A CEO does not need to understand how AI models work to steer an AI strategy well. The job is to ask questions that force clarity: where will AI create value, what could go wrong, who is accountable, and what will we do in the next 90 days? If your leadership team can answer the seven questions below in plain language, you have a strategy. If they cannot, you have a list of tools.
1. Where will AI create value in our business?
Ask for specific workflows, not general ambition. "Use AI in customer service" is a wish; "draft first replies to routine customer emails so staff review instead of write" is a candidate. Good starting points tend to be work that is frequent, text-heavy, rule-bound enough to check, and painful today. Ask the team to rank candidates by value and by how easily the output can be reviewed.
2. What is the measurable outcome?
Every use case should name what changes: hours saved, turnaround time, error rate, or quality of a deliverable. Agree on the baseline before the pilot starts, otherwise nobody can say later whether it worked. Our guide to measuring AI training ROI covers the same discipline for the people side.
3. What are the risks, and which ones can we accept?
Ask the team to list the failure modes: wrong answers presented confidently, confidential information pasted into the wrong tool, inconsistent output, over-reliance. Then ask which are acceptable for which tasks. An internal brainstorm tolerates errors that a customer-facing quote or a regulatory filing does not. See what an AI hallucination is and which tasks you should not automate.
4. What data will AI touch?
Ask exactly which data goes into which tools, who approved it, and where it is processed. Customer and employee personal data deserves particular care. Our overview of AI governance and PDPA in Malaysia is a starting point. This is general information, not legal advice; confirm specifics with your legal or compliance team.
5. Who owns this, and where do humans stay in the loop?
AI initiatives stall when everyone is interested and nobody is accountable. Name one executive owner, and define for each use case where a person reviews the output before it has an effect. The idea of human in the loop is the simplest control a company can apply, and it should be decided at design time, not after an incident.
6. Are our people ready?
Tools without skills produce uneven results. Ask how many staff use AI regularly today, how well, and whether practices are shared or each person improvises. Training, a usage policy and a few agreed templates usually matter more than the choice of tool. Agmo Academy's AI training programs and the AI Forward CXO Program for senior leaders address this; in-house options are on the corporate training page.
7. What will we do in the next 90 days?
A strategy that cannot be started this quarter is a slide. A workable 90-day shape looks like this:
- Days 1–30: pick two or three use cases, set baselines, publish a short usage policy, and name the owner.
- Days 31–60: run small pilots with a handful of users, with review steps in place, and collect honest feedback.
- Days 61–90: compare results to the baselines, decide what to stop, scale or redesign, and plan training for the next group.
The mechanics of a pilot are covered in how to run an AI pilot.
Questions to ask your own leadership team
When the answers come back, listen for warning signs: vague benefits, no named owner, no mention of data, or a plan that depends on one enthusiastic person. Strong answers are specific, include what will be checked by a human, and admit what is still unknown. Agmo Academy is the training arm of Agmo Holdings Berhad and an HRD Corp registered training provider; eligible training may be claimable, subject to eligibility and HRD Corp approval.