Global spending on information technology is expected to reach $6.37 trillion in 2026, a 14.2% increase over the previous year, according to the latest estimate from Gartner. The growth will be highly concentrated in the infrastructure needed to develop and deploy artificial intelligence: data center systems will grow by 62.5%, and Infrastructure as a Service (IaaS) will advance by 29.3%.
The key points of worldwide tech spending in 20 seconds
- Gartner raises its 2026 tech spending forecast to $6.37 trillion.
- Data center systems will grow 62.5%, reaching $822 billion.
- Spending on IaaS will hit $287 billion, a 29.3% increase.
- Software, devices, and services will continue growing, but at much slower rates.
- Investment is focused on servers for AI, cloud, and computing capacity.
This new outlook improves on earlier estimates from Gartner released earlier this year. In February, the forecast was $6.15 trillion with a 10.8% growth projection. In April, that was revised upwards to $6.31 trillion and 13.5%. The July update adds another $59 billion, setting the annual growth at 14.2%.
This change does not reflect a uniform recovery across the entire tech market. Most of the additional growth stems from segments directly linked to artificial intelligence, especially servers, accelerators, memory, high-speed networks, storage, and cloud services.
Gartner estimates that global tech spending will go from $5.58 trillion in 2025 to $6.37 trillion in 2026. The difference is roughly $792 billion in just one year, partly due to increased demand and partly due to rising hardware prices and the cost of certain components.
Data centers absorb much of the growth
Data center systems will see the largest jump in forecasted growth. Spending will rise from $506 billion in 2025 to $822 billion in 2026, a 62.5% increase.
This category includes servers, storage, and other equipment used to build computational capacity. Growth was already high in 2025, at 51.6%, but Gartner expects an even greater acceleration this year.
The main driver is the expansion of infrastructure for artificial intelligence. Major cloud providers are building data centers and expanding existing facilities to host clusters with thousands of accelerators. Simultaneously, companies, governments, and specialized providers are creating private platforms or leasing external capacity to train models and run inferences.
John-David Lovelock, Gartner’s VP Analyst, describes this computing capacity build-out as “the biggest infrastructure project ever attempted by humanity.” This phrase reflects the scale of the planned investment, not a technical measurement to directly compare with projects like power grids, highways, or other large infrastructures.
Spending isn’t limited to GPUs or graphics processing units. AI systems require high-bandwidth memory, CPUs, Ethernet or InfiniBand networks, storage, advanced cooling, and high electrical capacity.
Physical construction of data centers also influences timing. Demand for land, transformers, generators, cooling systems, and power connections is delaying many projects. Energy availability has become a limiting factor in deploying new capacity in some markets.
Increased expenditure does not mean the number of servers will grow proportionally. AI-focused systems tend to be far more expensive than traditional enterprise servers, so a significant portion of the growth results from more costly configurations.
Infrastructure as a Service (IaaS) will grow nearly 30%
IaaS will be the second-fastest-growing category. Gartner forecasts that spending will reach $287 billion, up from $222 billion in 2025.
The projected increase is 29.3%, higher than last year’s 25.3%. This category includes on-demand compute resources, storage, and networking services from cloud providers.
AI drives this model because many organizations cannot bear the upfront investment, timelines, or complexity of building their own infrastructure. Instead, they rent GPU capacity and related services from public cloud providers, regional operators, and specialized vendors called neoclouds.
Hyperscalers like Amazon Web Services, Microsoft Azure, Google Cloud, and Oracle Cloud continue to dominate this market. However, increasing demand is also creating opportunities for specialized providers of GPUs, sovereign clouds, and infrastructure services tailored to regulated sectors.
This growth in IaaS doesn’t mean all companies are migrating entirely to public clouds. Many maintain hybrid architectures combining in-house infrastructure, private clouds, managed services, and on-demand resources.
Data sovereignty, cost control, and capacity availability increasingly influence these decisions. A business might use public cloud for temporary AI training projects but retain inference or sensitive data on private infrastructure.
Software is growing, but far behind AI hardware
Software spending is expected to reach around $1.47 trillion, with a 15.5% growth rate. Although high, this increase is far below the projected growth for data center systems.
Companies are allocating more budget to applications with assistants, automation, and generative functions. Spending on data platforms, cybersecurity, observability, software development, and AI governance is also rising.
Gartner warns that this growth will not benefit all vendors equally. The extra budget is focused on products directly linked to AI projects, while other tools compete for an increasingly constrained share of corporate spending.
Device spending, including computers, smartphones, and other user equipment, will grow 9.8%, reaching $868 billion. Upgrading devices to run some AI functions locally will support this growth, but it will remain much more moderate than data center expansion.
IT services will reach $1.57 trillion, up 5.3%, while communications services will total $1.35 trillion, a 4.4% increase.
Together, these two categories account for nearly half the market but have the slowest growth rates. This indicates that the overall expansion for 2026 is heavily driven by investments in AI capacity.
More spending doesn’t mean more margin for all companies
The increase in tech budgets coexists with growing pressure on IT departments.
Gartner points to several cost-driving factors: inflation, supply shortages, higher prices for hardware and memory, AI project funding, and frequent shifts in business priorities.
Memory is one of the most tense components. Manufacturers are channeling more high-margin capacity into products for AI accelerators, especially HBM memory. This can limit supply for other technologies and increase server, storage, and device costs.
There’s also internal competition for budget. Funds allocated to assistants, models, agents, or data centers don’t always add to previous spending — often leading to postponements, vendor consolidations, or cuts elsewhere.
Gartner’s phrase that “the rising tide doesn’t lift all boats” summarizes this situation. Infrastructure vendors for AI may see significant growth, while other tech companies may struggle to maintain sales.
For clients, the challenge will be to differentiate between necessary spending to support real workloads and capacity contracted based on forecasts that may not materialize. Investing too early risks underutilization; waiting too long can hinder access to GPU, energy, or data center space.
Forecasts are still subject to change
Gartner’s figures are estimates based on market analysis, not final year-end results. The consultancy updates its forecasts periodically by analyzing sales data from over a thousand providers and adjusting for changes in prices, demand, and economic conditions.
Throughout 2026, revisions reveal how quickly the market is evolving. In October 2025, Gartner expected that annual spending would slightly surpass $6 trillion, with a 9.8% growth. Nine months later, the forecast is nearly $290 billion higher.
Much of this difference is due to demand for AI infrastructure. Still, the ultimate outcome relies on data center deployment capabilities, energy supply, and maintaining chip, memory, and networking component flows.
It also depends on how quickly companies turn AI prototypes into production applications. The industry is building enormous capacity in anticipation of rising model and agent use. If growth slows, some investments might take longer to become profitable.
Frequently Asked Questions
How much will be spent on technology in 2026?
Gartner forecasts global tech spending will reach $6.37 trillion, a 14.2% increase over 2025.
Which category will see the biggest growth?
Data center systems will lead growth, with an estimated 62.5% increase, reaching $822 billion.
What will be the growth in IaaS cloud services?
Spending on Infrastructure as a Service is expected to hit $287 billion, up 29.3% from the previous year.
Why is tech spending increasing so much?
The growth is concentrated in servers for AI, accelerators, memory, networks, data centers, cloud services, and AI-enabled software.
via: gartner
