At the Pharma Meets AI conference in Barcelona, Spain, in April 2026, discussions around AI governance highlighted a clear shift from high-level policy frameworks to more integrated, operational models. As artificial intelligence (AI) adoption scales across pharmaceutical organisations, governance is no longer being treated as a standalone function but is increasingly embedded within core business processes.
Kathrin Hahn, data privacy, digital, and AI lead at Novartis, outlined how effective AI governance requires a comprehensive “integrated assurance” approach, bringing together governance, risk management, compliance, and internal controls under a unified framework. This ensures accountability is clearly defined while enabling consistent oversight across AI use cases.
Go deeper with GlobalData
A key focus is the responsible use of AI, guided by principles such as transparency, data protection, and ethical deployment. However, beyond principles, Hahn emphasised the importance of translating governance into practical implementation. This includes embedding AI risk and compliance structures directly within business functions, supported by continuous monitoring, audits, and clearly defined accountability at the operational level.
Notably, the shift towards “AI governance 2.0” reflects a broader cultural transformation, where AI is no longer confined to specialist teams. Instead, employees across the organisation are expected to engage with AI tools, supported by training, awareness initiatives, and defined performance objectives.
As AI becomes more pervasive in drug development and commercial functions, embedding governance into day-to-day operations will be critical to ensuring both innovation and responsible use at scale.
