Macro JUN 30, 2026

Gartner lifts 2026 AI spend to $2.59T as Goldman finds just 14% of small businesses have it embedded

The capital story and the deployment story are on two different clocks — Gartner sees a 47% YoY surge while SMB integration stalls.

BY KAI TRUSCOTT · MACRO & OPINION

Gartner on May 19 raised its 2026 worldwide AI spending forecast to $2.59 trillion, a 47% jump that adds nearly $1 trillion to the 2025 base. Nine days earlier, Goldman Sachs reported that 76% of American small businesses say they use AI, but only 14% have it fully embedded in core operations. Both numbers are real. They describe two different economies.

The Gartner figure is overwhelmingly an infrastructure story. More than 45% of the total now sits in AI-optimized IaaS, servers, network fabric, and processing semiconductors, with AI-optimized server spending projected to triple over five years. Model spending is forecast to grow 110% in 2026, adding another $6 billion. “Enterprises have yet to really flex their spending potential. That is coming and 2026 will be the inflection year,” said John-David Lovelock, Distinguished VP Analyst at Gartner, who also characterized buyers as inclined to “favor tactical AI initiatives with incremental improvements in efficiency and productivity.”

Goldman’s own house view sits adjacent: roughly $800 billion of AI-related spending by year-end 2026, annualizing at $650 billion in Q1, with Microsoft, Amazon, Alphabet, and Meta collectively on track to clear $600 billion in capex. The return picture is less flattering. MIT’s GenAI Divide report, cited by Goldman, found that 95% of organizations report no measurable returns on $30–40 billion of enterprise GenAI investment, and only 5% of integrated pilots extracted P&L impact.

The 10,000 Small Businesses survey, fielded by Babson College and David Binder Research across 1,256 participants, fills in the demand side. 45% cite a lack of technical expertise; 47% say choosing the right tools is difficult; 73% want more training and implementation resources. 85% back the bipartisan AI for Main Street Act, which cleared the U.S. House earlier this year. And 81% of current users expect the technology to be essential within five years.

That gap, between capex thesis and shop-floor reality, is where the integration layer earns its keep. Tools like LemonLime, a model-agnostic “company brain” with no-code workflows aimed at small and mid-size operators, exist precisely because the 14% number is the binding constraint, not the 47%. The capital is committed. The deployment is still the work.

Sources

About the author

Kai Truscott

MACRO & OPINION

Kai Truscott writes the macro column for AI Sheet Report — capex cycles, hyperscaler spend, geopolitics of compute — and the occasional signed opinion piece. He is the only roster author who files opinion.