Evaluating and Scaling AI in Grants Management

Organizations exploring AI in grants management often start with the basics: cleaning up data, mapping processes, and running a few low-risk pilots such as drafting narratives or summarizing funding announcements.

Building AI Readiness in Grants Management

Discover Where to Start

Preparation is especially important for grant recipients, who must confirm that new technology supports compliance requirements, internal controls, and sensitive data protection. Moving too quickly can create data quality, privacy, and workflow integration risks; waiting too long can leave organizations behind as peers improve efficiency, accelerate applications, and respond faster to funding opportunities.

Once that foundation is in place, the next question becomes more concrete: how does an organization keep AI-generated work trustworthy as it moves toward a formal submission, and which tools should it adopt to scale that work across the grants lifecycle without outpacing its compliance and internal control requirements?

Key Takeaways

• A Human-in-the-Loop review process, including verifying AI-generated figures, dates, and citations, protects compliance before any formal submission
• Organizations evaluating AI tools should confirm that the tools support Uniform Guidance requirements, integrate with existing systems, and allow audit-ready data export
• Tools should be assessed within the broader technology environment, not in isolation, to avoid duplicate data entry and system fragmentation
• As experience grows, organizations can expand into more advanced capabilities such as predictive analytics and automated subrecipient risk assessments

The Human-in-the-Loop Imperative

The most important part of any AI strategy is the Human-in-the-Loop protocol. AI is a helpful assistant, but it cannot be the final decision-maker. AI-generated outputs may be incomplete or contain inaccuracies, reinforcing the need for consistent human review before use in any formal submission. In a grants management context, this may include inaccurate citations, fabricated data, or misinterpreted requirements. Staff should understand this limitation so that human review is treated as a required safeguard rather than a formality.

Organizations should establish a simple checklist requiring staff to verify any AI-generated figures, dates, and technical details. This approach keeps organizations responsible for all grant activities and confirms the final product reflects the team's technical and local knowledge.

By focusing on these accessible strategies, organizations can bridge capacity gaps while remaining competitive and compliant in a digital world. The goal is AI-enabled work, where technology carries the administrative weight and compounds efficiency.

A Practical Example

A budget justification drafted with AI assistance in one grant cycle becomes a reusable template in the next, and a NOFO summary checklist created for one opportunity can be adapted for the next in minutes rather than hours. Over time, these incremental gains reshape the capacity equation for the entire grants office.

With review protocols in place, organizations are ready to evaluate and select the tools that will carry this work forward.

AI Tool Evaluation and Selection

As organizations go beyond preparation, teams may wish to evaluate potential AI tools using grant-specific criteria. When considering solutions, organizations should assess whether a tool meets Uniform Guidance requirements, integrates with existing systems, and maintains audit-ready documentation. Many vendors now offer AI-enabled grants management features, but not all are designed for recipients. A structured evaluation checklist, covering privacy, transparency, data retention, and exportability, can help organizations make informed decisions.

Organizations should not evaluate AI tools in isolation; rather, they should consider how a tool fits within the broader technology environment. The critical questions are often the ones not asked:

• Does this tool connect to our existing grants management platform or financial system?
• Can data be exported in standard formats that support audit requirements?
• Will staff need to re-enter information that already exists elsewhere?

Starting Your Modernization Journey

As organizations gain experience, they can expand into more advanced capabilities, including predictive analytics for program outcomes, automated subrecipient risk assessments, and integrated AI features within grant management systems. Many vendors are already embedding secure, privacy‑first AI tools directly into their platforms, making it easier for recipients to adopt AI without major system overhauls. The key is to scale gradually, aligning each new capability with organizational capacity and regulatory requirements.

As AI capabilities continue to evolve, grant recipients have an opportunity to strengthen their operations by reducing administrative burden and improving program outcomes. The most important step is simply to begin. These early actions create a foundation that supports responsible, secure, and sustainable adoption—thus maximizing potential for AI to enhance the essential work of delivering services and programs to communities.

At EisnerAmper, our team helps organizations adopt AI for long-term success, without compromising compliance, security, or scalability. To start your modernization journey, contact us today.