🔎 AI Vendor Verification: Navigating Hype, Reality, and Compliance

Guide for enterprise decision-makers on verifying vendor claims regarding artificial intelligence, emphasizing that trust must shift from mere sentiment to a verifiable engineering state by 2025. The core challenge identified is the GenAI Divide, a fundamental chasm between AI's theoretical capability and the near-zero measurable ROI reported by the vast majority of organizations. The document details methods for detecting AI washing and identifying "wrapper" vendors who merely resell public foundation models as proprietary technology, recommending technical forensics like latency analysis and refusal testing. Operational reality is scrutinized, revealing that sophisticated agentic AI exhibits significant fragility in multi-step workflows and that high hallucination rates persist even with advanced retrieval systems. Therefore, organizations must mandate compliance with rigorous global frameworks, specifically citing the transparency and testing requirements of the EU AI Act, the operational standards of the NIST AI Risk Management Framework, and the certified audit process established by ISO/IEC 42006.