FT Pharma Leadership Forum

Harnessing AI and Data to Transform Pharma Commercial Growth

The pharmaceutical industry is navigating a perfect storm of challenges that are profoundly reshaping its commercial landscape and impacting future growth prospects. Intensifying pricing pressures are forcing manufacturers to justify product value with hard evidence. Changes in national healthcare systems and the growing role of health technology assessment in healthcare decision making further add to commercialisation complexity. Simultaneously, R&D costs continue to increase, creating a significant financial burden on companies. This confluence of external pressures is forcing a re-evaluation of every aspect of the business.

In this context, the accelerating adoption of Artificial Intelligence (AI), along with advances in agentic AI, presents both an opportunity and a new set of complexities. AI promises to streamline drug discovery, optimise clinical trials, and personalise patient engagement, potentially reducing costs and accelerating market access. However, it also demands significant investment in new technologies, talent, and data infrastructure. For those responsible for P&L, and digital leaders, it will mean re-evaluating strategic investments in R&D and digital infrastructure, whilst overseeing a workforce and cultural transformation that requires re-skilling of teams, enabling them to navigate complex digital ecosystems. Brand and commercial teams will need to redesign personalised, integrated customer journeys that span digital and in-person touchpoints, demanding a deep understanding of patient and physician preferences.

This event, held in partnership with Indegene, will bring together financial, commercial and digital leaders from pharmaceutical and biotechnology companies to share insights on how they are adjusting to the new commercial realities of pharma and overcoming complexities of enterprise-wide adoption and implementation of AI to enable innovation at scale, drive growth, and shape future business models.