“How should we use AI?” is an understandable question for a CEO or operational leader. It covers so much ground that answering it directly often produces a tour of possibilities. Someone shows tools, describes competitors, and draws a roadmap. You leave with plenty of ideas, but it can still be difficult to explain which one matters to your company and why it should come first.
I'd start a little closer to the work. How does your business create value today? Where do capable people have to compensate for a process that makes their job harder? What would you like customers to experience differently? You don't have to know the answer before we begin. Those questions help us discover the places worth examining.
As possibilities emerge, we can make each one more specific:
Where is the business experiencing a costly friction, and does AI deserve the right to be tested there?
Now we can ask who experiences it, what happens today, what has already been tried, and what improvement would mean. We can also discover that AI adds little, that another approach is simpler, or that the company needs to prepare before testing anything. Those are useful answers because they change where you put your attention.
AI can touch almost every activity in a company. Your ability to take on change is much more limited. As a leader, you decide which questions deserve investigation, which uses are ready to test, how much learning you can afford, and what evidence would justify more investment. You also decide what to stop and what can remain at a perfectly ordinary level of capability.
The method has four movements:
- Map the business. See where value is created, delayed, lost, protected, or put at risk, and use that view to discover several candidate opportunities.
- Choose the strongest opportunity. Compare the candidates using business impact, likelihood of success, adoption friction, time to evidence, and cost and risk. Explain the reasons before choosing what deserves attention.
- Buy the evidence cheaply. When conditions support a test, use a small piece of real work, a business owner, and a decision rule agreed in advance. When they don't, prepare, measure, or wait deliberately.
- Manage what follows. Decide whether to stop, continue, invest, or industrialize, and keep those choices together as a portfolio of business outcomes.
You can do this without becoming an AI expert. You will need people who know the work, room for facts that challenge the plan, and a willingness to change your mind. The method gives that conversation a structure so you can make one justified decision and learn enough to make the next.