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Create a Network of AI Champions Across the Business

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Build a credible champion network that supports adoption, captures problems, and spreads proven practices without becoming unpaid technical support.

Champions work when they are respected in their functions, given time, trained for a defined role, and connected to decision-makers. A volunteer chat channel is not a change system. This decision connects to Build an AI Strategy That Starts With Business Value and Turn Company Priorities Into an AI Opportunity Portfolio, which provide the strategic direction and portfolio context. Use this four-part leadership framework Selection — Choose trusted operators from different functions, locations, and levels—not only enthusiasts. Role — Define coaching, feedback, pattern sharing, and escalation; exclude unsupported promises. Enablement — Provide training, office hours, approved examples, and access to owners. Recognition and evidence — Allocate time, reward contribution, and measure resolved barriers and adoption quality. A practical decision example A company selects twelve champions for a six-month term. They hold short office hours, capture recurring questions, test approved practices, and escalate policy gaps. Product and governance teams respond on published timelines. This is a hypothetical example; use your own baseline, constraints, and evidence. Evidence, governance, and responsible use Use the NIST AI Risk Management Framework to connect the initiative to governance, context, measurement, and ongoing management. The companion NIST AI RMF Playbook turns those functions into questions leaders can assign and review. The GAO AI Accountability Framework is useful for examining governance, data, performance, and monitoring across the system life cycle. Compare the plan with the OECD AI Principles, particularly transparency, robustness, accountability, and respect for people affected by the system. For generative AI, review the NIST Generative AI Profile and test representative cases using OpenAI’s evaluation guidance. Use the OWASP Top 10 for LLM Applications to discuss application threats before a model can access sensitive information or take actions. Check performance statements against the FTC’s guidance on AI claims, and review information handling with the FTC’s privacy and security resources. For a broader organizational management approach, study the ISO/IEC 42001 overview. Take this to the next leadership meeting Create the champion role description, selection criteria, monthly time allocation, training path, escalation channel, measures, recognition, and rotation plan. Record the owner, evidence source, decision date, and what would cause the company to stop. The goal is not to make the document look complete. The goal is to make the next decision explicit, measurable, and accountable. Continue with Assess Whether Your Data Is Ready for AI. Use Run a Quarterly AI Portfolio Review: Keep, Fix, Scale, or Stop to revisit the decision with current evidence.

About the author

I help businesses replace manual processes with practical AI systems—and show what changed, what it cost, and what results improved.

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