Generative AI has quickly become part of the regulatory conversation.

For medtech organizations, the opportunity is clear: support teams facing increasing complexity, growing data volumes, and rising operational demands. But in a regulated environment, potential alone is not enough. AI outputs must also be accurate, consistent, and trustworthy.

This white paper explores how leading large language models perform across representative regulatory affairs tasks, including strategic advice, technical classification, and information retrieval. It highlights where AI can add value, where it remains limited, and why human-in-the-loop approaches continue to matter.

In this white paper, you’ll learn:

• How AI performed across different regulatory task types
• Where variability and hallucinations create risk
• Why tactical support does not equal expert replacement
• What thoughtful AI adoption should look like in medtech regulatory affairs

Download now