Enterprises would account for $1.8 trillion of that total, followed by consumers at $366 billion, hyperscalers’ internal use at $204 billion, and emerging technologies such as physical AI at $200 billion. The estimates represent global spending, excluding China, and reflect infrastructure costs concentrated mainly in the U.S., where most new capacity is being built.

The $1.8 trillion is a measure of what the AI ecosystem would need from enterprises, rather than a forecast of actual spending.

In one illustrative scenario, BCG estimates that companies could contribute that amount by reallocating $857 billion from existing technology budgets and adding $937 billion in new spending. That would put enterprise tech budgets roughly 13% above International Data Corporation’s IT spending forecast, with AI’s share of those budgets rising from 5% today to 25% in 2030.

The scenario underscores how much the AI industry’s growth depends on corporate spending. For CFOs seeking additional AI investment, that means presenting boards with evidence of productivity gains, cost reductions, new revenue or competitive advantage, said Clark O’Niell, BCG’s global lead for AI, infrastructure and cyber. Some strategic benefits, however, may be difficult to capture in traditional ROI calculations.

“The question isn’t just whether AI delivers an immediate financial return,” he said. “It’s also what the cost of falling behind could be.”

That argument deserves scrutiny, too. Fear of falling behind can be a legitimate strategic consideration, but it shouldn’t become a substitute for a business case.

BCG considers the AI build-out as more resilient than past infrastructure booms, partly because hyperscalers have financed much of their investment through cash flow rather than debt. But the ability to finance infrastructure doesn’t guarantee that it will generate adequate returns.

O’Niell identifies two indicators worth watching. The first is how infrastructure investment is financed, with a sustained shift toward debt signaling greater risk. The second is whether deployed compute generates sufficient revenue. As frontier labs enter public markets, their disclosures could reveal whether revenue is keeping pace with compute costs.

The economics leave limited room for disappointment.

BCG assumes AI chips have an average five-year lifespan and estimates that each gigawatt of capacity coming online in 2026 must generate about $15 billion in revenue to cover its costs. Weaker-than-expected demand could trigger price wars and losses for model providers and data-center operators.

For corporate buyers, those pressures have a practical implication. O’Niell advises most to avoid long-term price-per-token commitments as AI prices continue to fall. Contract flexibility could help CFOs capture future cost reductions.

The $2.6 trillion is achievable, he said, “but it’s not guaranteed.” And even if enterprises provide the spending, the question remains whether they will capture enough of the economic value to justify it.

Sheryl Estrada
Sheryl.Estrada@fortune.com

Leaderboard

Tom Inman was appointed CFO of Ditto, a software platform. Inman brings more than 25 years of experience in finance, venture capital and strategic operations. His appointment comes as Ditto accelerates its expansion across commercial and defense markets. Inman joins Ditto from Performance Drone Works, where he served in senior finance leadership roles. Previously, he worked at Slingshot Aerospace, where he served as VP of finance. Earlier in his career, he spent 18 years in venture capital and private investment management, serving as managing director of Limestone Capital Advisors, and a principal at Gefinor Ventures.

Roger Smith, CFO of Ur-Energy Inc. (NYSE American: URG), an ISR uranium producer, will retire from the company effective Dec. 1, after a 45-year career in mining industry finance and accounting. Jade Walle, currently VP of finance, has been promoted to CFO, upon Smith’s retirement. Walle joined Ur-Energy in September 2025. Most recently, he was an audit partner with PwC, having begun his career there in 1996. His technical background includes service in PwC’s Global Capital Markets Group in London. 

Big Deal

Americans are open to AI, but they want a person to make the final call. In a Pew Research Center survey of 3,488 U.S. adults, most respondents said they were comfortable with AI handling routine health care tasks like translating for patients or scheduling appointments, most often with a human doing a final review.

Support drops off sharply as the stakes rise. Only 5% are open to AI deciding an insurance claim on its own, and 46% don’t want AI involved in those decisions at all. Trust is also thin: 58% have little or no confidence that health insurers will use AI in patients’ best interests; half say the same of AI companies, and 51% expect AI to make the security of personal health information worse.

Views of AI’s effect on health care costs are more closely divided: 26% say AI will make costs worse, 19% say it will make them better, and 32% aren’t sure. Still, Americans see benefits in some areas.

More say AI will improve access to health care services than say it will worsen it (31% vs. 20%).

Going deeper

Wall Street is bracing for more policy turbulence after the midterms. My Fortune colleague Eleanor Pringle reports that analysts expect President Trump to double down on tariffs, possibly take a more aggressive stance on Iran, and face a Dec. 11 government funding deadline. Read more here. 

Overheard