Why AI in pharmacovigilance is a boardroom issue now

Artificial intelligence (AI) has moved from experimentation to execution in healthcare, and pharmacovigilance (PV) is leaning into its capabilities. Safety surveillance is no longer just a regulatory necessity, it is a strategic imperative as adverse events are reported, more data sources come online and novel therapies target niche populations.

That’s why the FDA’s 2025 draft guidance on AI and its Emerging Drug Safety Technology Program (EDSTP) matter far beyond regulatory affairs. For healthcare executives responsible for technology investments, compliance oversight or clinical operations, these developments mark a turning point. That point is that AI in drug safety is no longer a future consideration. In fact, it is a present-day operational and reputational concern.

AI in safety is no longer optional, it’s becoming standard

Historically, pharmacovigilance operations have relied heavily on manual workflows, with a significant portion of team capacity focused on case processing tasks. This traditional approach is no longer scalable due to rising case volumes, compressed timelines and increasingly complex data. Organizations are responding to these challenges by deploying AI to reduce manual burdens, automate literature review, draw comprehensive insight from contact centers and draft extensive safety narratives with high precision.

However, technology is only part of the story. What is also evolving is the posture of regulatory bodies. In January 2025, the FDA issued draft guidance that explicitly supports the use of AI in PV, provided organizations can demonstrate oversight, transparency and data integrity. This endorsement transforms AI from an internal experiment to a sanctioned, auditable part of regulatory operations.

Healthcare executives must come to terms with the fact that ignoring AI in PV is a potential liability. Teams still relying on purely manual processes, if they don’t already, will certainly struggle to meet future expectations for speed, consistency and traceability.

The talent equation is changing faster than ever before

One of the least discussed but most disruptive effects of AI in PV is its impact on shaping the workforce of the future. Safety teams are becoming more efficient and gaining new skills. While automation can handle high-volume tasks, human oversight remains essential for interpreting results and ensuring clinical and regulatory integrity.

Today’s PV teams must be fluent in medical terminology and machine learning basics. They need to know how to question algorithmic outputs, identify gaps in training data and escalate ambiguous findings for expert review. This shift won’t happen automatically or without intentional effort. 

Organizations must invest in reskilling programs, create interdisciplinary roles and bring safety professionals into the loop when designing AI systems. Otherwise, technology risks being underutilized. For COOs, CHROs and compliance leaders, the message is evident that success with AI starts with people, not platforms.

Strategic use cases drive real-world value

Not every task in PV benefits equally from AI or needs it, and treating automation as a blanket solution is a recipe for frustration among all team members. The best results come from targeted, high-leverage applications that directly reduce cost, enhance speed or improve accuracy.

For example, AI-enabled literature monitoring tools can significantly reduce manual review time while improving consistency across global teams. Natural language processing in contact centers can flag adverse events in real time, helping sponsors triage faster and report sooner. Drafting support for safety narratives saves time and ensures that human reviewers can focus on nuance, not formatting.

In all these examples, the common denominator is that AI-based tools don’t replace experts. Instead, they make them more effective. These tools also free up budget and headcount for higher-value tasks, which is particularly important in today’s constrained financial environment. If you’re a CFO or in an operational strategy role, these are the efficiencies that matter and are what make AI a value multiplier.

Regulatory confidence is earned, not assumed

While the FDA has unlocked the door for AI, the doorway is not yet wide open. Organizations must still prove that their systems are reliable, explainable and appropriately governed. That includes maintaining detailed records of model assumptions, version histories, validation results and decision traceability.

The EDSTP offers an important forum for proactive dialogue, allowing companies to engage directly with FDA officials about their AI use cases in PV. These conversations are non-binding but highly valuable and serve to help shape future development strategies that are compliant by design.

Healthcare executives responsible for quality, technology or enterprise risk should see AI regulation not as a hurdle, but as a chance to become an industry leader. Building a transparent, auditable framework isn’t just about remaining compliant. It’s about earning trust with regulators, investors and the general public. The takeaway is simple: early investment in governance pays off. A penny today can become a dollar tomorrow.

If you’re starting now, you’re late

The organizations seeing the most success today started their journeys years ago, with pilot programs, stakeholder education and early regulatory engagement. This early adoption is now paying off, but there is still time for other organizations to start their journeys.

Those who wait until the next guidance is finalized may find themselves racing to catch up, not just in technology, but in readiness, resourcing and reputation. The organizations best positioned for future compliance are those already engaging in EDSTP discussions, building internal AI fluency and embedding oversight into every step of their safety workflows. 

From safety to strategic differentiator

PV used to be a back-office function that was critical but invisible. That era is ending. As AI transforms how safety is managed, it also changes who needs to be at the table. CIOs, CFOs, CHROs and quality leaders must all align around the shared goal of driving innovation and set forth measurable outcomes.

The FDA’s 2025 guidance doesn’t just give the green light to AI. It sets the tone for what comes next, including cross-functional collaboration, real-time adaptability and systems that combine automation with judgment.

Healthcare’s future will be shaped by how we manage data, detect risk and act on insight. In PV, AI isn’t just enabling that future, it’s accelerating it.