From pilot to production: how governance, data access, and enterprise outcomes determine AI scaling
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From pilot to production: how governance, data access, and enterprise outcomes determine AI scaling

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Published by AINave Editorial • Reviewed by Ramit

TL;DRAI pilots often succeed in testing but stall when scaled. A Fortune Brainstorm Tech roundtable featuring Amgen, Salesforce, and Thomson Reuters highlights governance, data access, and measurable outcomes as the keys to moving from pilot to production.
An AI project can shine in a pilot yet struggle to scale. The Fortune Brainstorm Tech roundtable with leaders from Amgen, Salesforce, and Thomson Reuters emphasizes that the bottlenecks are not always the models but the organizational groundwork surrounding them. Tight governance on which pilots advance, a clear focus on enterprise outcomes, and upfront data readiness are repeatedly cited as the critical gates to production. For agentic AI, understanding the full workflow and ensuring documentation exist before deployment is essential to avoid misaligned expectations. Early discovery of data needs, privacy considerations, and security requirements helps set scalable deployments up for success. The discussion also underlines the need for cross-functional sponsorship across finance, technology, and HR to ensure a project can deliver a measurable enterprise impact rather than merely technical novelty. See the full Fortune Brainstorm Tech discussion for context and nuance: Fortune Brainstorm Tech roundtable.

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