From Pilot to Platform: How AI is Reshaping Big Pharma

This week I had the pleasure of attending a Linking Leaders roundtable in NYC with industry colleagues from big pharma and big biotech, where we dove deep into how our organizations are adopting AI. While many smaller biopharma companies are still finding their footing, it’s clear that larger players are beginning to scale—moving from isolated pilot projects to enterprise-wide AI platforms. That shift is not just exciting—it’s transformative.

We shared real-world examples of how AI is already delivering measurable impact: document automation pipelines, reduced CSR and BLA timelines, intelligent site selection algorithms reducing time-to-initiation, and purpose-built GPTs that streamline operational workflows. Several organizations reported improved site enrollment rates and greater consistency in execution thanks to AI-powered insights. Importantly, many are democratizing access across teams—not limiting AI use to a specialized group, but embedding it in daily workflows for broader benefit.

Of course, we all acknowledged the limitations. AI can hallucinate or err, so human oversight remains essential. But when treated as a co-pilot—drafting, reviewing, analyzing—it enhances speed and elevates the quality of decision-making. By handling repetitive, time-consuming tasks, AI allows teams to redirect their focus toward higher-value strategic work that truly requires human insight.

We also spent time looking forward. One of the most thought-provoking parts of the conversation centered on agentic AI—systems that act autonomously or semi-autonomously. With that capability on the near horizon, we must begin preparing now. How do we govern AI agents? What safeguards and audit trails are required? How must SOPs, compliance frameworks, and team roles evolve to accommodate this shift?

Finally, we discussed the uneven global regulatory landscape. The FDA appears to be leaning into AI’s potential, while agencies like EMA and MHRA are more cautious. This disparity creates uncertainty—but also opportunity. If we can collaborate across organizations, we can shape responsible pathways for adoption that both enable innovation and maintain regulatory confidence.

AI in pharma is no longer a theoretical concept—it’s happening. And networks like this roundtable are critical for sharing best practices, tackling shared challenges, and ensuring we build not just fast, but wisely. I’m hopeful that by working together, we can accelerate safe, ethical AI adoption across the entire industry.