Signal over noise: what will make AI stick in pharma R&D

AI is moving quickly from experimentation to practical adoption across life sciences. The opportunity is real, but so is the noise. Predictive AI, generative AI, agentic systems, AI co-scientists, foundation models, digital biomarkers and workflow automation are all competing for attention, investment and partnership dollars. For innovators and pharma R&D leaders, the key question is no longer whether AI will matter. It is which capabilities will become embedded in the way medicines are discovered and developed, and which will remain temporary hype.

On 6 October in Basel, Switzerland, Johnson & Johnson hosted external innovators, investors, academic leaders and ecosystem partners to a discussion on what will make AI stick in pharma R&D. The recording of the program above examines where AI is already showing durable value, where expectations may be running ahead of evidence, and how external innovators can build capabilities that are differentiated, scalable and relevant to real R&D needs.