Treating enterprise AI as an operating layer
View original at technologyreview.comMIT Technology Review - Ai Research Title: Treating enterprise AI as an operating layer Date: 2026-04-16 13:00 Source: https://www.technologyreview.com/2026/04/16/1135554/treating-enterprise-ai-as-an-operating-layer/ <p>There’s a fault line running through enterprise AI, and it’s not the one getting the most attention…
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The prevailing narrative says nimble startups will out-innovate incumbents by building AI-native from scratch. If AI is primarily a model problem, that story holds. But in many enterprise domains, AI is a systems problem—integrations, permissions, evaluation, and change management—where advantage accrues to whomever already sits inside high-volume, high-stakes operations.
60% confidenceThe goal is to permanently embed the accumulated expertise of thousands of domain experts—their knowledge, decisions, and reasoning—into an AI platform that amplifies what every operator can accomplish, producing a quality of execution that neither humans nor AI achieve independently.
60% confidenceModel providers like OpenAI and Anthropic sell intelligence as a service that is highly capable and increasingly interchangeable. The distinction that matters is whether intelligence resets on every prompt or accumulates over time.
60% confidenceAn AI-native platform inverts traditional architecture by ingesting a problem, applying accumulated domain knowledge, executing autonomously what it can with high confidence, and routing targeted sub-tasks to human experts when the situation demands judgment that the system can't yet reliably provide.
60% confidenceIf an organization processes 50,000 cases a week and captures just three high-quality decision points per case, that's 150,000 labeled examples every week without creating a separate data-collection program.
60% confidence
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