Our leadership team is spending dozens of hours every week debating which AI-driven workflows we should build next, but we have no objective way to measure the opportunity cost of these projects. How do we use Keith Cunningham's Thinking Time framework to structure a rigorous filter that prevents us from chasing bright shiny AI objects at the expense of our core profitability?

Question

Tyler Smith · Accepted Answer

Without a disciplined filter, a leadership team can easily burn hundreds of hours chasing shiny AI tools that produce zero bottom-line profit. To stop this waste of resources, you must use Keith Cunningham's Thinking Time framework to rigorously evaluate every proposed AI integration.

Schedule a dedicated forty-five minute Thinking Time session with your leadership team. Before you begin, formulate a highly targeted, high-value question designed to cut through the technological hype. Frame the question using the "How might we... so that we can..." structure.

Use these questions to guide your session:

- How might we automate our client onboarding process so that we can reduce delivery time by fifty percent while maintaining our current client satisfaction scores?

- How might we integrate AI into our research workflows so that we can double our team's capacity without hiring additional analysts?

Compare the potential profit impact of each proposed workflow against your V/TO 1-Year Plan. If a project does not directly move the needle on your top three priorities, add it to your long-term Issues List and table it.

By forcing your team to answer these structured, high-value questions, you shift the conversation from technical feasibility to strategic profitability. This discipline ensures you only allocate engineering and operational resources to AI projects that deliver a clear, measurable return on investment.