmic."
Translation: the future of immigration adjudication in the U.S. is no longer just digital - it is algorithmic. Source Greenberg Traurig.

This is one of the largest law firms in the U.S. (Greenberg Traurig - Top 15 by revenue). When such a source publicly states "algorithmic," it means that their client base has already accumulated enough confirmations to make such a statement publicly.

Mukherji v. Miller. Details that show the scale

Returning to the case I have already written about, but with specifics that were not available before. The plaintiff is Anahita Mukherji, an Indian journalist. She satisfied 5 out of 10 regulatory criteria for EB-1A - that is, 1.6 times more than the formal minimum (3 are needed). USCIS still denied.

Reddy Neumann Brown in the analysis of the decision:

Reddy Neumann Brown PC, analysis of Mukherji v. Miller, January 2026
"the court ordered USCIS to approve the applicant's EB-1A petition outright, rather than send the case back"
Translation: the court ordered USCIS to approve the EB-1A petition of the applicant outright, rather than send the case back for reconsideration. - This is an extremely rare judicial decision. Usually, courts send cases back with instructions. "Outright approval" means the judge saw such an arbitrary denial that he did not even trust USCIS to correct it.

DOJ filed a notice of appeal on March 27, 2026, in the U.S. Court of Appeals for the 8th Circuit, case No. 26-01578. The decision is still district, not circuit - but as a precedent, this is the first time a federal court after Loper Bright (2024) told USCIS "you did not just make a mistake in one case, your EB-1A evaluation system is itself arbitrary and capricious." In the appeal, the 8th Circuit can either affirm (which will strengthen the precedent in the region) or overturn (which will return the Kazarian framework as it was). The decision is expected in 2026-2027.

Why I look at ICE and CBP when writing about USCIS

One argument often heard in defense of USCIS: "AI is only auxiliary for them - processing PDFs, translation, classification. There is still a long way to go before evaluating petitions substantively." To understand how robust this argument is, one needs to look at neighboring components of DHS. If in ICE and CBP the official formula "AI only assists humans" has already blurred into facial recognition without privacy assessment and into LLM processing of reports - this changes the forecast for USCIS as well.

All three facts below are not directly about EB-1/O-1/NIW. But they demonstrate the methodology of DHS - how AI systems are deployed, how they are revealed, and what the chance is that something similar is already working within USCIS adjudication but is not publicly disclosed.

Hurricane Score. The same formula that protects AI in USCIS

In November 2024, DHS Chief AI Officer Eric Hysen revealed the existence of the Hurricane Score - an algorithm ranking immigrants on a scale of 1-5, in response to a letter from Just Futures Law (the same organization that filed the lawsuit Pangea v. USCIS).

Eric Hysen, DHS Chief AI Officer, letter Just Futures Law, November 2024
"The Hurricane Score does not make decisions on detention, deportation, or surveillance; instead, it is used to inform human decision-making."
Translation: Hurricane Score does not make decisions on detention, deportation, or surveillance; instead, it is used to inform human decision-making. Source AP via ABC17 News.

Why this is important for EB-1/O-1/NIW. The formula "AI assists the human, the final decision is made by the human" is the same formula that DHS uses to defend the ELIS Evidence Classifier, PAiTH Legal Persona, and any other system related to your petitions. Hurricane Score shows that this formula has already blurred in practice: the algorithm assigns you a score, the officer most often agrees, the balance shifts.

Joshua Perez Garcia described exactly this in his article - automation bias is a real mechanism, not a theoretical threat. For an EB-1A applicant, this means that when USCIS says "PAiTH only suggests to the officer" - we already have a precedent in a related DHS system where "suggestion" turns into a de-facto decision.

Mobile Fortify. The methodology of "hidden deployment → disclosure" applies to USCIS

In January 2026, Wired published an investigation based on the DHS 2025 AI Use Case Inventory: ICE and CBP had already used the Mobile Fortify application for facial recognition since June 2025. The vendor is Japanese NEC (NeoFace). The contract is approximately $23.9 million. It was used over 100,000 times before public disclosure.

• Database: 1.2 billion face photos for matching;
• Privacy Impact Assessment not conducted before deployment;
• Photos of U.S. citizens are also stored - for 15 years;
• A lawsuit from the state of Illinois and Chicago regarding the illegality of its use has already been filed.

Sources: Wikipedia with Wired citations, Biometric Update, FedScoop.

Why this is important for EB-1/O-1/NIW. Mobile Fortify is enforcement (ICE/CBP), not adjudication (USCIS). But the disclosure scenario is important: a high-risk AI system is deployed without a PIA, operates for over 7 months in silence, and surfaces through a combination of (1) annual AI inventory updates, (2) leaked emails in 404 Media, (3) Wired investigation, (4) lawsuits.

If something similar is working within USCIS adjudication for EB-1A/NIW (for example, some classifier that influences the final merits determination more strongly than stated) - it will likely surface in the same way in the next 12-24 months. Active FOIA lawsuits Pangea v. USCIS and Refugees International v. USCIS are precisely the part of the path that is already underway.

AI Enhanced ICE Tip Processing. Precedent for using commercial LLM in immigration workflow

From the same DHS AI Inventory January 2026 - ICE has been using a Palantir tool since May 2025 to process the flow of anonymous tip submissions from the public:

FedScoop, January 2026, based on DHS AI Inventory

"It uses generative AI to summarize public tip submissions, translate messages written in other languages, and generate short 'bottom line up front' summaries that help agents decide which tips require immediate attention... DHS records say the system relies on commercially available large language models trained on public data, with no additional training on ICE-specific records."
Translation: it uses generative AI to summarize tip submissions, translates from other languages, generates short "bottom line up front" summaries helping agents decide which tips require immediate attention. DHS states: the system relies on commercially available LLM trained on public data, without additional training on ICE-specific records.

Why this is critically important for EB-1/O-1/NIW. ICE officially uses commercial LLMs (the same class as ChatGPT, Claude, Gemini) within the immigration workflow for classification and summarization. This created an institutional precedent that commercial LLMs are permissible in DHS workflows. The PAiTH Legal Persona in USCIS (Pre-deployment status) functionally does the same - generates summaries of petition documents and draft legal memoranda.

When USCIS transitions PAiTH from Pre-deployment to Deployed (which is a matter of months, not years) - the only formal boundary remaining between AI processing of ICE tips and AI processing of your EB-1A petition from an architectural standpoint will be "the final decision is made by a human." The same boundary that is already blurring in the case of Hurricane Score.

What to do right now. Practical takeaways for EB-1A, O-1, EB-2 NIW applicants

These recommendations work regardless of whether your petition is processed by AI or a human. They protect against both scenarios.

1. Submit your dossier in a format optimized for ML-classifiers

Clear exhibit-tabs (tabs for each application-evidence) with labels in English. Each piece of evidence - a separate PDF or clearly separated section. Attach a Table of Contents with explicit categorization by the 10 Kazarian criteria (for EB-1A) or the 3 prongs of Dhanasar (the three prongs of Dhanasar - this is the case Matter of Dhanasar, 26 I&N Dec. 884 (AAO 2016), which established the triple test for EB-2 NIW: substantial merit + national importance, well-positioned to advance, balance of factors favors waiver - detailed guide: "EB-2 NIW (1) 2026: complete guide") or the 8 criteria for O-1.

There are detailed analyses for each of the 10 EB-1A criteria on the forum: awards, membership, publications, judging, original contribution, articles, leading role, salary.

2. File names are critical

Recommendation_Letter_Dr_Smith_Harvard.pdf, not scan_001.pdf. The ELIS Classifier uses names and content for tagging.

3. OCR layer in all PDFs

An OCR layer is a text layer that a computer can read as text, not an image. No "ghost text" (hidden text - Cozen explicitly calls this a trigger for cross-document mismatch). 300 DPI (dots per inch - scanning density) minimum for scans.

4. Attach certified human translations

Do not rely on USCIS internal Azure translation. Attach certified human translations with a certificate of accuracy (a formal document from the translator confirming that the translation is accurate) per 8 CFR § 103.2(b)(3) for Russian awards, diplomas, media publications. This is legally required AND neutralizes the risk of AI-mistranslation (AI incorrect translation).

5. Russian transliterations

Attach an explicit name variation memorandum in each petition with all variations of name transliteration according to GOST (Russian standard), ISO 9 (international ISO standard), BGN/PCGN (Board on Geographic Names standard used in American passports). Explain possible false matches in ATLAS in advance.

6. Uniform job titles in ALL documents

Cross-document mismatches trigger flags.

7. EB-1A in premium processing - risky in 2026

According to Reddy Neumann Brown's recommendation - avoid premium processing except for critical deadlines.

8. Upon receiving an RFE - verify EVERY citation of case law

The pattern of systematic misquoting (Silverman, APWU, Visinscaia, Caron International) is documented. This may be a PAiTH hallucination.

9. Use phrasing from the DHS AI Use Case Inventory

In each entry, the DHS Inventory AI tool is marked as a "decision support tool" - not as an autonomous decision-maker. In response to an RFE, one can directly reference the DHS inventory and demand that the final decision be made by an officer considering all presented evidence, rather than being delegated to a machine.

Where to Watch for Updates

1 DHS AI Use Case Inventory
Updates every six months. Particularly: will the PAiTH Legal Persona be in Deployed status (currently Pre-deployment). And will they "reclassify" the ELIS Evidence Classifier from a regular system to High-Impact.

2 Pangea v. USCIS and Refugees International v. USCIS
Productions may contain prompts, training data, contracts. Any court order in these cases is a turning point.

3 Cozen O'Connor, Reddy Neumann Brown, Greenberg Traurig
Next RFE alerts. If patterns strengthen - it means AI is being applied more broadly.

4 Reddit r/EB1, r/USCIS, Trackitt
First accounts of RFEs that cite non-existent court cases (smoking gun for AI hallucination in RFEs).

5 SAM.gov and USAspending.gov
New USCIS contracts with AI vendors. Particularly: will they expand the VOWS contract with Palantir from marriage fraud to employment-based categories.

6 USCIS GitHub
github.com/USCIS - currently almost empty. If repositories with ML models appear - it will be an unexpected self-disclosure.

Brief Summary

1. USCIS Officially Uses AI/ML in Petition Processing

This is publicly confirmed by the DHS AI Use Case Inventory: 29 USCIS AI use cases. Anthropic Claude processes PDFs when submitted through myUSCIS, Microsoft Azure translates foreign documents, and the ML classifier labels your evidence.

2. The Main Promise of DHS

AI does not make final decisions. This is explicitly stated in the DHS AI Use Case Inventory: each system is marked as a "decision support tool." There are no public leaks contradicting this.

3. Where AI Actually Intervenes in EB-1A/O-1/NIW

Intake (Claude from Anthropic) → identity resolution (PCIS) → fraud screening (ATLAS) → evidence classification (ELIS Classifier) → translation (Azure) → officer assistance (PAiTH Legal Persona).

4. Attorneys Document AI-pattern RFEs Starting January 2025

But these same patterns can equally be explained by OCR errors and human templates. Without leaked prompts, we cannot distinguish.

5. Two FOIA Lawsuits in Active Phase

Pangea v. USCIS and Refugees International v. USCIS. If the courts rule in favor of the plaintiffs - we will obtain the first real documents.

6. Former DOJ Insiders and 14 of 15 Major Think Tanks Remain Silent

Only Cato (David Bier) has released its own analysis. This is a diagnostic signal.

7. The Main Practical Conclusion

Prepare the petition so that it is equally well processed by both the AI classifier and the human officer. Clear file names, OCR layer, certified translations, name variation memorandum, uniform job titles. This protects against both scenarios.

USCIS and AI 2026: Is Artificial Intelligence Being Used?

USCIS + AI
EB-1A
O-1
EB-2 NIW
2026

USCIS and AI 2026 is a topic discussed on forums by EB-1A, O-1, and EB-2 NIW applicants every day. People write "AI scans my petition," "Claude reads my recommendation letters," "the officer just trusts what the model showed." The good news: there is no need to guess.

DHS itself publishes a list of its AI systems by law, there are texts of FOIA lawsuits, there is a federal court ruling, and dozens of public stories from applicants. In this overview, I have gathered what is confirmed by official documents and working links - and showed what AI does in USCIS, what it does not do, and what this means for the applicant.

This is a general overview. Details are revealed in three separate articles below.

USCIS officially uses AI: as of January 28, 2026, there are 29 USCIS AI use cases in the DHS AI Use Case Inventory. Anthropic Claude 3.7 Sonnet processes PDFs during online submissions through myUSCIS, Microsoft Azure translates foreign documents, and a machine learning classifier labels evidence. The main promise from DHS (direct quote from Reuters, May 2024): "AI will not be making immigration decisions."

There are no public leaks contradicting this. However, attorneys have noted RFE with signs of AI generation since January 2025, two FOIA lawsuits demand the disclosure of prompts and contracts, and in January 2026, a federal court in the case Mukherji v. Miller overturned a USCIS denial for EB-1A for the first time based on Loper Bright.

Why the topic "USCIS and AI" became hot in 2026

? Does USCIS use artificial intelligence in processing my EB-1A, O-1, or EB-2 NIW petition in 2026?

When someone writes in immigration Telegram channels, "USCIS runs petitions through AI," the usual reaction is to roll their eyes. It sounds like a conspiracy theory. In reality, USCIS publicly disclosed this because it is required by law. According to the Advancing American AI Act (S.1353, 117th Congress), every federal agency is required to maintain and publish an inventory of its AI systems. DHS does this on the page dhs.gov/ai/use-case-inventory/uscis. The latest update is January 28, 2026, and it contains 29 USCIS AI use cases.

In 2026, the conversation shifted from "they say" to "here are the documents." Three events brought the topic into factual territory.

• DHS AI Use Case Inventory - a federal registry of AI systems that the Department of Homeland Security is required to publish. In the January 2026 version, it contains 29 use cases for USCIS, each specifying the vendor, model, status, and area of application.
• Two FOIA lawsuits - Pangea Legal Services v. USCIS (1:24-cv-02809-ACR) and Refugees International v. USCIS (1:24-cv-03559) - both filed in the US District Court for the District of Columbia, both presided over by Judge Ana C. Reyes, both demanding USCIS disclose records regarding the use of AI in adjudication.
• The Mukherji v. Miller decision (D. Nebraska, January 28, 2026) - a federal court overturned a USCIS denial for EB-1A for the first time, relying on Loper Bright Enterprises v. Raimondo (2024), which overturned Chevron deference.

Let's start with the first point - the registry. Here’s how USCIS describes one of the systems working with petitions in its own words. The task formulation here is narrow: extract data, not evaluate it.

[QUOTE | DHS AI Use Case Inventory, case DHS-2598, update January 28, 2026] "The GenAI powered library utilizes Amazon Bedrock - Anthropic Claude 3.7 Sonnet V1 Foundation Model to extract data from PDF forms." (translation): This is the literal text from the public DHS registry, not a paraphrase. The GenAI PDF Intake library uses Claude 3.7 Sonnet via AWS Bedrock to extract data from PDF forms. Source: dhs.gov/ai/use-case-inventory/uscis.

I intentionally placed these two quotes side by side because the main line of dispute runs between them. This is the framework of the entire conversation. Some in the community are convinced that AI writes RFEs right now. Others, including former USCIS insiders, point to the official list where adjudication-AI simply does not exist. The truth lies in between: AI is used at the stages of intake, translation, classification, and fraud screening - but not as the one who decides to approve or deny.

Three facts that are documented

If we remove rumors and leave only what is recorded in documents with working links, three solid facts remain. They do not prove that AI decides the fate of a petition - but they show where AI is actually present and why the topic has ceased to be speculation.

1 USCIS uses Claude 3.7 Sonnet from Anthropic via AWS Bedrock
Use case DHS-2598 "PDF Intake (PDFI) for myUSCIS", status Deployed. Purpose - extracting data from uploaded PDF forms. This is not a petition classifier; it is intelligent document processing based on LLM.
Source: DHS AI Use Case Inventory, update January 2026.

2 FOIA lawsuits are active and moving towards document disclosure
Pangea Legal Services v. USCIS (1:24-cv-02809-ACR) and Refugees International v. USCIS (1:24-cv-03559) - both before Judge Ana C. Reyes. According to the Joint Status Report from March 31, 2026, USCIS completed production by June 30, 2025, but the most sensitive documents (prompts, training data) have not yet been released. The Vaughn Index has not been issued.
Source: Just Futures Law - DHS AI FOIA.

3 Q3 FY2025 showed a decline in approval rates in discretionary categories
EB-1A: 66.6% approvals - the lowest in 3 years. EB-2 NIW: 54%. O-1 for contrast: 93.8% and remains steady. The decline is specifically where qualitative judgment is needed, not a checklist.
Source: Manifest Law / Boundless analysis FY2025.

I am not the only one noticing this. Major immigration firms are observing the same in their work with real clients - and link the increase in RFEs specifically to how evidence is initially tagged and prioritized.

[QUOTE | Cozen O'Connor, "Growing Use of AI in Immigration Adjudications", April 2026] "USCIS has not published any error-rate data, and practitioners report RFEs for documents that were in fact submitted, consistent with classifier mis-tagging."
(translation): USCIS does not publish error rate data, and practitioners report RFEs for documents that were actually submitted - this is consistent with classifier mis-tagging. Source: Cozen O'Connor.

Navigation through three related articles

To prevent this overview from becoming a lengthy document, I have separated the details into three distinct articles. Each addresses its specific question - you can read the one you need right now or all three in order.

1 What specific AI systems are in USCIS
A detailed breakdown of use cases from the DHS Inventory: Claude PDF Intake, Azure Translator, ELIS Evidence Classifier, ATLAS (PIA-084), PAiTH Legal Persona, DHSChat. With vendor, model, and verbatim quotes from the inventory. Plus testimonies from three former insiders.
Read: USCIS AI Systems 2026.

2 FOIA lawsuits and courts against USCIS
Pangea v. USCIS, Refugees International v. USCIS, Mukherji v. Miller. Who is the plaintiff, what are they demanding, what has already been disclosed, real production numbers. The impact of Loper Bright on lawsuits regarding AI in adjudication.
Read: FOIA lawsuits against USCIS.

3 4 patterns of AI-RFE and petition defense checklist
Analysis from Cozen O'Connor, Reddy Neumann Brown, The Seltzer Firm plus real cases from Reddit r/eb_1a and r/EB2_NIW. What most often "breaks" the model in EB-1A and NIW petitions. A practical checklist for the applicant.
Read: 4 patterns of AI-RFE and checklist.

Disclaimer and sources

This is not legal advice. I am not a licensed immigration attorney. I have gathered and verified public DHS documents, court dockets, and official statements - but the decision regarding your EB-1A, O-1, or NIW petition should be discussed with a licensed immigration attorney who knows your case. If any link has stopped working - please comment, and I will correct it.

Sources I used in this overview

✓
DHS AI Use Case Inventory (USCIS) dhs.gov/ai/use-case-inventory/uscis - 29 USCIS AI use cases, update January 28, 2026.

✓
Pangea Legal Services v. USCIS Just Futures Law DHS AI FOIA - docket 1:24-cv-02809-ACR.

✓ Q3 FY2025 approval rates Manifest Law / Boundless FY2025 - EB-1A 66.6%, NIW 54%, O-1 93.8%.

✓ Cozen O'Connor immigration alert "Growing Use of AI in Immigration Adjudications", April 2026.

✓ Loper Bright Enterprises v. Raimondo (2024) SCOTUS opinion 22-451 - cancellation of Chevron deference.

• USCIS AI systems - detailed analysis of use cases from DHS Inventory
• FOIA lawsuits and courts - Pangea, Mukherji, Loper Bright
• 4 patterns of AI-RFE and protection checklist - what most often "breaks" the model
• AOS-memo: USCIS memorandum on Adjustment of Status 2026 - what has changed in policy alongside AI

USCIS AI Systems 2026: Claude, Azure, ELIS, ATLAS, PAiTH and

USCIS AI systems DHS Inventory Claude 3.7 ATLAS PAiTH 2026

USCIS AI systems 2026 - this is not one model and not one "officer panel", but 29 separate use cases in the DHS AI Use Case Inventory, each with its own vendor, model, and area of application. In this article, I analyze the key systems that relate to EB-1A, O-1, and EB-2 NIW petitions: Claude PDF Intake, Azure Translator, ELIS Evidence Classifier, ATLAS, PAiTH Legal Persona, and DHSChat. For each, I provide a verbatim quote from the official DHS document and a link. At the end - testimonies from three former immigration system employees.

This is one of four articles in the cluster about USCIS and AI. The overall context and verdict - in the USCIS and AI 2026 overview. Here is only a detailed analysis of AI systems.

Where USCIS AI systems are described - DHS AI Use Case Inventory

? Where is the complete list of USCIS AI systems for 2026 officially published?

All USCIS AI systems are recorded in one public source - the DHS AI Use Case Inventory. This is a federal registry that the Department of Homeland Security is required to maintain by law Advancing American AI Act (S.1353, 117th Congress). Each entry contains an ID (for example, DHS-2598), the name of the use case, the agency (USCIS, ICE, CBP, TSA), AI classification, status (Deployed, Pre-deployment, Inactive), and a description of the purpose. The registry itself is publicly accessible: USCIS AI Use Cases page on dhs.gov.

In the version from January 28, 2026, there are 29 use cases with the agency "USCIS". Of these, about 12 relate directly or indirectly to petition processing. The rest are infrastructure-related (DHSChat, internal document search, personnel tasks).

To understand the scale, it is useful to look at DHS as a whole: USCIS is just part of a much larger wave. The head of AI in the department himself cited growth figures.

[QUOTE | Eric Hysen, CIO DHS, official statement, December 16, 2024] "158 active use cases [across DHS], compared to 67 total use cases in 2023... We identified 39 safety- and/or rights-impacting use cases." (translation): 158 active use cases across DHS compared to 67 in 2023, of which 39 are classified as impacting safety and/or rights. Source: DHS.

• USCIS and AI 2026 - general overview - return to the overall context
• FOIA lawsuits against USCIS - Pangea, Mukherji v. Miller, Loper Bright
• 4 patterns of AI-RFE and protection checklist - practice for the applicant
• AOS-memo 2026 - parallel changes in Adjustment of Status policy

Disclaimer. I am not a licensed immigration attorney. The described use cases and formulations are taken from the public DHS AI Use Case Inventory and the official PIA-084. Insider quotes are from public publications with source attribution. If any link has stopped working - let me know, I will fix it.

FOIA Lawsuits Against USCIS 2026: Pangea, Mukherji v. Miller and

FOIA Lawsuits Pangea v. USCIS Mukherji v. Miller Loper Bright 2026

FOIA lawsuits against USCIS 2026 are legal cases that attempt to compel the agency to disclose how exactly AI is used in the processing of petitions. Two of them - Pangea Legal Services v. USCIS and Refugees International v. USCIS - demand documents: prompts, training data, contracts with vendors. The third case, Mukherji v. Miller, stands out: it is not a document request but a direct lawsuit against a specific denial of EB-1A - and in January 2026, the plaintiff won it. In this article, I analyze all three in order and explain what they actually provide to the applicant right now.

This is one of four articles in the cluster about USCIS and AI. Here, only the courts are discussed. A general overview and verdict are in the main article, while specific USCIS AI systems are analyzed separately.

Why FOIA Lawsuits Against USCIS

? What legal cases compel USCIS to disclose how exactly AI is used in deciding my petition?

FOIA is the Freedom of Information Act, 5 U.S.C. 552. Under it, any person or organization can request documents from a federal agency, and if the agency refuses or delays - file a lawsuit. With AI in USCIS, the logic is this: the organization requests "give all records on the application of AI in adjudication," USCIS responds with a denial or heavily redacted documents, and then the case goes to federal court, which decides what and in what form must be released.

Why is this necessary for the applicant - the best explanation comes from a former USCIS asylum officer. The problem is not that AI exists, but that its operation is invisible to the applicant.

[QUOTE | Joshua Perez Garcia, former USCIS Asylum Officer (6 years), ILW.com, May 11, 2026] "The officer has seen what the system surfaced; the applicant and attorney have not. The NOID does not disclose it. The denial letter does not disclose it." (translation): The officer has seen what the system highlighted; the applicant and attorney have not. The NOID (Notice of Intent to Deny) does not disclose this. The denial letter does not either. It is this invisibility that FOIA lawsuits aim to uncover. Source: ILW.com.

2

Mukherji - a precedent for overturning an EB-1A denial If the 8th Circuit upholds the Bataillon decision, applicants will have a direct argument: the opaque final merits determination can be challenged through the APA. This decision can already be cited in a motion to reopen after a denial. When: appeal in the 8th Circuit; as of late May 2026 there was no opinion yet, and one was expected in 2026-2027.

3

Pangea and Refugees International - disclosure of prompts If Reyes compels USCIS to release prompts and training data, attorneys will see exactly what the AI systems are trained on and what they are looking for. This is the most powerful tool - but also the most distant: the shutdown has frozen production, and the Vaughn Index has not been released. When: realistically 2027-2028.

Conclusions

1. Pangea and Refugees International - FOIA for documents

Both are before Judge Ana C. Reyes. The goal is to compel USCIS to disclose how AI is used in adjudication. USCIS has released its part, but prompts are still not available, and the government shutdown since February 14, 2026 has frozen the rest.

2. Mukherji v. Miller - APA challenge, and the plaintiff won

The federal court in Nebraska (Judge Bataillon, January 28, 2026) found the final merits determination on EB-1A arbitrary and capricious and ordered the petition to be approved directly, relying on Loper Bright. The DOJ is appealing in the 8th Circuit.

3. Loper Bright has already changed the balance

The cancellation of Chevron deference means that arguments against the USCIS AI policy are now considered by courts independently, without mandatory deference to the agency. This is already working at the RFE stage.

4. Systemic disclosure prompts are still early

All FOIA litigations are at an early stage: the Vaughn Index has not been released, there is no ruling on the merits, and the shutdown has frozen issuance. However, a personal FOIA request for one's A-file is available to the applicant right now.

• USCIS and AI 2026 - an overview
• USCIS AI systems - use cases from DHS Inventory
• 4 patterns of AI-RFE and checklist for protection - practice for the applicant
• AOS-memo 2026 - parallel changes in Adjustment of Status

Disclaimer. I am not a licensed immigration attorney and not a litigation specialist. The statuses of cases are indicated based on the latest publicly available docket entries and publications as of the date of writing. Before using in your own petition strategy, check the current status on PACER or CourtListener. If any link has stopped working - let me know, I will fix it.

FAQ

Related

Reference material, not legal advice: rules and practice change - check the primary sources and consult a licensed attorney where needed.

Related materials - Wait for the decision

• How to track your case after filing an O-1/EB-1 petition
• RFE: What Is a Request for Evidence
• Why an RFE Comes: Causes and Statistics
• RFE response: how to answer USCIS step by step
• How to format evidence so USCIS counts it: real RFEs
• NOID: how to respond to a Notice of Intent to Deny
• What Happens After EB-1 / EB-2 Petition Approval
• How to Read the Visa Bulletin for EB-1 and EB-2
• Priority Date: How to Find It and What It Means
• Final Action Dates and Dates for Filing
• The standards that trigger an RFE
• How the evidence was gathered
• Mandamus and Congress: what really works in case of delay

All articles in «Wait for the decision»

Next stepCost + timeline estimatorWhat it costs and how long it takes: an O-1 budget plus preparation and processing timelines.

From community discussions

• «Whatever you do, don't do this, I beg you. I tried it, it's a 100% denial. I got a 13-page RFE about how this carries no national importance for the US. Any words about a shortage are a red flag for the officer. They didn't even read my RFE response with the redefined endeavor.»

  community member · from public community chats

• «Once the case is filed, no evidence obtained after the filing date is accepted for that case. That is, it's reviewed as of the time of filing. The RFE will come for what's already been filed, and they expect a response on what's written there.»

  Eugene · from public community chats

• «My lawyer told me that at the figure skating World Championships a pair won a medal, but EB-1 was approved for only one person, because collective awards don't count.»

  Maksim · from public community chats

Personal opinions of community members from public discussions, not legal advice.

Did this answer help?

YesNo