How do you build a credible internal business case for AI investment that will survive board scrutiny?

Building a credible internal business case for AI investment requires shifting from exploratory pilots to data-driven proof of ROI, as boards now demand measurable outcomes like productivity gains and cost efficiencies to justify budgets and avoid risks of overcommitment [1][2]. Start by treating AI initiatives as a portfolio, scoring and ranking use cases based on potential value, then stage-gating them to ensure alignment with business goals and mitigate misaligned bets [4]. Emphasize long-term value creation over short-term gains, incorporating robust governance for risk management and error reduction to build trust and normalize adoption [3]. Key to surviving scrutiny is demonstrating organizational readiness and disciplined measurement of returns, focusing on strategic integration rather than hype, as poor strategy often leads to losses [6][12]. CIOs must prepare evidence of financial viability and balanced investments to secure continued funding [9].