NSF AI Dear Colleague Letter (DCL)

An NSF AI Dear Colleague Letter (DCL) is any of several topic-specific Dear Colleague Letters the National Science Foundation has issued that have artificial intelligence as their explicit subject -- typically flagging a funding priority and directing proposers toward an existing mechanism (RAPID, Planning Grant, EAGER, or a standing program) rather than creating an independent competition. To count as one, a document must (a) be formally issued as a DCL under NSF's Proposal & Award Policies & Procedures Guide (PAPPG) Chapter I definition, carrying an NSF publication number in the nsf.gov DCL series, and (b) name AI/generative AI as the letter's subject. This is a narrower category than 'NSF AI policy' generally, and it explicitly excludes NSF's December 2023 guidance on generative-AI use in the merit review process, which was issued as a Notice to the Research Community, not a DCL -- a distinction searchers frequently get wrong and this page exists to clarify.

ByCASRAI Editorial Board

· Last updated 23 Jul 2026

Worked examples

Is an instance

NSF 23-097, 'Rapidly Accelerating Research on Artificial Intelligence in K-12 Education in Formal and Informal Settings' (issued May 8, 2023), directs RAPID proposals of up to $200,000 for up to one year, submitted first as a one-page concept outline to a dedicated program mailbox rather than through a standalone competition.

Is an instance

NSF 26-023, 'Unleashing a New Age of AI-Enabled Scientific Discovery through the Genesis Mission' (published July 22, 2026), directs proposers to submit through existing NSF funding opportunities with a 'Genesis Mission:' title prefix, tied to AI-driven scientific workflows, foundational research supporting the initiative's National Science and Technology Challenges, and AI-for-science workforce development.

Looks similar, but isn't

Not an instance

NSF's December 2023 'Notice to the Research Community on AI,' which prohibits reviewers from uploading proposal or review content to non-approved generative-AI tools and encourages (but does not require) proposers to disclose generative-AI use in the Project Description, is not a DCL -- it was issued as a Notice, a different PAPPG-defined document type. See NSF AI Policy for full coverage of that strand and the related research-misconduct language.

Not an instance

The PAPPG 24-1, Supplement 1 amendment (effective December 8, 2025) that added AI-based tools to NSF's research-misconduct definition is a PAPPG revision, not a DCL -- it changes the governing policy document itself rather than communicating informally alongside it.

An NSF AI Dear Colleague Letter (DCL) is a topic-specific Dear Colleague Letter — one of the U.S. National Science Foundation’s standard, lower-weight mechanisms for communicating with the research community — that has artificial intelligence as its explicit subject. NSF has issued several of these since 2023, most commonly to flag a funding priority and point proposers toward an existing submission mechanism rather than to launch a new standalone competition.

What makes a document count as an NSF AI DCL

Per NSF’s Proposal & Award Policies & Procedures Guide (PAPPG), Chapter I, a DCL is used to provide general information, clarify or amend existing NSF policy, or inform the community about upcoming opportunities — it does not, on its own, establish independent eligibility rules, a dedicated review process, or a hard proposal deadline the way a Program Solicitation does. An NSF AI DCL is simply a DCL, in that formal sense, whose subject is AI. That test matters because it is what separates a genuine AI DCL from NSF’s other AI-related documents, several of which are commonly (and incorrectly) referred to as DCLs. See NSF Dear Colleague Letter (DCL) for the general mechanism this category sits inside.

Real examples

NSF 23-097, Rapidly Accelerating Research on Artificial Intelligence in K-12 Education in Formal and Informal Settings (issued May 8, 2023) — invites Rapid Response Research (RAPID) proposals, up to $200,000 for up to one year, on developing age-appropriate AI tools for equitable learning, teaching AI concepts to K-12 students, and integrating generative AI responsibly in educational settings. Proposers submit a one-page concept outline to a dedicated program mailbox before a full proposal.
NSF 26-023, Unleashing a New Age of AI-Enabled Scientific Discovery through the Genesis Mission (published July 22, 2026) — directs proposers toward existing NSF funding opportunities, using a ‘Genesis Mission:’ title prefix to flag relevance, across three priority areas: AI-driven autonomous/semi-autonomous research workflows, foundational research supporting the initiative’s named National Science and Technology Challenges, and AI-for-science workforce development including federally cost-shared research fellowships.
NSF’s Directorate for Engineering and other directorates have issued further AI-specific DCLs in the same period covering engineering research in AI, AI-ready test bed planning grants, and a request for information on researcher use cases for the National AI Research Resource (NAIRR) pilot — all following the same pattern of pointing proposers to an existing mechanism rather than creating a new one.

What is commonly mistaken for a DCL, but is not

The single most-referenced NSF AI document — its December 2023 guidance on generative AI in the merit review process — is not a DCL. NSF issued it as a Notice to the Research Community, a separate PAPPG-defined document type. That notice prohibits reviewers from uploading any proposal or review content to non-approved generative-AI tools (a confidentiality-pledge violation if they do) and encourages, without requiring, proposers to disclose generative-AI use in the Project Description. Likewise, the December 2025 PAPPG amendment (PAPPG 24-1, Supplement 1) that explicitly folded AI-assisted fabrication, falsification, and plagiarism into NSF’s research-misconduct definition is a revision to the PAPPG itself, not a DCL. Both are real, current NSF AI policy — they are just a different document type than the letters above. See NSF AI Policy for the full picture across all these strands in one place.

Why the distinction matters for research administration

Sponsored-programs staff tracking NSF’s AI-related communications for horizon-scanning purposes need to know which category a given document falls into, because the practical consequences differ. A DCL usually just adds AI as an encouraged topic under an existing mechanism’s standing rules (budget caps, deadlines, review criteria) — it rarely changes compliance obligations. A Notice, by contrast, can create an immediate operational obligation (e.g., reviewers must not paste proposal text into an unapproved AI tool) that applies agency-wide regardless of which program a proposal sits under. And a PAPPG amendment changes the underlying rulebook itself. Conflating the three risks either under-reacting to a real new obligation or over-reacting to what is, structurally, just an encouraged-topic flag.

Related terms

NSF Dear Colleague Letter (DCL) — the general mechanism.
NSF AI Policy — full coverage of the Notice, the PAPPG misconduct amendment, and NSF’s AI infrastructure investments.
National AI Research Resource (NAIRR)
NSF AI Institutes (National AI Research Institutes)
Generative-AI disclosure statement
NIH vs NSF vs ERC: AI Policies for Grant Writing

Use in your systems

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