The short version
Why do traditional enterprise ROI metrics fail to capture the returns from AI investment in Economy 4.0 conditions, and what does this mean for how executives should govern AI programme decisions?
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Economy 6.0 is a framework for understanding the current phase of economic evolution and what distinguishes it from the digital economy phases that came before. The progression labels successive eras by what drives growth and value creation: Economy 1.0 was agrarian, 2.0 was…
AI investment ROI looks invisible because the measurement failure is structural — legacy accounting cannot see compounding, non-rival digital value, so executives must redesign measurement before scaling AI programmes.
Why do traditional enterprise ROI metrics fail to capture the returns from AI investment in Economy 4.0 conditions, and what does this mean for how executives should govern AI programme decisions?
Two bodies of research illustrate how AI value accrues above the enterprise accounting layer, from GDP-level projections to structural lags in financial reporting.
GAAP and IFRS accounting standards were designed for an economy where value lived in physical assets and was captured through depreciation and inventory. AI investment produces value that compounds (model accuracy improves with use), is non-rival (the same model can serve multiple functions simultaneously), and is largely invisible to standard capital accounting. The D1 (Digital Economy) framework names this directly: Economy 4.0 creates value through digital asset dynamics that pre-date the current accounting infrastructure. Executives who continue to evaluate AI programmes against legacy ROI frameworks are measuring the wrong variables. The McKinsey finding — that firms that redesign their measurement approach achieve 2.2x higher ROI confidence — is not a data insight; it is a governance design insight.
PwC's GDP projection is a modelled scenario, not an observed outcome. Deloitte and KPMG CFO research relies on executive self-reporting. The McKinsey "redesign group" finding does not establish causality between measurement redesign and actual performance improvement — it is possible that better-managed organisations both redesign measurement and perform better for unrelated reasons.
Three governance actions follow from the measurement failure, shifting the executive frame from cost displacement to compound value generation.
Through 2026, the built environment is moving from passive infrastructure to intelligence-led operations within D1 (Digital Economy). Digital twins of buildings have left the visualisation phase and become operational platforms that ingest sensor and asset data, predict…

Economy 6.0 is a framework for understanding the current phase of economic evolution and what distinguishes it from the digital economy phases that came before. The progression labels successive eras by what drives growth and value creation: Economy 1.0 was agrarian, 2.0 was…

Through 2026, the built environment is moving from passive infrastructure to intelligence-led operations within D1 (Digital Economy). Digital twins of buildings have left the visualisation phase and become operational platforms that ingest sensor and asset data, predict…

The Pipeline to Platform framework describes the fundamental shift in how businesses create and capture value. A pipeline business moves value in one direction: a company produces something, passes it through a chain of steps, and delivers it to a customer. A platform…