Every board meeting, every investment committee, every strategic planning session features the same question: Should we invest in AI?
The answer is never simply yes or no. The real question is whether a specific AI application meets three criteria that separate transformative investments from expensive experiments.
Question 1: Does it solve a problem that already costs you money?
The best AI investments replace existing costs, not create new capabilities. A manufacturing company spending $2M annually on quality inspection has a clear target. An AI system that reduces defects by 40% pays for itself in months, not years.
Question 2: Can you measure success in 90 days?
AI projects that take 18 months to show results rarely show results at all. The technology moves fast, the team loses focus, and business priorities shift. The most successful AI deployments I have seen share a common trait: measurable impact within one quarter.
Question 3: Who owns this after launch?
Identify the person who will own the system six months after launch. Not a team, not a department, a person with a name, a budget, and authority. If that person does not exist, the investment will fail regardless of initial performance.
These three questions form a simple filter: quantified problem, 90-day milestone, named owner. Projects that pass all three succeed far more often than those that pass one or two.
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