Artificial intelligence (AI) is now being adopted across the Medical Affairs value chain — from Medical Information and Literature Surveillance, to scientific content generation, real-world evidence (RWE) analysis, medical writing, KOL engagement analytics, and pharmacovigilance signal triage. As adoption accelerates, so does regulatory scrutiny. A wave of legislation and guidance published between 2024 and 2026 has begun to define what ‘responsible’ and ‘auditable’ AI use looks like in the life-sciences setting.

This framework provides Medical Affairs professionals with a practical, regulation-aligned approach to auditing AI systems and their applications — whether those systems are built in-house, licensed, or, increasingly, operated by third-party vendors and business partners who deliver AI-enabled services to the pharmaceutical company. A defining feature of the current landscape is that pharma organizations remain accountable for outputs even when the AI is run by an external provider. For that reason, transparency and disclosure of any AI-involved process and output — across the company and its supply chain — is treated throughout this document as a foundational control rather than an optional nicety.

It is important to state plainly that the regulatory environment is still evolving. The EU AI Act is phasing in obligations through 2027; the FDA’s AI guidance for drug and biological products remains in draft; the EMA–FDA joint principles are explicitly non-binding; the UK is developing a dedicated AI-in-healthcare framework expected in 2026; and several APAC regulators are mid-consultation. This framework therefore emphasizes durable principles — governance, human oversight, data quality, validation, traceability, and transparency — that are likely to survive future regulatory change, rather than transient procedural detail.