Tech sector pours $1T into AI and sends customers the bill
Global technology spending is being reshaped by an unprecedented AI infrastructure build-out, with the cost increasingly passed on to enterprise customers through higher hardware and software prices. Gartner analyst John-David Lovelock told The Register that tech firms' own technology spending is around $1 trillion and set to grow 34.7 per cent in 2026, describing the AI infrastructure push as the largest infrastructure project in human history, dwarfing projects like the US highway system and the Great Wall of China combined.
Gartner has raised its overall 2026 global tech spending forecast to $6.37 trillion, up 14.2 per cent year-on-year and higher than its earlier estimates of $6.31 trillion in April and $6.15 trillion in February. Growth is uneven: devices are forecast to grow 9.8 per cent (partly due to pricier memory and chips), while services and telecoms grow more slowly at 5.3 and 4.4 per cent respectively; infrastructure-as-a-service is expanding fastest, up 29.3 per cent to $287 billion as firms build datacentre capacity for AI demand. CIOs are reportedly pushing back hard against price rises from vendors, with some success only in IT services, while questions remain over whether such price increases are sustainable or merely defensive moves to protect market share, as cheaper Chinese models and open-source alternatives emerge.
In short
- Tech firms' own spending set to hit $1 trillion, up 34.7% in 2026
- Gartner raises 2026 global tech spend forecast to $6.37 trillion
- Enterprises face rising prices as vendors pass on AI infrastructure costs
Steelman: both sides, in good faith
The strongest fair case each way — we don't pick a winner.
The case for
The technology sector is undertaking infrastructure investments of unprecedented scale, described as dwarfing the US highway system and Great Wall of China combined. These genuine capital costs must be recovered to sustain research and development and remain globally competitive; innovation has historically been funded through price premiums during early adoption phases. The market remains competitive, with customers able to choose from Chinese alternatives, open-source models, and other vendors, providing natural constraints on pricing power.
The case against
Whilst massive infrastructure investments are indeed occurring, companies are using market power to extract profit significantly beyond cost recovery. Cost-of-service arguments are undermined by the fact that CIOs successfully push back only on IT services—not on infrastructure-as-a-service, which grew 29.3%—indicating pricing power is strongest where competition is weakest. Moreover, this infrastructure buildout was a strategic choice by technology firms rather than customer demand, yet customers are forced to absorb costs whilst shareholders capture profits.
Explained simply
Technology companies are spending unprecedented sums on building the computing infrastructure needed to power artificial intelligence systems. This infrastructure push is so vast that analysts have compared it to the largest projects in history, including the entire US highway system. The investment is reshaping how the tech sector spends money.
The costs of this AI build-out are being passed on to customers who buy technology products and services. Prices for computer hardware and software are rising substantially, and companies buying from these vendors have limited options to negotiate lower prices. This affects businesses across virtually every industry that depends on technology.
The key question is whether these price increases will hold or prove unsustainable. Cheaper alternatives are emerging from technology makers in other countries and from open-source projects, which could limit how much vendors can charge before customers look elsewhere. Analysts are divided on whether companies are genuinely passing on necessary costs or using the AI boom as an opportunity to boost profits.