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The $2 trillion headline referred to a Gartner forecast for 2026 published in September 2025. Gartner’s updated forecast, published September 16, 2026, puts worldwide AI spending that year at $2.670 trillion. That is still an estimate—not a tally of money already spent—and AI infrastructure accounts for the largest share.
Why the $2 trillion headline changed
Gartner forecast $2.023 trillion in worldwide AI spending for 2026 in its September 17, 2025 release. A year later, Gartner raised its 2026 forecast to $2.670 trillion. The two figures come from successive forecast editions, not from a comparison between an estimate and audited actual spending. Gartner’s newer release also changed some category boundaries, so the difference should not be read as a precise measure of newly added spending.
The updated total is Gartner’s estimate of worldwide spending across its AI categories. Its public release does not provide the full forecasting methodology, and the category list should not be treated as an independently audited ledger of every dollar associated with AI. Gartner’s September 2026 forecast supplies the current estimate and breakdown.
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In Gartner’s September 2026 forecast, infrastructure is by far the largest listed category. Services and software follow. The values below are Gartner’s worldwide forecasts for 2026, converted from millions to billions of U.S. dollars.
| Gartner category | 2026 forecast |
|---|---|
| AI infrastructure | $1,484.397 billion |
| AI services | $576.481 billion |
| AI software | $461.637 billion |
| AI cybersecurity | $51.347 billion |
| AI agents and assistants | $29.219 billion |
| Generative AI models | $28.266 billion |
| AI platforms for data science and machine learning | $26.445 billion |
| AI application development platforms | $9.541 billion |
| AI data | $3.126 billion |
These are Gartner’s categories and forecast values, not necessarily a complete or non-overlapping breakdown of every AI-related purchase. Gartner says it separated cross-functional agents and assistants from AI software and added consumer agents and assistants in the newer release. That taxonomy change is one reason not to compare category totals across editions as if their definitions stayed fixed.
Why infrastructure leads
Gartner says demand for AI infrastructure remains strong amid anticipated future workloads. Its September 2026 release identifies hyperscalers and service providers buying AI-optimized servers as the largest single area of spending. John-David Lovelock, Distinguished VP Analyst at Gartner, said: “The capacity growth from hyperscalers and service providers purchasing AI-optimized servers will continue to be the largest single area of spending.”
The forecast also reflects AI features moving into software businesses already sell. Gartner says vendors are embedding agentic AI into existing products, with enterprises pursuing operational efficiency, workflow automation, customer engagement, and decision support. Those are Gartner’s stated explanations for the forecast, not independently verified outcomes for every organization.
A narrower Gartner measure illustrates how infrastructure demand can extend beyond training models. Its August 2026 forecast puts spending on AI-optimized infrastructure as a service (IaaS) at $42.276 billion in 2026, including $23.3 billion for inference and $19 billion for training. This IaaS estimate is only one slice of infrastructure spending; it should not be substituted for, or added mechanically to, the global total. Gartner’s AI-optimized IaaS forecast gives that narrower scope.
What the earlier forecast said about devices and hardware
The September 2025 forecast offered a more granular view of hardware and consumer devices. The figures below are Gartner’s estimates for 2026 from that earlier release—not revised 2026 values from the September 2026 forecast.
| Category in Gartner’s September 2025 release | 2025 forecast | 2026 forecast |
|---|---|---|
| AI-optimized servers | $267.534 billion | $329.528 billion |
| AI processing semiconductors | $209.192 billion | $267.934 billion |
| AI PCs | $90.432 billion | $144.413 billion |
| GenAI smartphones | $298.189 billion | $393.297 billion |
These categories help show why “AI spending” reaches beyond cloud data centers: Gartner’s earlier forecast included devices as well as the components and servers used to run AI workloads. Because those numbers belong to the 2025 edition and its category definitions, they should not be combined with the later release’s top-level categories. Gartner’s September 2025 forecast contains the original estimates and its explanation of the expected infrastructure expansion.
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How to read the narrower AI market forecasts
Gartner also publishes forecasts for specific markets that are much smaller than the global total. These can provide context, but their scopes may overlap with broader categories, so they are not extra amounts to add on top of the $2.670 trillion forecast.
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- AI models and platforms: Gartner forecast $64.252 billion in end-user spending for 2026 in a July 2026 release, including $23.356 billion for foundation generative AI models and $4.910 billion for domain-specific and specialized generative models. See Gartner’s models and platforms forecast.
- AI-optimized IaaS: Gartner forecast $42.276 billion for 2026 in an August 2026 release. This measures a particular cloud infrastructure market, not all AI infrastructure. See Gartner’s IaaS forecast.
What the forecast can—and cannot—tell you
Gartner’s updated estimate indicates a vast market, with infrastructure dominating its 2026 category breakdown and services and software also accounting for substantial forecasts. It does not establish how much organizations ultimately spent, prove that the forecast’s expected benefits materialized, or identify which individual products drove the totals. Treat the figures as Gartner’s dated forecasts, and check the release and category definition before comparing one number with another.
The September 18, 2025 ITPro article used the earlier $2 trillion headline; its date clarifies why that figure is now historical. Read the original ITPro article.
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