"AI Investment by U.S. Companies to Reach $1.75 Trillion by 2035, a Sevenfold Increase" - Oxford Economics

The total artificial intelligence (AI) investment spending by all U.S. companies was approximately $230 billion in 2025, and it is projected to reach $1.75 trillion by 2035, ten years later. The proportion of AI-related investment in overall technology spending by U.S. companies is also expected to increase from about 7% to 22% over the same period.

As AI adoption spreads and per-company spending increases, the share of AI in corporate technology budgets is expected to reach 25% to 35% across most industries by the mid-2030s. By industry, professional services and IT & programming, which are early adopters of AI, are projected to increase their share from about 10% in 2025 to around 45% in 2035. Construction, on the other hand, is expected to rise from a relatively low 3% to 17% over the same period.

The UK think tank Oxford Economics stated this in a report titled "AI is reshaping the composition of enterprise tech spending," released on the 27th (local time).

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The following is a summary of the main points.

AI is the primary driver behind the growth of corporate technology budgets, which are expected to steadily increase through 2035. AI is no longer a supplementary line item, but rather the core factor driving increases in technology budgets. Its contribution will grow significantly over time. In 2025, AI-related investment amounts to about $230 billion, accounting for roughly 7% of total enterprise tech spending in the U.S. By 2035, this is projected to exceed $1.75 trillion, representing about 22% of the total. As companies move from experimentation to actual production deployment, the annual growth rate is expected to remain above 30% through 2028.

This shift is also reflected in how spending is distributed across different technologies. AI expenditures are concentrated in service-oriented categories such as enterprise software, IT services, and internet·cloud services. These areas account for the bulk of direct AI-related spending by companies. IT services alone, which include not only customized systems and software provision but also data center management, saw about $85 billion in AI-related spending in 2025. This demonstrates that integration and consulting currently play a key role in the AI adoption phase. Instead of building proprietary computing infrastructure or custom AI systems, companies are primarily spending on consulting, custom software, and cloud services to leverage AI.

Hardware also plays a substantial role in U.S. AI spending, albeit through a different channel. Much of what companies consume as cloud AI services ultimately relies on physical infrastructure such as GPUs, AI-optimized servers, and high-performance networking. This infrastructure is purchased at scale by a small number of U.S.-based hyperscalers. Because these purchases are accounted for based on the buyer's location, this makes "devices" one of the largest AI spending categories in the U.S. outlook, even though the computing may be consumed worldwide. This is especially pronounced due to the concentration of major cloud providers’ headquarters in the U.S.

Industry segmentation provides an even clearer picture of where these investments are taking hold. Financial and insurance services stand out as the largest contributors to AI spending in absolute terms, followed by IT·programming and professional services. These industries not only have large existing technology budgets but also strong use cases for AI, ranging from process automation to advanced analytics and customer engagement. Other service-oriented sectors, such as media and telecommunications, also stand out, whereas industrial sectors and heavy manufacturing play a relatively smaller role.

When looking at the intensity of AI adoption as a share of total technology budgets, the financial, technology provider, and professional services sectors show the highest AI concentration. These sectors have large technology budgets and, by the nature of their work, are well-suited to automation and AI-assisted decision-making. At the same time, there are significant differences by industry. Some smaller sectors, such as private education and healthcare, have relatively small total tech budgets but a comparatively high share allocated to AI, reflecting the relatively rapid pace of AI adoption in these fields. In contrast, asset-intensive sectors such as construction and transportation are lagging behind.

AI adoption is accelerating, though not uniformly. The pace and pattern of this spread are determined by differences in digital maturity, cost structure, and the extent to which companies can integrate AI into their operations. The outlook by industry through 2035 shows how AI concentration is expected to change. In nearly every industry, the AI share is projected to increase significantly. However, even as AI adoption broadens, the gap in absolute AI spending between the most and least AI-intensive sectors is expected to widen further. This suggests that both the nature of the work done in each sector and the existing level of digitalization will continue to shape where AI investments are concentrated.

As AI adoption spreads and per-company spending increases, the share of AI in corporate technology budgets is expected to approach one-third by the mid-2030s. After that, as the technology matures, this share is expected to stabilize.

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