Four out of five dollars spent on artificial intelligence now sit outside traditional IT budgets, according to a Wednesday report from the Boston Consulting Group that surveyed more than 1,300 CIOs and tech leaders. The research captures how AI has evolved from a technical project into a company-wide transformation, with investment spreading across departments rather than remaining concentrated in technology teams. AI now ranks among the largest enterprise investments, the report finds.

Corporate spending on AI has nearly doubled in less than a year, climbing from 1.7% of revenue in late 2025 to 3.3% today, the BCG research shows. A rising portion of that investment flows to non-technical deployment, funding areas such as AI talent recruitment and governance frameworks. Nearly half of technology leaders currently see measurable returns from their AI initiatives, while 61% worry they could lose their jobs if they fail to guide their organizations through the AI shift, citing a Writer survey released in April. Agentic systems—which can restructure entire workflows rather than assist with isolated tasks—are projected to deliver two-fifths of all AI value by 2030, and 42% of companies expect to grant agents autonomy by that year.

Vlad Lukic, who leads BCG's tech and digital advantage practice globally, told CIO Dive that the distributed nature of AI investment reflects its role as business transformation. "What CIOs do need, though, is visibility and a common management model across that spend," he said. CIOs should function as chief integration officers, Lukic explained, setting architecture and controls while helping businesses scale successful use cases and connecting spending back to measurable value instead of managing fragmented projects. The report notes that autonomy alone doesn't generate returns—companies extracting the most value from agents have built structured operating models, data systems, ownership frameworks, and controls around their AI deployments.

BCG recommends that companies redesigning operations around AI allocate 10% of effort to algorithms, 20% to technology and data infrastructure, and the remaining 70% to people, organization, and processes. "The bulk of the work is in redesigning processes, changing roles and ways of working, building new skills, and managing the organizational change required to make AI part of day-to-day operations," Lukic said. A robust technology stack won't deliver returns in static workflows or without employee adoption, the report cautions. As AI spending continues to expand beyond technology departments, CIOs will need comprehensive visibility into where the technology is deployed, how it ties to business outcomes, and what total costs look like across the organization. The shift from experimentation to scaled deployment will separate companies that achieve sustained value from those stuck with disconnected pilot projects. Organizations that treat AI as primarily a technology challenge rather than an operational overhaul risk burning capital without reshaping the workflows where returns actually materialize.