Why traditional validation may fall short for artificial intelligence in bioanalysis: a perspective from the European Bioanalysis Forum

In this paper published in Bioanalysis, the European Bioanalysis Forum (EBF) challenges the adequacy of traditional validation frameworks for artificial intelligence (AI) in bioanalysis, featuring insights from Stuart McDougall, Principal Research Fellow.

It argues that static, checklist-driven validation is ill-suited for adaptive, learning systems. Instead, they propose “adaptive qualification” - a dynamic, context-sensitive approach grounded in scientific oversight and continuous engagement. AI is reframed not as a tool but as a trainee, requiring lifecycle monitoring rather than one-time validation. EBF emphasises the need for scientific stewardship, collaborative ownership across disciplines, trust built on transparency and relevance and a shift from rigid compliance to thoughtful, fit-for-purpose oversight.