KPMG International released its first Global AI Pulse survey on March 31, 2026, and the headline number is hard to ignore: despite organizations planning to spend an average of $186 million on AI over the next 12 months, only 11% have reached the stage of deploying and scaling AI agents in ways that produce enterprise-wide business outcomes.

The survey polled 2,110 C-suite and senior business leaders across 20 countries, with three-quarters of respondents representing organizations with annual revenues exceeding $1 billion. It is the most comprehensive look yet at the gap between AI investment and AI results.

Big Spending, Uneven Returns

The data paints a picture most business leaders will recognize. Investment in AI is accelerating everywhere. Planned spend is highest in Asia-Pacific ($245 million average), followed by the Americas ($178 million) and EMEA ($157 million). But spending more has not translated to results for most organizations.

While 32% of respondents say they are deploying and scaling agents, and 27% are orchestrating multiple agents across their business, the 11% figure reflects a much more demanding benchmark: agents actually driving enterprise-wide business outcomes. Not one department. Not one workflow. The whole organization.

KPMG’s Global Head of AI and Digital Innovation, Steve Chase, put it plainly: “The first Global AI Pulse results reinforce that spending more on AI is not the same as creating value. Leading organisations are moving beyond enablement, deploying AI agents to reimagine processes and reshape how decisions and work flow across the enterprise.”

What the 11% Are Doing Differently

The organizations in that top tier are not just running more AI tools. They are deploying agents that coordinate work across functions, route decisions without human sign-off at every step, and surface insights from operational data in near real-time. The agents flag anomalies before they become incidents, not after.

The performance difference is substantial. Among the AI leaders, 82% say AI is already delivering meaningful business value. Among their peers, the figure drops to 62%. That 20-point gap is likely to widen as agent deployments compound over time.

KPMG notes that AI leaders outpace their peers in deploying agents more deeply within key business functions: IT (75% vs. 64%), operations (64% vs. 55%), and marketing (49% vs. 43%).

The Common Blocker

The survey also highlights what is holding most organizations back. Nearly three in four leaders say they are somewhat or greatly concerned about data security, privacy, and risk. That is the highest concern across all factors tested, and it is keeping many businesses stuck in experimentation and piloting.

Regional attitudes to how humans and AI agents should collaborate also vary considerably. East Asia anticipates AI agents leading projects (42%), Australia favors human-directed AI (34%), and North America leans toward peer-to-peer human-AI collaboration (31%). There is no single playbook, and organizations that try to copy someone else’s approach without adapting it to their context tend to struggle.

The Investment Is Not Going Away

One of the clearest signals from the survey: 74% of global leaders say AI will remain a top investment priority even in the event of a recession. This is no longer discretionary spending. Business leaders are treating AI agents as infrastructure, not experiments.

That is a significant shift from even 12 months ago. And it means the competitive pressure to move from pilot to production is real and growing.

What This Means for Business

The KPMG data confirms something most business leaders already suspect but struggle to act on: the gap is not about access to AI tools. Most organizations have access. The gap is between deploying AI in isolated pockets and actually redesigning how work flows across the business.

Organizations that have crossed that threshold share a few traits. They started with a clear business problem, not a technology wishlist. They got their data in order before expecting agents to do meaningful work. And they designed agent workflows with human oversight built in, not bolted on afterward.

If you are still in the experimentation phase, the survey is a useful benchmark. At the current trajectory, the 11% who are scaling effectively will have a compounding advantage by the time the rest of the market catches up.

The full KPMG Global AI Pulse Q1 2026 report, including regional breakdowns and sector-level analysis, will be available at kpmg.com/aipulse on April 15, 2026.

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