INSYTE: A Classification Framework for Traditional to Agentic AI Systems

Existing classification frameworks for artificial intelligence (AI) and autonomous systems are being outpaced by recent advancements in AI technologies. This limits their applicability to modern intelligent systems, particularly agentic AI systems (autonomous systems that leverage foundation models to achieve wide-ranging, multi-layered goals). To address this deficiency, we introduce INSYTE, a multi-faceted framework that supports the classification of AI systems ranging from traditional rule-based systems to cutting-edge embodied AI and agentic systems. To that end, INSYTE considers the essential characteristics of an AI system across eight key dimensions grouped into four categories: system design (underspecification and adaptiveness); functionality (breadth and depth); operating environment (diversity and dynamism); and independence from human operational control (intervention and oversight). Different AI systems (or versions of systems) yield different “patterns” on an eight-axis radar chart that INSYTE uses to provide an immediate visual summary of an AI system's overall capability, and a detailed representation of its individual characteristics. The INSYTE framework aligns with OECD's definition of deployed AI systems, which is becoming the standard definition used by legislators and developers worldwide.