AI implementation and strategy for cultural organizations.
Sort work you do into three buckets: Work AI can do alone, work people and AI do together, and work only people can do.
The comforting myth is that AI frees you up for the third, work only humans can do.
Nice sentiment. Not what happens.
What actually happens is the hybrid work bucket swells (work AI and people do together).
More of your time goes to directing AI, judging what comes back, and shaping how to make AI work better. So the work is “K-shaped” — at once, more strategic and more mundane at the same time.
(Worth a read: AI Doesn't Reduce Work—It Intensifies It, HBR, Feb 2026)
So. AI work is (for now) intensely human work.
And it’s why I believe that the real work of today for any organization is helping your team get genuinely good at leading the AI.
Things that AI is good at today with one-shot/ little guidance from you.
Summarize the board packet.
Pull the giving history on a donor.
Draft a first pass at the grant narrative.
This type of work grows every month as AI companies add to their feature set. Just keeping up with this type of AI capability is a lot!
The hybrid work — this area of work is growing fastest. Read the Harvard Business study above. This is work where you and AI do a lot of iterative rounds together. A rough draft shaped into something that sounds like you. A workflow that used to cross three departments now mapped into some automation. Someone has to steer, and that someone knows the organization (you).
This is the promised land of what AI is selling us. (“If AI does all the other stuff… what creative green glades do you get to spend your days in?”)
Except. AI needs human guidance. Constantly.
For the foreseeable future, human-only work relative to AI is a thin but growing slice of reality.
But. The ALWAYS-human work has never been more valuable and worth honing. Humans will always be better than AI at many things.
What should this season feel like?
How do we reach the people in our community not attending?
How will this exhibition land in our community?
Is this marketing text tone-deaf?
How will that donor react?
Every piece of software you run now has AI. Which raises lots of questions.
Every one of those has a price tag. Duplicate licenses, exposed data, staff hours, overhead sprawl.
More AI is not better AI.
We need knowledge, coordination, methodical, applied AI.
And governance.
This is my work.
I am a unifying voice of AI problem solving across the building. (Often, the extra set of hands your IT team wishes they had.)
I partner with whoever owns the AI question — CIO, CTO, COO, Executive Director — then embed with the teams we're solving for.
Cross-organization questions surface. We discover the right solutions (which may or may not be AI). Then we get to work: build, configure, test, train.
The team knows how it works when I leave because they helped build it. Your AI governance catches up to what's actually happening because we make sure it does.
Every one of them ends the same way — your team comes out more AI-capable, and less dependent on me.
Good discovery for AI connects your top organizational pain points/ opportunities with the current state of AI.
The discovery process is a compact and thorough research phase to uncover how your organization functions today. These findings connect with my knowledge of current-state AI. You arrive with a prioritized roadmap of highest-value AI opportunities for your organization.
I do not build black box solutions and sell you a maintenance plan. AI is iterative and ever-evolving technology. It needs to be built differently. Try/learn/try/learn. With AI, you learn by doing. And by building it next to me.
Outcome: Good AI solutions get delivered (eye on the prize with ROI and meeting the objectives squarely). Your team learns by doing (without getting swamped or sidetracked). Best part: the team knows how to fly the plane (and build more planes) when I’m gone.
Governance is all about leadership, alignment and clarity across the organization. And it’s more about being a practice-in-motion than a set of documents or committees.
I work across the organization to surface clarity around organizational values, ok/not-ok’s with AI, where experimentation is encouraged, how data should be handled with AI systems and how staff should surface questions as AI evolves. Good governance is building a living practice, not a set of documents.
AI transformation is organizational transformation. As work evolves, so do job functions and team dynamics. Much of AI transformation is about empowering your people, providing clarity and equipping them with optimism and skill. None of how this happens this is obvious for teams-in-transition. Busy executive teams may not have capacity to take this on fully. I bring 15 years of arts-sector technology leadership and AI focus to the table. Covertly or overtly, I can augment your busy executive team with help making the organizational turns you need to make with as your organization evolves.
I am platform-agnostic, model-agnostic (even somewhat AI-agnostic). My work is helping the cultural sector leverage emerging technology while keeping true to themselves.
Beliefs that guide my work:
The AI era rewards a particular set of skills. Skills I've spent a career learning:
I am platform-agnostic, model-agnostic (even somewhat AI-agnostic). I have no horse in this race except helping the cultural sector leverage current technology while keeping true to themselves.
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ReadAn AI consultant for arts and culture helps museums, performing arts organizations, and cultural nonprofits decide where AI genuinely fits, put it to work hands-on alongside staff, and govern its use as the technology keeps moving.
Readiness and opportunity mapping, hands-on implementation, living governance, and successful collaboration with the people inside the institution charged with AI success.
Modern organizations need great technology to run. The goal is not “more AI.” The goal is AI effectively applied to hard business problems where AI can help most. My job is helping organizations make clear choices about what tasks belong with people, what tasks belong with tools (and which tools), and what needs both. Against a fast-evolving AI landscape.
No conversation is too small or too big. It's low-key discovery in both directions.