AI-Written Applications: How to Set Fair Guardrails and Detection Practices in Foundant

Artificial intelligence is now part of the grantmaking process. Applicants are increasingly using AI tools to help draft responses, and funders are beginning to utilize AI to summarize applications, organize reviewer notes, or support internal workflows.

The use of AI raises important questions. How do you maintain fairness when AI is used on both sides of the process? How do you protect equity and human judgment while still benefiting from efficiency?

For funders using grant management software, the goal of AI integrations is to create clear, ethical guardrails that support transparent review processes and responsible use of AI within your own workflows.

Why do AI-written applications matter when you are using AI to review applications?

The use of AI in grantmaking has numerous practical applications that benefit both applicants and funders. Recent research shows that 66.3% of respondents are using AI to help write grant applications. According to the 2025 Charity Digital Skills Report, 76% of charities reported using AI in 2025, up from 61% the previous year.

Concerns around accuracy, fairness, and authenticity are understandably raised as AI becomes more common in the grantmaking process. The issue is not whether applicants used AI to draft content. 

In fact, allowing applicants to submit AI-written applications often levels the playing field. The real concern is whether review processes remain transparent and grounded in human judgment.

Artificial intelligence should never replace the judgment and nuance required in the evaluation process. However, with thoughtful integration in grant management tools, foundation staff can responsibly use AI to support their grant lifecycle workflow. 

AI integrations enable staff to:

• Summarize lengthy application responses
• Provide reviewer note support
• Standardize follow-up language

Clear guardrails around AI use help ensure those benefits don’t come at the cost of equity.

How can funders set fair, transparent guardrails for AI use?

Responsible AI use starts with clear expectations and defined use cases. To establish appropriate expectations for AI-written applications and their use in the review process, funders should outline acceptable practices so that everyone understands what is appropriate and what is not.

This need for clear expectations and transparency around AI use is urgent. Recent research shows that 72% of funders do not yet have an organizational policy governing AI use, even as experimentation with AI tools is becoming more common among grantmaking teams.

Here is how funders should think about AI use guardrails:

1. Create a simple AI-use policy: Transparent policies build trust on both sides of the process. Define acceptable and unacceptable practices, such as misrepresenting organizational capacity or data.
2. Review rubrics: Rubrics help reviewers focus on substance rather than writing quality, so as not to unintentionally disqualify small organizations or applicants with limited resources. Criteria should prioritize feasibility and alignment.
3. Train reviewers on ethical AI use: AI can support funders in the review cycle, but it should never replace independent scoring or final decisions. Clear guidance and appropriate training protect the integrity of the review process.

As funding continues to evolve with the integration of AI, it’s crucial for funders to approach this technology with a mindset that prioritizes integrity and fairness. Establishing clear guidelines and providing adequate training harnesses the potential of AI while ensuring that all applicants, regardless of their resources, are given a fair chance to succeed. The goal should be to foster an inclusive and equitable funding environment that benefits everyone involved.

What ethical and practical methods support fair AI detection during reviews?

The use of AI detection tools is becoming commonplace. Although many tools promise to detect AI use, they are often unreliable. More often than not, they disproportionately flag ESL writers or organizations with limited staff. When this happens, biases are introduced rather than reduced.

A more ethical approach to application review that doesn’t rely on AI detectors is to review applications with integrity. 

This means staff focus on fairness and equity, taking the time to:

• Check internal consistency across application sections
• Verify claims that require documentation
• Request clarification when responses raise questions

Regardless of how an application was drafted, reviewing application consistency and verifying claims applies to all applicants equally.

Grant management systems can support this approach. Software for grantmakers offers structured rubrics, review comment fields, and workflow prompts that allow review teams to document concerns. Requests for clarification can be logged and tracked within the system, creating a clear audit trail.

For foundations, it’s helpful to establish internal policies that reinforce privacy expectations and responsible handling of sensitive information throughout the grant lifecycle. Grants management software enables the implementation of ethical and practical review methods, allowing staff to manage data responsibly.  

A practical roadmap for implementing responsible AI-supported reviewing in Foundant

For lean teams, responsible AI adoption works best as a step-by-step process. Throughout each step, transparency, fairness, and human judgment should remain central. 

Here is what that looks like in practice:

1. Draft an AI-use policy: Clearly define acceptable and unacceptable uses for both applicants and reviewers.
2. Update application instructions: Communicate expectations transparently so applicants understand how their submissions will be evaluated.
3. Standardize review criteria: Focus rubrics on alignment, feasibility, and impact rather than writing style.
4. Train reviewers on ethical AI use: Reinforce that AI supports summarization and documentation, not scoring or decisions.
5. Use workflows to document and clarify: Leverage reviewer comments and clarification requests to maintain consistency and transparency.
6. Revisit guardrails annually: AI tools evolve quickly. Policies should grow with them.

When used responsibly, integrated AI in grant workflow management software can help reduce administrative burden and improve consistency across reviews and processes. With clear guardrails and supportive workflows, funders can embrace efficiency without compromising equity.

Want to strengthen your review process with fair, human-centered AI guardrails? 

Start a conversation with Foundant to explore tools and workflows that support equitable, transparent grantmaking.