Record investment figures are rewriting the relationship between technology budgets and economic output. The question now is whether enterprises can convert that spending into results.
US enterprise and government technology spending will reach $2.9 trillion in 2026. That is an 8.3% annual growth rate, the highest on record, and it is happening while GDP expansion remains constrained by trade policy shifts and geopolitical pressure. Forrester (News - Alert)'s US Tech Market Forecast 2025 to 2030 puts the longer arc in even sharper relief: by 2030, tech spending is projected to represent 8.9% of the entire US economy.
Demand for everything from cloud infrastructure to interactive avatar development services is driving that shift, and the gap between technology investment and broader economic output keeps widening.
What is driving this acceleration
Three structural forces explain the numbers. The first is AI infrastructure investment. Demand for AI-optimized servers is pushing computer equipment spending up 25% year-over-year in 2026. Software follows at 11.8%, led by expansion in cybersecurity, databases, and AI platforms. Adoption of AI-assisted development tools is surging across enterprise teams. The US produced 40 notable AI models in 2024. China produced 15, Europe three.
The second force is sector concentration. The media and information sector alone is set to capture 43% of total US tech spending growth in 2026, driven by hyperscaler capital expenditure. Financial services, high-tech manufacturing, healthcare, and retail follow as the sectors with the largest potential gains from generative AI adoption. These industries share as a common pressure point the need to move from pilot programs to production deployments at scale.
The third is a reshaping of the labor market. AI-related job postings now account for roughly 20% of US tech roles. CIO staff spending is growing at 5% as firms compete for talent in security, data science, and engineering. Most tech jobs will be impacted by AI in some form, and enterprises are adjusting hiring and reskilling strategies accordingly.
Turning investment into measurable returns
The harder problem is execution. The fact of converting generative AI experiments into clear, measurable returns on investment remains the central challenge for technology leaders. In addition the data center energy consumption and dependence on global chip supply chains. Spending at this scale demands accountability, and that pressure is filtering down to every line of the technology budget.
This is where integrated Extended Reality deployments are gaining ground as a more targeted alternative to broad AI initiatives. Combining AR, VR, and MR with AI-powered interfaces gives enterprises a defined use case and a measurable output. Companies like Imascono, a specialist in XR solutions and AI avatars for corporate environments, are increasingly called on by organizations in banking, healthcare, and retail that need to demonstrate concrete ROI from their technology budgets.
A spending cycle that rewards execution
The 2030 projection reflects long-term structural commitment, not cyclical enthusiasm. US enterprises are funding technology at a rate that consistently outpaces GDP growth, and that gap is widening. For technology buyers, the competitive window is narrowing. Organizations that have already deployed integrated XR and AI solutions are building institutional knowledge and workflow integration that late movers will find difficult to replicate quickly
