AI is accelerating what happens upstream in the life sciences pipeline, but manufacturing capacity cannot be created overnight. For Colm Bambury, Director of Digital Technology at Amgen, that makes it increasingly important for manufacturers to get more from the sites and capabilities they already have. Ahead of his session at the Life Sciences Industry Conference 2026 on Thursday 22nd October at the Crowne Plaza Hotel, Santry, he shared his perspective on where AI can create practical value.

The opportunity is not simply about improving efficiency. AI can help manufacturers improve reliability, planning, throughput and the speed of decision-making, helping sites respond to increasing demands across the pipeline. Bambury sees a clear risk for organisations that delay: "It is allowing the gap between pipeline ambition and manufacturing readiness to grow." With manufacturing networks operating within complex GMP requirements, making better use of existing capacity will become an increasingly important part of the challenge.

Scaling AI successfully also requires agreement between manufacturing, quality and digital teams before the technology is deployed. Bambury identifies five areas that need to be clear: the problem being solved, who owns the data, the level of risk that is acceptable, where human accountability sits and who will operate the capability after launch. Teams must also decide what should be standard across a manufacturing network and what needs to remain specific to individual sites. Without that alignment, "a successful AI demonstration can remain just that, a demonstration."

His picture of an AI-ready site is less about visible technology and more about how people work. "What would feel different is how quickly people can move from a question to a trusted answer and then to action." Data would be accessible, secure and placed in the right context, while AI would become part of everyday work rather than sitting outside normal operations. Governance would be built into the process, and employees would have the confidence to use AI while understanding when its output needs to be questioned or escalated.

For life sciences leaders, Bambury believes the key question is: "Where is a real operational constraint that AI could help us remove, and what is preventing us from acting?" For site leaders still considering the conference, he sees value in hearing how others are approaching the same challenges. "No organisation has all the answers." Comparing practical experiences and challenging assumptions can help manufacturers understand what is working as AI adoption continues to develop.

That openness is also what Bambury values about engaging with the wider life sciences community. Many organisations are facing similar questions around data, technology, governance and adoption, creating opportunities to share experience rather than solve every challenge independently. "Open conversations help us test our thinking, learn from one another and build relationships that may allow us to tackle some of those challenges together."

Full details and registration are available at pharmaawards.ie/conference, and subscribe to the newsletter for speaker announcements and agenda updates.