This session lays out a practical blueprint for standing up an AI Center of Excellence - how to centralize tool vetting, build a shared prompt library, and create a single source of truth without becoming a bottleneck that slows every team down. It covers how to position the CoE as a resource teams want to use rather than a gate they must pass through, since adoption depends heavily on that distinction. Attendees will look at phased approaches suitable for organizations with no existing structure, as well as adjustments for those refining an early, informal version of one. The session closes with a practical rollout plan participants can adapt and propose internally.
Every department reinventing its own AI approach from scratch is not just inefficient, it is a governance and quality risk hiding in plain sight, department by department. Leaders often assume this fragmentation will resolve itself as teams mature, but without a central structure, it tends to calcify instead, with each department's habits becoming harder to unwind the longer they persist. If your organization has more than a handful of teams independently experimenting with AI, this session addresses a structural problem that training alone cannot fix. The earlier a CoE is introduced, the less entrenched resistance you will face from teams used to going it alone.
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