AI ROI Gap: 71% Can’t Measure Returns (2026)

Summary

Recent 2026 research from Fortune, Deloitte, and the Futurum Group highlights a critical enterprise challenge: most organizations are investing heavily in AI, but very few can actually measure its financial impact. Only about 29% of executives report confidence in their ability to measure AI ROI, while a much smaller fraction—around 5% of enterprises—achieve meaningful, scalable returns. This measurement gap has become one of the primary barriers to AI value realization. However, the emergence of agentic AI is reshaping the ROI landscape. Early deployments report significantly higher returns, with average ROI estimates reaching approximately 171%, and up to 192% in some US enterprise cases. A large share of organizations—around 74%—report achieving positive ROI within the first year of deployment. Survey data from the Futurum Group (1H 2026, 830 IT decision-makers) also shows that AI is now producing nearly double the direct financial impact compared to earlier adoption phases. The key differentiator among high-performing organizations is not model sophistication, but measurement design: successful teams embed ROI tracking and evaluation mechanisms into workflows before deployment rather than after implementation. This shift reframes AI success as an instrumentation and governance problem rather than a purely technical one.