Who Decides? Navigating AI Governance in Clinical Research

By Andrea Bastek, Vice President, Market Strategy

As artificial intelligence becomes more embedded in clinical research, questions around governance are quickly moving from theoretical to urgent. Clear ownership of AI oversight — across sponsors, CROs, sites, and technology partners — is essential to ensure ethical use, data integrity, and regulatory compliance.

Effective governance frameworks must balance innovation with accountability, defining who is responsible for model validation, bias monitoring, data security, and decision transparency. Without alignment, organizations risk fragmented processes, inconsistent standards, and regulatory exposure. Establishing cross-functional collaboration and standardized policies can help ensure AI is applied responsibly while still delivering operational gains. For research leaders, the challenge isn’t just adopting AI — it’s building the structures that guide its safe and effective use across the trial lifecycle.

Read on to explore practical considerations for defining roles and responsibilities in AI-driven research environments.