The global artificial intelligence market is experiencing growth rates that make even the internet boom look restrained. New data from Gartner, Goldman Sachs, and Menlo Ventures paints a picture of an industry on the verge of becoming the largest capital allocation in human history -- and the spending breakdown reveals where the money is actually going.

“The global artificial intelligence market is experiencing growth rates that make even the internet boom look restrained.”

Worldwide AI Spending: The Numbers That Will Shock You

According to Gartner's latest forecast, worldwide AI spending is projected to reach $2.59 trillion in 2026 -- a 47% year-over-year increase from 2025's already staggering $1.76 trillion. By 2027, that number climbs to $3.49 trillion.

For context, that means AI spending will surpass the entire global gaming industry ($200B), the entire global cybersecurity market ($200B), and is on track to exceed total global IT spending in a few years.

Here's how the trajectory looks:

Goldman Sachs Research corroborates this explosive growth. Their analysis -- which adjusts widely cited hyperscaler capex figures to capture the full picture -- estimates $1 trillion of AI-related investment globally in 2026, including $581 billion in the US alone. Cumulative investment since 2022 will total approximately $1.8 trillion.

The implication is sobering: by 2028, Goldman Sachs projects AI capex will rise from 1.8% of US GDP to 2.8% -- levels consistent with the peak investment impulses observed in prior general-purpose technology buildouts like the railroad boom and the internet.

Who's Eating the Money? The 2025 Spending Breakdown

Not all AI spending is equal. The breakdown reveals a market that's already shifting from infrastructure bets to actual applications:

Infrastructure layer: $18 billion (half of genAI spend) - Foundation model APIs: $12.5B -- the fuel behind every AI application - Model training infrastructure: $4.0B -- powering frontier labs - AI infrastructure: $1.5B -- data orchestration and management

Application layer: $19 billion (more than half of all genAI spend) - This represents 6% of the entire global SaaS market, achieved within just three years of ChatGPT's launch

Menlo Ventures' third annual enterprise report surveyed ~500 US enterprise AI decision-makers and found something remarkable: 76% of AI use cases are now purchased rather than built internally. In 2024, that figure was 53%. Enterprises are buying solutions faster than they're building them.

The conversion rates tell the same story: 47% of AI deals go to production compared to just 25% for traditional SaaS. Once organizations commit to exploring AI, they follow through.

Here's how that spending distributes across categories:

The Enterprise Inflection Year

Gartner calls 2026 "the inflection year." Here's what that means in practice:

Budgets are permanent. In 2023, innovation budgets made up a quarter of LLM spending. That has dropped to just 7%. AI is now a core IT line-item, not a pet project.

Multiple models are the norm. 37% of enterprises now use 5 or more models in production -- up from 29% last year. The days of betting on a single AI vendor are over.

AI adoption is unprecedented. The Stanford AI Index 2026 found that 88% of organizations have adopted AI, and 4 in 5 university students now use generative AI. Generative AI reached 53% population adoption within three years -- faster than the PC or the internet.

The value proposition is real. An estimated $172 billion in annual value reaches US consumers from generative AI tools by early 2026, with the median value per user tripling between 2025 and 2026.

The LLM Provider Power Shift

Perhaps the most consequential shift isn't in spending amounts but in who gets the money. The Menlo report reveals that Anthropic has unseated OpenAI as the enterprise LLM leader:

Anthropic's 40% enterprise share is driven by its dominance in coding (54% of enterprise coding tool spend), powered by Claude Code and Sonnet models. Over the same period, OpenAI lost nearly half its enterprise share.

Together, these three companies account for 88% of enterprise LLM API usage -- a concentration that's both a strength and a risk.

What This Means for Businesses

The data is unambiguous: AI spending will continue to accelerate through 2027 and beyond, with infrastructure spending growing at 45% annually and model spending projected to grow 110% in 2026 alone.

For businesses, the imperative is clear:

  • Get past pilot mode. Innovation-budget AI is dead. AI spending is now part of core operations.
  • Buy, don't just build. 76% of enterprises purchase AI solutions now -- the tooling has matured enough that off-the-shelf beats custom.
  • Diversify model providers. With the Anthropic/OpenAI/Google triopoly capturing 88% of spend, lock-in risk is real.
  • Expect ROI to accelerate. 47% of AI deals go to production vs. 25% for traditional software -- the conversion rate is nearly double.

The AI spending explosion isn't a bubble. It's a structural reallocation of capital toward the defining technology of our generation. The question is no longer if AI will reshape your industry, but whether your organization can move fast enough to capture the value.

---

Sources: Gartner Forecast 2026 (May 2026), Goldman Sachs Research AI Capex Report (2026), Menlo Ventures State of Generative AI in the Enterprise (December 2025), Stanford HAI AI Index 2026 Report, a16z Enterprise AI Survey (2025).