How digital regulation will reshape quality, compliance and operational expectations across the life sciences ecosystem.
Written by: Cassidy Reid & Alice Redmond
A Regulator Moving Faster Than Industry Is Used To
The FDA deployment of agentic AI across its organization represents far more than another incremental technology upgrade. It marks a decisive shift in how the FDA ecosystem will operate moving forward. Agentic AI refers to AI systems that can plan, reason and execute multi-step tasks toward a defined goal, while operating under human oversight. Unlike simple generative AI (e.g., text summarization), agentic AI can Break down complex workflows into steps, Coordinate actions across multiple processes and Integrate outputs for decision support (but not make regulatory decisions autonomously). The FDA is deploying these tools internally for Pre-market reviews and validation, post-market surveillance and adverse event analysis, Inspections and compliance tasks and administrative functions like meeting management.
While the headlines have focused on the novelty of the technology itself, the deeper story (and the one that will matter most to industry) is how dramatically this changes the expectations placed on sponsors, manufacturers and quality organizations. With agentic AI now assisting in reviews, surveillance, inspections, and compliance work at scale1, the cadence and rigor of regulatory evaluation are about to change permanently.
AI-Driven Review Means New Pressures on Industry Data
For years, regulatory timelines have been strained by staffing reductions, increased submission complexity and high-profile delays across therapeutic areas2. The FDA response (deploying AI systems capable of orchestrating multi-step workflows, generating contextual summaries and identifying inconsistencies across large submissions) signals an intention to close this gap not through headcount, but through digital leverage. These are not simple chat interfaces. They are agentic systems designed to plan and execute regulatory tasks under human oversight1. This shift accelerates the review process and increases the analytical precision with which submissions will be examined.
Legacy Documentation Will Not Hold Up Under Machine-Assisted Scrutiny
Such a transformation places new pressure on companies whose documentation, data governance practices or quality systems are optimized primarily for human reviewers. Much of the industry still relies on legacy document structures and unstandardized data formats that require manual interpretation. Yet an FDA supported by Agentic AI will increasingly surface inconsistencies, risk signals and data gaps early and with unprecedented granularity. As the agency has clarified, these tools operate within a secure environment and do not train on industry-submitted data, which is an important step to maintain confidentiality1. However, the implications remain clear: companies must assume that machine-assisted analytics will become part of every future interaction with regulators.
Internal Culture Must Shift—Quality, Regulatory, and Digital Can No Longer Operate in Silos
Early internal adoption of the agency’s generative AI model, Elsa, was voluntarily used by roughly 70% of FDA staff 3, demonstrating both the appetite for digital assistance and the agency’s forward momentum. While Elsa’s early deployment faced criticism for factual inaccuracies 3, the move toward more robust agentic systems reflects a commitment to maturing these tools quickly. The agency’s new Agentic AI Challenge, which invites FDA employees to propose internal AI-driven innovations1, signals an environment where regulatory workflows will evolve continuously guided not only by policy but by frontline operational insight.
Standardization and Data Integrity Will Become Strategic Differentiators
For companies, this means the window for incremental modernization is closing. In an AI-augmented regulatory environment, the quality of submissions will be assessed not just by human interpretation, but by systems trained to detect deviations from expected patterns across products, processes and sites. As hundreds of biopharma executives recently warned, systemic stress within the FDA has already raised the stakes for consistency, clarity and reliability in the agency’s review process2. The introduction of agentic AI compounds that reality.
At CAI, the significance of this shift extends beyond technology. It is a cultural realignment. When regulators adopt tools capable of rapid cross-document analysis and structured data evaluation, companies must respond by elevating the discipline with which they generate, manage and present information. Documentation must become more standardized. Data must become more traceable. Quality systems must mature to support interoperability and audit readiness. The organizations that continue to rely on inconsistent templates, site-specific variations or unstructured reports will feel the impact immediately.
AI Will Expose Weak Processes—and Reward Mature Ones
As Alice Redmond, Chief Risk & Quality Officer at CAI, often notes, “Digitization exposes structural gaps in workflows, enabling leaders to address root causes with data-driven insights.” In an FDA ecosystem supported by agentic AI, deviations that once blended into the noise of human review will stand out, can be trended and mitigation put in place. This will add to knowledge and support a Quality Culture. Conversely, organizations with well-designed data flows, structured submissions and robust governance will navigate the regulatory landscape with greater stability.
Cassidy Reid, Head of Digital Transformation at CAI, emphasizes that AI readiness must now be treated as a matter of operational resilience. “This is not about adopting AI because it is novel. It is about preparing for a regulator that now operates with more speed, analytical depth mand internal digital capability than ever before. Companies that modernize proactively will be able to adapt quickly to this new equilibrium. Those who wait will find themselves struggling to keep up.”
CAI Is AI-Ready—and Prepared to Guide Industry Through the Shift
CAI has spent the past few years building AI-ready systems, documentation practices and quality frameworks designed for precisely this moment. As the FDA adopts agentic AI, regulatory expectations are shifting toward a future where clarity, consistency and data integrity are not competitive advantages; they are prerequisites. Our teams stand ready to support clients through this transition, ensuring that operations, submissions and quality systems are aligned with the realities of a modern, technology-enabled regulator.
The FDA has taken a consequential step forward. Now the industry must decide whether to move with it – or fall behind.
References
- FDA deployment of agentic AI, its capabilities, use cases, and security posture as reported in Quality Assurance Magazine, Dec. 1, 2025.
- Staffing reductions, review delays, leadership instability, and industry concerns documented in Fierce Biotech, Dec. 1, 2025.
- Elsa large language model adoption rates, accuracy concerns, and rollout details reported in Stat News, Dec. 1, 2025.