Brian Lewis, an AI product lead at Millennium speaking in a personal capacity, describes the gap between an impressive AI demo and an enterprise contract. His evaluation funnel narrows many potential vendors into a few demos and very few signed deals. Useful products must solve a defined problem, integrate from the start and meet success criteria set by the buyer.
Lewis highlights practical requirements across security, reliability and legal review: controlled data retention, configurable access, working admin APIs, audit logs, deployment management and reachable support. He describes pilot failures involving broad default permissions, undocumented changes and data practices that contradicted vendor promises.
The buyer also has work to do. Lewis argues that clean architecture, centralized knowledge, integrations and change management are essential foundations for AI adoption. Agents inherit existing access problems and can amplify them, so stronger models cannot compensate for weak entitlements or unreliable enterprise systems.
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