AI in Pharmacovigilance: Separating Signal from Noise

Jul 30, 2026 | Christina Kim

“Where do we start with AI?” After meeting with PV leaders at events and roundtables over the last 12 months, this is the core question I hear most often.

PV teams are struggling with the gap between the promise of AI and the operational reality. AI will undoubtedly add value to PV operations. Until then, the day-to-day workloads including case intake, literature reviews, and aggregate reports, continue to increase while headcount remains flat and operational costs rise.

As workloads grow, lean teams face increasing pressure to adapt by adopting AI and new ways of working or risk falling behind. With continual AI announcements and new vendor automation and AI offerings—some proven and others aspirational, it can be difficult for teams to separate the signal from the noise. Most organizations cannot afford to pilot multiple AI solutions to determine value, especially with the required validation and change management efforts.

So where should teams start? Begin by asking these two questions to guide a strategy that supports immediate results and future growth:

• Where can AI deliver the greatest value today? Understand where your teams are spending the most time on repetitive, manual work.
• Do you have the right foundation for AI? AI is only as effective as the data and processes that support it.

Identify high-impact opportunities to deliver immediate value

Key opportunities for AI and deterministic automation are repetitive, manual processes that consume the most time. Here are two examples highlighted in recent conversations with PV leaders:

• Literature reviews: A PV leader with a team of four told me he spends a minimum of 10 hours a week combing through literature articles and navigating spreadsheets from his vendor.
• Duplicate case detection: Another safety operations head tracks duplicates manually in Excel every Monday because his vendor charges for every case touched, even if it is invalid or a duplicate.

Headcount rarely grows ahead of demand, but case volumes, SDEAs, and reporting obligations continue to increase. Organizations that scale most effectively aren’t simply adding people; they’re building a foundation that allows AI and automation to take on more work without linear headcount growth.

Build the foundation to scale AI

The right foundation starts with your safety data and processes. If your safety operations, data, and content are fragmented across multiple systems, or your safety data is managed outside of your PV system by CROs, it will take more time and effort to realize value from AI.

Organizations that own its safety data and content within a unified safety platform improves operational efficiency through connected processes and deterministic automation. It also provides the context needed for native, industry-specific AI to support PV-specific tasks, workflows, and business processes. Sponsors, CROs, and other partners can collaborate in the same sponsor safety system, improving security, compliance, data consistency, and operational efficiency.

What’s eating up your team’s time right now? Send me an email and let me know. Your feedback directly shapes what we cover next.

A couple of quick opportunities in the meantime:

• Join our upcoming Veeva AI for Safety webinar to learn more about Veeva AI and where we are heading. Livestreams are hosted on Veeva Connect, so you will need to use your company email address for access.
• Save the date for Veeva R&D and Quality Summit in Boston (Oct 20-21). We are hosting an invite-only roundtable for emerging biotech safety leaders. Send me a note if you’d join us.

Bringing Together Agentic AI and Rules-based Automation to Modernize Pharmacovigilance

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By bringing together deep AI agents and rules-based automation, Veeva’s approach increases efficiency and productivity while maintaining control and oversight.

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