Google Cloud's third annual AI ROI survey, conducted with the National Research Group across 2,403 executives, found that most organizations now report financial returns from AI. A smaller group reports those returns accelerating, and three specific practices separate that group from everyone else.
Eighty-four percent of the 2,403 executives Google Cloud surveyed this year report increasing financial returns from AI initiatives. Twenty-six percent of that group say those returns are accelerating year over year, a cohort Google Cloud calls AI ROI Leaders (Google Cloud, 2026).
The gap between those two numbers is the finding worth sitting with.
What the Survey Found
The ROI Leader Practices
Findings Across the Full Survey
Faster strategic decision-making and increased workforce capacity now rank as the top measurable impacts of AI investment, ahead of foundational productivity gains. Improved customer lifetime value and faster innovation cycles also show up as measurable returns. Respondents named AI-powered analytics, workflow automation, customer experience, and AI infrastructure among the areas of greatest investment potential, out of eight areas identified in the full report.
The survey drew on 2,403 executives polled with the National Research Group, plus roughly 300,000 supporting data points across industry, geography, company size, and adoption stage (Google Cloud, 2026).
What Ownership and Training Look Like in Practice
A finance leader naming the specific agents approved for purchase-order approvals, or a human resources leader rolling out a tool that turns dense benefit manuals into instant answers, are the kind of decisions the survey is describing. Ownership and training show up before the technology does.
The three practices behind accelerating returns are organizational. Ownership, workflow embedding, and training show up before the technology does.
Where the Returns Show Up
Unknowns and Uncertainties
Google says the underlying data was analyzed across four dimensions: industry, geography, company size, and AI adoption stage. The published blog post doesn't break the 84%, 26%, or the three ROI Leader practices out along any of those lines, so it isn't yet possible to tell whether Financial Services or Retail organizations post different numbers than Manufacturing, or whether the ROI Leader gap narrows or widens with company size.
Two of the three ROI Leader practices come with exact percentages: 48% for clear ownership, 38% for training. The workflow-embedding practice does not. Google describes it only as "almost half," with no published number.
The headline returns are self-reported. Executives described their own results in a survey; nobody checked those results against audited financial statements. That's standard for research like this, and worth naming as a limit on how far the numbers travel.
Ninety-seven percent of the executives surveyed plan to increase AI investment next year. Whether that investment lands closer to the 84% group or the 26% group depends on practices the report names but does not yet break down by industry or company size.
Before the next AI budget increase, name who holds decision authority for the next agentic rollout, and check whether training on it is mandatory or optional. Those two answers predict which side of the 84%-to-26% gap your organization lands on more reliably than the size of the check you write.
Parker, Oliver. "How AI ROI Leaders Prioritize Investments for Real Business Outcomes." Google Cloud Blog, 27 July 2026, cloud.google.com.
