- The regional AI maturity gap has halved since Q1 with 64 percent of organizations in the Americas scaling AI or beyond, compared with 61 percent in Asia Pacific and 56 percent in EMEA
- US$210 million average planned AI investment over the next 12 months, up from US$186 million in Q1
- 55 percent operate a formal AI harness layer, rising to 86 percent among those reporting established ROI
- 86 percent are adapting their cybersecurity operating model for AI-accelerated threats
- 12 percent consistently assess the value of AI against its cost, rising to 48 percent among those already reporting returns
London, 24 September: The organizations furthest along in artificial intelligence are showing what scale demands, as focus shifts from whether AI works to how it is governed, secured, orchestrated and measured at scale, according to the latest KPMG Q3 Global AI Pulse Survey.
Based on a survey of 2,131 senior leaders across 20 countries, the research finds that regional AI maturity is converging while planned investment continues to rise. Sixty-four percent of organizations in the Americas are scaling AI or beyond, compared with 61 percent in Asia Pacific and 56 percent in EMEA. The spread between the leading and trailing regions has halved from 16 points in Q1 to eight points in Q3, while average planned AI investment has increased from US$186 million to US$210 million.
What scale demands
As AI adoption expands, organizations are strengthening the leadership, controls and shared systems needed to run it at scale. Fifty-five percent operate a formal AI harness layer, the controls and tooling between AI models and business use, rising to 86 percent among organizations reporting established ROI. Fifty-three percent place accountability for AI-informed decisions at C-suite level or above, including 35 percent with a named executive and 18 percent with the CEO or executive committee.
This shift towards senior ownership is matched by greater coordination across the enterprise. Employee adoption rises with organizational maturity: 34 percent report significant employee adoption of AI agents, up from 25 percent in Q1.
A formal AI harness layer becomes more prevalent as organizations mature. The report finds it is in place at 31 percent of organizations in the experimentation stage, 58 percent of those scaling AI and 86 percent of those reporting established ROI.
Scale raises the stakes
As AI moves deeper into core operations, cybersecurity, model sovereignty and provider dependency are increasingly becoming questions of resilience and continuity. Eighty-six percent of organizations are adapting their cybersecurity operations and strengthening policies, processes and controls, with concerns highest among those already achieving measurable returns.
Seventy-one percent of organizations reporting established ROI include cyber and data security among their AI budget priorities, compared with 36 percent of organizations at the experimentation stage. Model sovereignty is also moving into formal decision-making as organizations consider where AI models, data and intellectual property are hosted, controlled and governed. Seventy-two percent formally consider model sovereignty in AI decision-making, including 21 percent with an enterprise-wide strategy under regular review. Among organizations reporting established ROI, that figure rises to 53 percent. The emphasis is on managing dependency and continuity more deliberately, rather than slowing deployment.
Connecting cost to value
Despite rising planned investment, approaches to managing AI’s value and economics remain among the least mature areas of governance. The challenge is no longer simply adoption, but building the financial discipline, accountability and oversight needed to convert early benefits into sustained financial returns.
The report reveals that as AI investment rises, the next challenge is building the financial discipline and oversight needed to connect cost with value. While 61 percent review AI costs during approval and 59 percent monitor them in operation, only 12 percent consistently assess AI value against cost across the organization. The figure rises to 48 percent among organizations reporting established ROI, highlighting the growing importance of economic management as AI investment scales.
Lisa Heneghan, Global Chief Digital Officer, KPMG International, said: “What scale demands is not simply more AI, but the accountability and coordination to run it well and treat it as an enterprise-wide priority. Winning at scale requires senior leadership accountability, building governance and robust controls that turn investment into results, without losing control of risk to scale securely, sustainably and profitably.”
The report concludes that the next source of AI advantage may be how well organizations meet what scale demands: organizations that combine clear accountability, coordinated governance, resilience and reliable value measurement will likely be best placed to turn broad adoption into sustained performance.
