AI Infrastructure Spending Jumps to $121 Billion in Q2 2026 as Pricing and CPU-Based AI Demand Broaden Growth; 2026 Forecast Raised to $521 Billion
IDC ·
Executive Answer According to IDC’s Worldwide Quarterly AI Infrastructure Tracker, spending reached $121.4 billion in Q2 2026, up 53% year-over-year and 34% sequentially as deployments paused in the first quarter resumed. The defining shift was a broadening of demand: non-accelerated, CPU-based infrastructure grew 61% year-over-year, faster than accelerated systems (+52%), as agentic AI orchestration, data-pipeline […] The post AI Infrastructure Spending Jumps to $121 Billion in Q2 2026 as Pricing and CPU-Based AI Demand Broaden Growth; 2026 Forecast Raised to $521 Billion appeared first on IDC .
According to IDC’s Worldwide Quarterly AI Infrastructure Tracker, spending reached $121.4 billion in Q2 2026, up 53% year-over-year and 34% sequentially as deployments paused in the first quarter resumed. The defining shift was a broadening of demand: non-accelerated, CPU-based infrastructure grew 61% year-over-year, faster than accelerated systems (+52%), as agentic AI orchestration, data-pipeline workloads, and sharply higher component prices pulled standard platforms into the buildout. IDC raised its full-year 2026 forecast to $521 billion, up from $497 billion last quarter, on higher component pricing, stronger CPU-based demand, and sustained hyperscaler capex.
The Q2 2026 results confirm that AI infrastructure investment has moved well beyond initial proof-of-concept phases into a sustained, multi-year capital commitment cycle, and that demand is broadening beyond accelerated systems while component pricing becomes a primary driver of value. Enterprise technology buyers, cloud service providers, and national governments are making long term decisions about where to build, how much to spend, and which AI workloads to prioritize.
For vendors, this means a prolonged period of elevated demand across accelerated compute, high-performance storage, and supporting network infrastructure, but also a faster-moving mix as CPU-based systems for agentic AI orchestration and data pipelines take a larger share of spend and memory costs lift prices across every configuration. For enterprises, the data signals that AI capacity is becoming a structural cost of doing business at scale, that elevated memory and storage pricing will raise the cost of waiting, and that late movers risk falling behind on both performance and cost efficiency.
IDC now projects the global AI infrastructure market will surpass $1 trillion in 2029, reaching $1.17 trillion, before climbing to $1.33 trillion in 2030 , above last quarter’s $1.08 trillion and $1.21 trillion.
“The defining feature of this quarter is breadth. AI infrastructure demand is extending beyond accelerated systems as agentic AI and data pipelines scale, while rising component prices lift spending across every configuration. Together, these trends point to AI becoming a lasting part of how enterprises build, and they underpin the higher outlook for the year.”
— Madhumitha Sathish, RM, AI and Workloads, Enterprise Infrastructure, IDC
IDC projects AI infrastructure spending will reach $521 billion in 2026, representing approximately 63% year-over-year growth; a further acceleration from the roughly 56 % pace estimated as recently as last quarter, and still one of the largest absolute-dollar expansions ever recorded in a single IT market segment. The forecast implies roughly $309 billion of spending in the second half of 2026, nearly 80% above the same period of 2025. The market is now forecast to surpass $1 trillion in 2029, reaching $1.17 trillion, before climbing to $1.33 trillion in 2030, a five-year compound annual growth rate (CAGR) of approximately 33% from 2025.
What could accelerate this trajectory:
What could constrain growth:
Investors and technology buyers should monitor Q3 2026 capital expenditure guidance from leading hyperscalers and AI platform providers, as these forward signals remain the most reliable leading indicator of near-term infrastructure demand.
Why did AI infrastructure spending rebound so sharply in Q2 2026?
Q1 2026 was held back as a platform transition paused some shipments and data center power constraints left deployed hardware idle. As those pauses began to resolve, Q2 spending rose 34% sequentially to $121.4 billion, up 53% year over year. Higher memory and component pricing amplified the rebound, lifting the value of nearly every configuration. The long-term expansion cycle remains firmly intact, and IDC’s full-year 2026 forecast was revised upward, not downward, this quarter.
Which regions are emerging as new AI infrastructure centers?
Western Europe (+84% year over year) and the Middle East & Africa (+109% year over year, from a small base) posted some of the fastest growth in Q2 2026, driven by government-backed sovereign AI programs, data sovereignty requirements, and hyperscaler expansion; more than 40 countries are now funding national AI infrastructure initiatives. China grew 27.9% year over year to $13.0 billion, while the United States still accounted for 76% of global spend. APeJC also grew 28.5%, supported by national AI strategies and localized cloud service provider expansion.
What risks should buyers and vendors watch in 2026?
Power availability is the single most important operational constraint heading into 2027. Data center commissioning timelines are increasingly driven by utility capacity rather than hardware lead times. In parallel, evolving trade policy, particularly around advanced GPU exports, will continue to reshape competitive dynamics across China, the Middle East, and other emerging markets. Memory pricing is a second pressure point: hyperscalers have secured much of the supply through multiyear agreements, leaving enterprise buyers exposed to elevated prices that IDC expects to persist through at least the second half of 2027.
Is AI infrastructure demand still limited to GPU-based systems, and what’s the outlook going forward?
No. Accelerated systems still account for most spending, reaching $105.8 billion in Q2 2026 (87% of the total, up 52% year over year), but non-accelerated infrastructure grew faster, reaching $15.6 billion (+61% year over year). Agentic AI deployments increasingly rely on CPU-based front-end infrastructure to orchestrate calls to backend models, and enterprises are using standard-rack x86 systems for data-pipeline and other lighter workloads that do not require dedicated GPUs, while inference and training scale-out continue to anchor accelerated demand. Higher component pricing is also lifting the value of these systems. How much of this momentum proves to be volume rather than price will become clearer as memory supply normalizes.
For comprehensive vendor share, forecast data, and taxonomy detail, see: IDC Worldwide Quarterly AI Infrastructure Tracker® . For taxonomy and methodology definitions, see: Worldwide Artificial Intelligence Infrastructure Tracker Taxonomy, 2025 .
Source: IDC Worldwide Quarterly Artificial Intelligence Infrastructure Tracker, Q2 2026. Release date: October 2026. Methodology note: Data derived from IDC’s AI Centric workload-based view of the server and storage markets.
Juan Seminara is Research Director for Worldwide Infrastructure Trackers at IDC, where he leads quantitative and qualitative analysis of IT infrastructure markets with a focus on enterprise servers, storage, and AI infrastructure. He can be reached at jseminara@idc.com .
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