AI Strategy: How to Choose What AI Product to Implement
How to pick AI projects worth building before you know if they'll work
Companies often can't tell which AI projects will actually pay off—two projects can look equally promising yet deserve opposite decisions. Researchers at real-estate brokerage Compass showed that a simple framework called expected ROI (eROI) breaks this deadlock by asking three separate questions before building anything: How valuable would it be if it worked? How likely is it to work? And what would implementation cost? This sidesteps the catch-22 that you can't estimate ROI without knowing if a project will succeed, yet can't know without building it first.
Companies waste millions funding AI projects that look good on paper but fail in practice. By separating value, likelihood, and cost into independent judgments, teams can make smarter bets earlier—and avoid costly failures. The framework works even with rough estimates rather than precise numbers, making it practical for any organization deciding where to invest in AI.