On May 8, 2025, the U.S. Food and Drug Administration (FDA) announced a historic milestone: the completion of its first AI-assisted scientific review pilot. Additionally, the Agency shared plans for a broader, agency-wide AI strategy focused on increasing productivity, enhancing scientific review, and improving public health outcomes. An aggressive timeline to scale the use of AI internally across all FDA centers by June 30, 2025 was also announced.
Axendia has been closely following FDA’s digital transformation journey and documented the evolution of FDA’s stance on AI, making this announcement certainly significant but not surprising. At FDA’s Digital Transformation Symposium in 2023, we noted the Agency is embedding AI in everything. “FDA is not building a center of excellence on AI. AI will be embedded in everything we do” said Mohammed Sohail Chaudhry, ODT’s Chief Technology Officer. This assertion was supported by Ram Iyer, ODT’s Chief Data Officer. Ram confirmed the Agency’s focus on scaling programs that improve connectivity to create AI-ready data. To this end, FDA is mastering its data via Enterprise Data Management and providing platforms and services that encourage AI innovation.
Commissioner US FDA
Source: FDA.gov
In March, we accurately predicted that Commissioner Dr. Makary’s appointment could signal innovation-friendly policies – particularly around AI – and today, that prediction is coming to fruition. “I was blown away by the success of our first AI-assisted scientific review pilot. We need to value our scientists’ time and reduce the amount of non-productive busywork that has historically consumed much of the review process. The agency-wide deployment of these capabilities holds tremendous promise in accelerating the review time for new therapies,” said Dr. Makary in the Agency’s press release.
Dr. Makary’s remarks not only highlight the operational benefits of AI but also validate the Agency’s growing confidence in digital tools to enhance—not replace—human expertise.
A Pilot with Purpose
According to the FDA press release, the pilot program focused on leveraging AI to support scientific review within the Center for Drug Evaluation and Research (CDER). The tool was used to assist with the quality assessment of Chemistry, Manufacturing, and Controls (CMC) sections of new drug applications.
Not only were the results promising but review teams reported that AI-assisted review increased consistency, expedited information retrieval, and reduced manual efforts. Based on this success, the FDA plans to extend AI capabilities across the Agency, including in areas like regulatory operations, pharmacovigilance, and post-market surveillance.
From AI-Friendly to AI-Forward
The FDA’s transition from AI-friendly to AI-forward didn’t happen overnight. Over the past few years, the Agency has taken deliberate steps to build the foundation for AI integration. In 2023, the release of the Agency’s “Action Plan for Artificial Intelligence in Medical Products” laid the groundwork for responsible and risk-based adoption. A year later in 2024, the Agency launched the “FDA AI Challenge,” inviting stakeholders to develop and demonstrate validated, transparent AI solutions.
These initiatives weren’t just academic. They were part of a its strategy to modernize regulatory science and ensure the FDA could keep pace with technological innovation.
Keeping an Eye on AI in Regulated Environments
Axendia’s market research report, “The State of Generative AI in Life Sciences: The Good, The Bad and The Ugly,” highlighted that life science companies have a clear understanding of the opportunities and risks of AI adoption in regulated environments. In a joint article with Garth Conrad, VP of Quality at Flex, we recently explored how AI could be harnessed to address regulatory burden, reduce time-to-market, and support quality-centric innovation.
The FDA’s announcement reaffirms that it sees AI as a tool to enhance its mission. Throughout our research and interactions with executives, we’ve witnessed the industry repeatedly voice concerns about staying compliant when using AI in GxP environments. Since the FDA now appears to be outpacing the very industry it oversees, it may be time for the industry to reexamine whether those fears are still justified.
Implications for Industry and What Comes Next
The FDA’s shift toward AI-assisted operations has broad implications for stakeholders across the life sciences ecosystem:
- Drug Sponsors and Developers should begin preparing for increased use of AI tools in regulatory review. This means investing in data integrity, validation frameworks, and traceability of AI decision-making processes.
- Technology Providers have a unique opportunity to support the FDA’s transformation by developing AI tools that are transparent, validated, and aligned with regulatory expectations.
- Regulatory Affairs and Quality Leaders must evolve their digital competency and collaborate with IT and data science teams to integrate AI responsibly.
The FDA’s announcement hints that a more structured AI governance framework will be coming soon. We expect future guidances will clarify the Agency’s expectations for the use of AI across submissions, monitoring, and compliance functions. Additionally, as AI plays a growing role in decision-making, questions around validation, accountability, and risk management will likely take center stage.
At Axendia, we believe this is a defining moment. AI is becoming embedded in the very fabric of how the FDA operates. The Agency is taking deliberate and cautious steps, but it is clearly moving forward.
In Brief
The FDA’s latest move indicates that quality and innovation must coexist. By using AI to support its own processes, the Agency is setting a precedent for how innovation can be embraced responsibly in regulated environments.
As we look ahead, Axendia will continue to monitor the evolving relationship between FDA and AI. One thing is clear: the future of regulation is not just digital, it’s intelligent.
Stay tuned.
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Read more of our analysis on FDA and AI here.
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The opinions and analysis expressed in this post reflect the judgment of Axendia at the time of publication and are subject to change without notice. Information contained in this post is current as of publication date. Information cited is not warranted by Axendia but has been obtained through a valid research methodology. This post is not intended to endorse any company or product and should not be attributed as such.