Great insights and conversations at yesterday’s AI Builders Forum — The Real Cost of AI: What It Takes to Build, Scale & Succeed.

Thank you to PMI San Francisco Bay Area Chapter, eChai Ventures, and The AI Foundry for bringing together such a thoughtful group of AI founders, operators, product leaders, and practitioners.

One takeaway that really stayed with me was the discussion around the true cost of AI. AI can require significant investment in technology, data, training, workflow redesign, governance, and change management. But the greater cost may come when organizations invest in AI without first being clear about the business problem they are trying to solve.

If the solution does not improve an outcome, remove friction, reduce cost, increase productivity, or create meaningful value, then even a technically successful implementation can become an expensive experiment.

It reinforced for me the importance of continuing to ask: What business problem are we solving, how will we measure success, and do we have the right people and processes in place to drive adoption?

Technology is only one part of the equation. Successful AI adoption also depends on training, workflow design, change management, and bringing the right people along with the transformation.

And on a personal note, it was finally wonderful to see Estelle Paysinger-Hill, PMP in person, and great catching up with Sanjay Belagodu, Seyi Oshinowo, MBA, PMP, PgMP, CAL, CSPO, Sara Abolhassani, PMP, Vijay Ratthinam, Anup (Andy) Deshpande.

Thank you to all of the speakers and moderators for sharing such practical perspectives on what it really takes to move AI from experimentation to meaningful business impact.