Funding Entities Explore AI Solutions Amid Surge in Grant Applications

The landscape of grant applications is undergoing a transformative shift as recent data from Funding Forward indicates a striking 57% increase in application volumes since 2022. This surge has been particularly evident within the National Institutes of Health (NIH), which reported an 11% rise in early-career grant applications in 2025 alone. These statistics not only reflect a growing enthusiasm for research funding but also expose the mounting challenges that grant-making organizations face in handling such an influx.

The increase in applications has compounded difficulties for funders, as traditional evaluation mechanisms may struggle to keep pace with this unprecedented volume. Acknowledging this reality, various funding bodies, including the NIH and the Ministry of Science and Technology of China, are now grappling with the complexities introduced by AI-assisted submissions. Consequently, several organizations are exploring the viability of implementing AI-enabled screening tools to enhance the application evaluation process.

Notably, the nationwide rise in grant applications attributed to the ease of generating complex proposals through AI technologies presents both opportunities and unintended consequences. While some funders are outright restricting the use of substantial AI contributions in applications, others adopt a more flexible stance, allowing initial AI involvement, provided it is disclosed. Noteworthy among these is the European Research Council, which has a lenient approach permitting applicants to use AI for preliminary drafting and brainstorming, yet requires full transparency regarding its use.

The report highlights a growing trend among funders to shift their focus from merely evaluating the content of the applications to assessing the applicant’s overall track record, institutional backing, and collaborative capabilities. By doing so, organizations aim to foster a more equitable funding landscape that does not unfairly favor seasoned researchers over burgeoning talent. For instance, the Horizon Europe funding program has taken a notable step by implementing a blind review process for initial evaluation stages, where a proposal’s methodology and research plans are assessed without knowledge of the applicant’s identity or affiliation.

While these steps are promising, the analysis also casts a critical eye on the potential pitfalls of intertwining AI into grant review processes. The idea of using AI to help manage application volumes, while seemingly advantageous, could inadvertently replicate existing biases present in the algorithms and datasets used for training. As funding bodies develop long-term strategies to refine evaluation methods, careful consideration must be given to mitigate inherent biases and ensure a balanced approach to assessing grant applications.

Moving forward, contractors and service providers may find opportunities to support funding agencies by enhancing their application triage capabilities, including compliance detection and bias assessment systems. Addressing these operational pressures becomes paramount as agencies adapt to the growing influence of AI on both submissions and evaluations, leading to an evolving procurement landscape directed at improving efficiency and fairness in the grant selection process.

Here are several actionable insights to retain in mind:

• The National Institutes of Health and China’s Ministry of Science and Technology have largely prohibited AI-developed applications.
• Funding organizations explore AI for triage processes to alleviate burdens on evaluators.
• Analysts raise concerns regarding biases in AI algorithms affecting funding fairness.
• Contractors should evaluate their service offerings against evolving compliance needs of funding bodies.
• Awareness and disclosure of AI use are being monitored closely by organizations like UK Research and Innovation.
• Innovation in application assessment could open new procurement opportunities in technological solutions for compliance and bias detection.
• Stakeholders are urged to remain informed about evolving procurement requirements as funders adjust to new funding dynamics driven by AI.