Commentary|Videos|January 14, 2026

Breaking Out of AI Pilot Mode in Clinical Development

See what will distinguish sponsors that scale AI into core operations from those stuck in experimentation, and why redesigning underlying processes—not just optimizing workflows—is critical to realizing long-term value.

In a recent video interview with Applied Clinical Trials, Liz Beatty, co-founder and chief strategy officer at Inato, discussed how sponsors can balance efficiency pressures with patient access as competition for sites and patients intensifies. Beatty explained that while AI-driven tools are accelerating protocol design, feasibility, and trial operations, overreliance on a small pool of familiar sites can create bottlenecks that undermine those gains. She highlighted a shift away from historical site performance data toward real-time patient eligibility insights, enabling more accurate trial planning and inclusive site selection. Beatty also outlined how community research sites can remain competitive by using technology to demonstrate verified patient access and readiness. Looking ahead to 2026, she emphasized that sponsors able to move beyond isolated AI pilots—by redesigning underlying processes and committing to scaled change management—will be best positioned to shorten timelines and expand access to clinical trials.

The interview transcript was lightly edited for clarity.

ACT: What will distinguish pharma companies that move beyond AI pilots in 2026 from those that remain stuck in experimentation?

Beatty: Every sponsor we speak with understands the importance of AI. It has been a buzzword in 2025, and it is not going away. The question is no longer whether AI matters, but how companies move from experimentation to real impact.

Pharma is understandably risk-averse, and many companies remain in pilot mode, running small experiments that never scale. The challenge is that you will never fully realize the value of AI if it remains isolated in pilots. Unlocking impact will require scale, operational change, and a deliberate focus on change management.

In 2026, I expect a small group of sponsors to break out of this pattern. They will start with a clear vision and organizational buy-in at every level for how AI will reshape the company. Leadership will need to accept both the upside and the initial friction, and teams will need to be empowered to push through that discomfort.

AI delivers limited value when it is layered on top of broken processes, which is a real challenge in pharma. The companies that pull ahead will be those willing to rethink and redesign how work gets done, not just optimize around the edges. Sponsors that go bold in 2026 will realize real efficiency gains and competitive advantage while others remain stuck debating how to move beyond pilots.

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