Pharma Case Study 1: Platform-Dependent Treatment Recommendation Divergence in Oncology

Abstract Conversational AI systems are increasingly used at the point of therapeutic choice in oncology. In structured decision-stage testing across multiple leading AI systems, identical treatment-selection questions produced materially different “preferred therapy” outcomes depending solely on platform. The divergence did not arise from guideline deviation or factual error. It emerged from structural differences in comparative framing and recommendation compression. This case study documents the observed behaviour in anonymised form and examines its governance implications.