The numbers are in, and they spell change for life sciences. 

That’s because nearly three-quarters (73%) of global pharmaceutical organizations are actively planning, piloting, or deploying agentic AI initiatives. 

This widespread means agentic AI is no longer a futuristic concept, but a present-day imperative for staying competitive and delivering life-changing medicines faster.

For those not yet in the know, agentic AI is a sophisticated form of AI designed not just to analyze data, but to act autonomously, plan, reason, and execute complex, multi-step tasks. This goes far beyond traditional automation. Instead, agentic AI is about creating intelligent systems that can drive innovation, accelerate drug development, and optimize operations like never before.

So, which companies are leading the charge, and how exactly are these intelligent agents reshaping the pharma landscape? Let's dive into the specifics.

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It’s been said that the only constant in the world is change. 

For decades, clinical trials have been a human only endeavor, with teams of clinicians, study teams, and patients working hand in hand to bring the latest molecules to market. Now, a new central actor has entered the clinical paradigm, agentic artificial intelligence. 

Only three years after OpenAI kicked off the artificial intelligence arms race, AI has gone from requiring users to prompt it, to pre-emptively identifying bottlenecks, safety risks, and more, thanks to agentic AI. 

Agentic AI is an autonomous, goal-oriented system that uses reasoning and external tools to independently plan, execute, and adapt multi-step actions with minimal human intervention to achieve complex objectives. 

Sponsors and CROs have begun using AI agents across their workforces to improve trials in ways that humans have traditionally struggled to accomplish. For instance, organizations have been creating AI agents to analyze prior trial protocols, benefiting from lessons learned across prior trials and real-world outcomes, enabling teams to anticipate risks and automating elements of submission drafting. Anomaly detection has helped teams better identify outliers in operational metrics or safety signals, prompting early interventions. Document intelligence accelerates medical writing by grounding generative outputs in verified data, which reduces cycle time without sacrificing accuracy. 

However, in each of these use cases, humans remain squarely “in the loop.” Or rather, the decision making isn’t left entirely to AI. Instead, the objective is to augment clinical, regulatory, and legal teams with tools that surface the right information at the right time.

This core concept, keeping a human in the loop, is essential to clinical decision making and operations as agentic AIs, while powerful, are not inherently suited to fully autonomous operation in all regulated contexts.

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The 2025 ESMO AI & Digital Oncology Congress, held in Berlin from November 12 to 14, highlighted the accelerating role of artificial intelligence across the oncology care continuum. Although imaging and pathology remain the most established fields for AI adoption, this year’s programming revealed a decisive shift toward workflow-integrated AI that enhances clinical operations, supports trial efficiency, and addresses the realities of patient monitoring. 

Across three days of sessions, side-room conversations, and industry demonstrations, one theme was clear. AI is evolving from experimental add-on technology into a practical clinical teammate, but scaling its impact will require robust validation, seamless integration, and a sustained focus on clinician trust.

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