Can You Upload a Confidential Grant Application to an AI Tool?

Can a Confidential Grant Application Be Given to AI?

You are reviewing a grant application and want help understanding an unfamiliar method, summarizing a long research plan, checking whether the proposed analysis makes sense, or organizing your critique. Uploading the application to an AI tool could save considerable time.

But the application is confidential. You received it because a funding organization authorized you to participate in its review process, not because the proposal became available for general use.

That distinction matters. For confidential grant applications, the first question is not whether AI would improve your review. It is whether you are permitted to disclose any of the application or information derived from it to the AI system at all.

For Reviewers, the Default Should Be No Unless the Funder Permits It

Grant Review Confidentiality Follows the Information

A grant application contains information entrusted for a specific purpose

A reviewer may receive extensive unpublished information: research ideas, preliminary results, experimental designs, budgets, commercialization plans, intellectual property, collaborator information, institutional strategies, and personal information about investigators.

Access is granted so the reviewer can evaluate the application under the funder's procedures. It does not create general permission to transmit the information to another person, organization, or service.

NIH states that confidentiality in peer review protects trade secrets, commercial or financial information, privileged information, and other confidential material. Its reviewers must certify their compliance with confidentiality requirements before gaining access to applications and review materials.

Some funders explicitly prohibit AI uploads by reviewers

This is not merely a theoretical concern. Major research funders have issued explicit rules.

The U.S. National Institutes of Health prohibits scientific peer reviewers from using generative AI technologies to analyze or formulate critiques of NIH grant applications and R&D contract proposals. NIH states that uploading or sharing application content, original concepts, critiques, or associated confidential information with online or unapproved third-party generative AI systems violates its peer-review confidentiality requirements.

The U.S. National Science Foundation likewise prohibits reviewers from uploading proposal content, review information, and related records to non-approved generative AI tools. NSF states that proposal information shared through open-internet generative AI cannot remain under NSF's confidentiality protections and treats such release as a breach of confidentiality.

The restriction is not limited to uploading the PDF

A reviewer can disclose an application without ever attaching the original file.

Suppose you type: "I am reviewing a grant proposing a new intervention for a rare condition. The investigators report these unpublished pilot results..." and then provide the central findings. You may have disclosed confidential application information even though the application itself never left your downloads folder.

NIH's confidentiality certification specifically encompasses grant applications, R&D contract proposals, information contained in them, reviewer critiques, review materials, evaluations, scores, discussions, and other associated confidential information.

The correct question is therefore not "Did I upload the application?" It is "Did I disclose information I received through the confidential review process?"

Your review notes can be confidential too

The confidentiality boundary may extend beyond the applicant's original document. Your preliminary critique, scores, notes, other reviewers' comments, panel discussions, conflicts of interest, and review-meeting information can also be protected.

NIH, for example, prohibits reviewers from recording or transcribing committee deliberations and from disclosing information about discussions, evaluations, or review documents outside authorized channels. Its confidentiality requirements specifically include critiques and associated meeting information.

An AI tool used to summarize a review meeting transcript or polish confidential panel notes could therefore create the same basic problem as uploading the application itself.

A no-training setting does not override the funder's prohibition

Suppose your AI account states that prompts are not used to train foundation models. That can be an important privacy protection in other contexts. It does not grant you permission to disclose a confidential grant application.

If the funder prohibits transmission to an unapproved AI platform, changing the provider's training setting does not alter the funder's rule. Nor does it necessarily eliminate other forms of processing, retention, logging, or access.

The distinction between AI model training and other uses of submitted prompts is important, but the funder's confidentiality requirement comes first.

A paid or enterprise AI account is not automatically an approved system

An enterprise AI service may provide stronger contractual protections, security controls, restricted model-training practices, and organizational governance. Those features can be valuable, but they do not by themselves establish that a funding organization has approved the system for confidential peer-review material.

NSF's policy, for example, distinguishes non-approved generative AI tools from systems authorized for agency use. NIH's confidentiality certification similarly refers to unapproved third-party platforms and requires authorization from the relevant designated official for exceptions.

If a funder provides or explicitly authorizes a particular AI capability, follow the conditions attached to that environment. Do not substitute a different tool simply because its marketing page describes it as secure.

Applicants and reviewers are not in the same position

This distinction is essential. A principal investigator developing their own application and a reviewer evaluating someone else's confidential application have different relationships to the material.

NSF's guidance explicitly distinguishes the two roles. It prohibits reviewers from uploading proposal material to non-approved generative AI tools while encouraging proposers to indicate the extent to which generative AI was used in developing their proposal.

NIH likewise distinguishes application preparation from peer review. NIH's current guidance allows that AI may be appropriate for limited aspects of application preparation in some circumstances, while applications substantially developed by AI, or containing sections substantially developed by AI, are not considered the original ideas of applicants and will not be considered. Reviewers, meanwhile, remain prohibited from using generative AI to analyze and formulate critiques of NIH applications.

This is why using your own confidential research proposal with AI and uploading a grant application entrusted to you for review should not be treated as the same question.

Confidentiality also protects intellectual priority

A grant application can reveal research plans years before the resulting studies or publications become public. Preliminary findings, novel hypotheses, experimental designs, technical approaches, commercialization strategies, and potentially patentable ideas may all appear in the application.

NIH's confidentiality rules explicitly prohibit reviewers from using application information for personal benefit or making it available for another individual's or organization's benefit. NSF similarly emphasizes the risks to researchers' control over their ideas when confidential proposal information is disclosed through unapproved generative AI.

Review confidentiality therefore protects more than personal data. It helps protect intellectual priority, proprietary information, and trust in the funding process.

AI can also compromise the independence of the review

Even if confidentiality were somehow resolved, grant review requires the judgment of the appointed reviewer. An AI-generated critique may overlook disciplinary nuance, misinterpret feasibility, hallucinate methodological requirements, or reproduce biases embedded in its training and retrieval processes.

NIH reviewers are appointed to assess applications using specified review criteria and their own judgment of scientific merit. Delegating that assessment to a generative model can therefore create an integrity problem alongside the confidentiality problem.

Generic questions can sometimes be separated from confidential content

A reviewer may legitimately need to refresh their understanding of a statistical method, theoretical framework, measurement instrument, or public body of literature. That does not necessarily require revealing anything about the application.

If the funder's policy permits use of an AI tool for general purposes, a genuinely generic question such as "What assumptions does a regression discontinuity design require?" is different from pasting the applicant's design and asking the AI to review it.

Authoritative methodological literature may often be the better source anyway. Peer review is one of those occasions when reading the methods paper remains inconveniently fashionable.

A Reviewer Wants Help Assessing an Unfamiliar Method

The reviewer obtained the methodological support needed without making the confidential application part of an external AI conversation.

Common Mistakes With Confidential Grant Applications and AI

Let the Funder's Confidentiality Rules Decide Before the AI Tool Does

If you are reviewing a grant application, the relevant authority is the funding organization's current review policy and the confidentiality agreement governing your assignment. The AI provider's features come second.

The conservative default is appropriate because the information belongs to an applicant who did not give you the application for general-purpose AI processing. The broader principle is the same as for confidential and unpublished research information in AI: authorization should precede disclosure.

Before Using AI While Reviewing a Grant Application

Questions About Confidential Grant Applications and AI

Confidential Grant Review Is Not an Open-AI Workspace

How to Cite This Guide

This guide is intended to be read, shared, and used in research, teaching, and academic work. If you draw on its ideas, explanations, or other content, please acknowledge the source by citing the guide. Doing so gives appropriate credit and helps your readers locate the original resource.