AI Scaling Needs Decision Gates

Enterprise AI initiatives often stall because organisations approve build budgets before validating use cases, readiness, governance, and economic logic. The report explains the gap between AI investment and measurable EBIT impact, showing how strategic pressure, legacy/data/talent constraints, and late governance create repeatable scaling loops. It proposes two diagnostic paths: opportunity mapping for firms without a validated use case, and readiness assessment for firms with pilots or candidate projects. Technology leaders should treat AI scaling as a decision-sequencing problem before treating it as a delivery problem.