5 Ways We're Confusing AI Capability and AI Reality with Microsoft CTO Kevin Scott
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Microsoft CTO Kevin Scott outlines five observations about the gap between AI capability and real-world deployment. Key points: (1) AI models are more capable than their current usage reflects — a 'capability overhang' — and deployment doesn't automatically follow capability improvements. (2) Models improve fastest where closed feedback loops exist, as seen in coding, but many domains like particle physics lack such loops. (3) Organizations change far slower than software, creating friction from regulation, legacy infrastructure, and human psychology. (4) High AI-driven output doesn't equal value — developers must stay focused on whether what they're building actually solves real problems. (5) Autonomous systems still require trust-building before people will delegate meaningful work to them, demanding a new way of thinking about trustworthy software.