The work is implementing AI (the outcome goes well beyond that)
Every cultural organization trying to get somewhere with AI has to bring three things into alignment.
THE INDIVIDUAL HUMAN VOICES. Organizations are made up of a group of individuals, all with strong opinions about AI. As I wrote yesterday in part 1: AI is always personal before it's professional. Every one of us as individuals arrives with our own opinion and stance about AI and that opinion is personal. AI strategy that overlooks the individual voice will get the technology right but the people wrong. First principle. Human opinion is squishy. Respect the squish. Love the squish.
THE ENABLING TECHNOLOGY ITSELF. What AI can do right now for culturals keeps changing and 2026 is moving fast. Agents are doing credible autonomous work, increasingly so in just the last few months. Frontier models are constantly outpacing themselves on long-running complex tasks and memory context. AI code-writing tools are turning any team on earth into a potential software team (one of the most exciting things about AI to me this year). The AI-meets-cultural-org greenfield is wiiiide open and people hear very different things standing at its brink. Wide-open horizon? Menacing unknowns? Both reads hold part of the truth. The technology has to be mapped honestly: what's feasible, what's emerging-feasible, what's hype. That’s what I help you do.
THE INSTITUTIONAL SOUL. Your reason for existing organizationally. Your principles and values meets your annual ticket sales/admission and fundraising goals. Your history. Your people. Your vibe. YOU. Obviously none of you lose this core on any topic but AI strategy that does not actively recenter on this over and over can introduce accidental drift. Keeping up with AI is like tapping your toe and rubbing your stomach at the same time. Easier than it looks. I always keep your center at the center while thinking widely and creatively with AI enablement.
My work with organizations as AI advisor is all about helping you align all three of these while focusing on getting the tech of AI right. I’m extra horsepower and deep expertise leverage that is useful for leadership teams as you weave all three of these things into a cohesive, org-specific AI roadmap and execution lane.
The work is AI. The outcome is deeply org-wide and goes well beyond AI.
This post is part 2 of 3. Part 1: Why AI is personal before it's professional. Part 3: How I do the work.
