KPMG Global AI Pulse Q3 2026

As planned AI investment continues to rise, the report looks at what running AI at scale actually demands: whether organizations can govern where their models come from, secure what those models can reach, orchestrate how they are used, and account for what they cost. Its framing is that competitive advantage is shifting from simply adopting AI to running it effectively.

A key finding highlighted in the report is that the AI management maturity gap is narrowing as programs mature. Among organizations that report established AI ROI, 86% operate either a formal cross-functional or enterprise-wide AI management layer, including 65% that have deployed it across the whole enterprise. By comparison, only 31% of organizations still at the experimentation stage report a formal cross-functional or enterprise-wide layer, with just 10% operating it enterprise-wide.

The report is organized around four questions: how organizations are building the "harness layer" needed to govern AI at scale, including controls, accountability and orchestration capabilities; why AI maturity gaps between regions are narrowing, and why execution and management capability matter more as a result; how organizations are connecting cybersecurity, model sovereignty and provider dependency as related challenges to resilience and continuity; and why connecting AI costs to business outcomes is becoming a critical management capability, and how inconsistently organizations currently apply that discipline.

The Global AI Pulse Q3 2026 is aimed at senior business, technology and risk leaders overseeing AI adoption and governance. It is available as a downloadable report alongside an on-page summary of the key findings, and it sits within an ongoing quarterly series that also includes Q1 2026 and Q2 2026 editions and a set of Q1 2026 sector-specific insights.