The next leg of global technology spending is being written by artificial intelligence, and the numbers now coming in point to a decisive break from the cautious budgets of the past few years. Instead of trimming costs at the margins, boards are authorizing large, multi‑year bets on AI infrastructure, software and services that will reshape how companies allocate every new dollar of IT spend. The result is a rare moment when macro forecasts, vendor pipelines and enterprise roadmaps are all pointing in the same direction: the AI boom is about to push information technology outlays sharply higher next year.
What is changing is not only the volume of money flowing into IT, but the mix. Spending that once went reflexively to cybersecurity tools or routine hardware refreshes is being re-routed into AI agents, data platforms and cloud capacity that can automate work and open new revenue streams. I see that shift showing up across forecasts for worldwide IT budgets, enterprise software, cloud infrastructure and even public‑sector technology plans, all converging on the same conclusion that AI is now the primary growth engine for technology investment.
AI turns a slow IT cycle into a new growth phase
After several years of uneven tech budgets, the clearest signal that AI is changing the cycle comes from the top‑down view of global spending. Forecasts for Worldwide IT now point to growth of 9.8% in 2026, with total outlays expected to reach $6.08 trillion for the first time. That is not the profile of a mature, saturated market; it is the profile of a sector being pulled forward by a new class of workloads, in this case AI infrastructure and devices that are explicitly identified as the engines that will continue to drive demand for data center systems and end‑user hardware. When I talk to CIOs, they describe AI projects as “non‑discretionary” in a way that routine upgrades simply are not, and the global numbers are starting to reflect that urgency.
The same pattern shows up when I look at the software layer. A separate forecast from late Nov, framed around how Enterprise Software Spend Will Grow, projects a Stunning 15.2% increase Next Year, with the analysis noting that But Most Of That Will Go to AI‑driven applications and price increases tied to those capabilities. In other words, the software boom is not broad‑based; it is being led by AI application software that is expanding faster than traditional SaaS itself. Put together, the hardware and software views tell a consistent story: AI is not a side project inside IT budgets, it is the organizing principle for the next phase of growth.
Budgets are being rewired around AI agents and growth use cases
The shift is not only about how much organizations will spend, but what they expect to get in return. Earlier this year, a detailed spending pulse on technology buyers highlighted that, as artificial intelligence evolves, IT budgets are keeping pace, with companies ratcheting up investment in AI agents and generative tools that can move the needle on revenue rather than just cut costs. Those Key Takeaways describe a world in which CIOs are deliberately shifting money away from maintenance and toward growth investments, especially in sectors like technology, media and telecommunications where AI can be embedded directly into products. I hear that in conversations with executives who are funding AI copilots for software developers, recommendation engines for streaming platforms and automated ad‑buying systems that promise higher yield.
That reallocation is already visible in how specific line items are growing or slowing. A recent look at public‑sector and critical‑infrastructure technology budgets noted that Here, Cybersecurity budgets grew only 4% in 2025 on average, down from 8% in the previous year, even as AI is expanding a $2 trillion to $3 trillion market that was closer to between $2 trillion and $3 trillion in 2015. That contrast captures the new hierarchy inside IT: essential but mature categories like security are still growing, just more slowly, while AI‑related initiatives are treated as the strategic frontier where leaders are willing to spend aggressively to avoid falling behind.
Cloud, chips and devices race to keep up with AI demand
On the supply side, the companies that provide the raw computing power for AI are scrambling to keep up, and that scramble is itself a powerful driver of IT spending. A recent investment outlook noted that All AI cloud providers are reporting supply shortages that are expected to persist well into, if not through, 2026, with All AI hyperscalers planning capital expenditures that could run into the hundreds of billions of dollars by 2028, if not by 2027. When the four largest hyperscalers are simultaneously racing to add data center capacity, specialized accelerators and high‑bandwidth networking, that spending cascades through the entire IT ecosystem, from chipmakers and server vendors to power and cooling suppliers.
The hardware refresh cycle is also being pulled forward on the device side. The same global forecast that pegs IT spending at $6.08 trillion highlights how AI Infrastructure and Devices Will Continue to Drive Demand, particularly for data center systems and AI‑capable endpoints. In practical terms, that means enterprises are not just buying more GPUs; they are also rolling out new generations of laptops, smartphones and edge devices that can run on‑device models or act as rich clients for AI services. I see this in procurement plans that prioritize AI‑ready workstations for engineers, AI‑enabled point‑of‑sale terminals in retail and connected vehicles that rely on real‑time inference for driver assistance. Each of those deployments shows up as incremental IT spend that would not exist without the AI workloads behind them.
From crowdsourced pilots to disciplined AI programs
There is, however, a growing recognition that not all AI spending is equally productive. Early in the generative AI wave, many organizations leaned on Crowdsourcing AI efforts, encouraging employees to experiment with tools in a bottom‑up fashion. That approach produced impressive adoption numbers but, as one forward‑looking analysis of In 2026 makes clear, it seldom produced meaningful business outcomes. The prediction for In 2026 is that more organizations will pivot from scattered pilots to disciplined AI programs, with clear governance, deployment protocols and skilled people in place to turn models into measurable results. I see that as a necessary evolution if the current surge in IT spending is going to translate into durable productivity gains rather than a short‑lived hype cycle.
That same analysis argues that the winners in this next phase will be the companies that treat AI as a core capability, not a side project. Instead of dozens of disconnected proofs of concept, they are building shared data platforms, standardized model pipelines and centralized teams that can support use cases across the enterprise. In budget terms, that means fewer small experiments and more large, multi‑year commitments to platforms and partners. It also means a different mix of vendors, with spending flowing toward providers that can help with integration, risk management and change management, not just model access. As those disciplined programs scale, they will lock in a higher baseline of IT spending that is tied directly to business strategy.
Winners, laggards and what next year means for CIOs
The companies best positioned to benefit from this AI‑driven spending wave are those that already sit at the intersection of data, compute and enterprise workflows. A recent analysis of the current boom described how AI is driving the strongest IT spending growth since the 1990s heyday for information technology sellers, with demand spilling over to cloud platforms like Amazon Web Services, Microsoft Azure and Google Cloud, as well as data specialists such as Snowflake and Databricks and large ecosystem players like Alibaba and others. That perspective, laid out in a late‑Nov look at how Nov AI demand is reshaping vendor fortunes, underscores how concentrated the upside can be when a new computing paradigm takes hold.
For CIOs, the message is both encouraging and sobering. On one hand, the macro environment is finally aligned with their ambitions: boards are prepared to fund AI initiatives, vendors are racing to ship new capabilities and the broader IT budget is set to grow at a pace that would have seemed optimistic only a few years ago. On the other hand, the bar for success is rising. With Enterprise Software Spend Will Grow at 15.2% Next Year and Worldwide IT outlays on track for $6.08 trillion, there will be little patience for AI projects that do not deliver. The leaders I speak with are responding by tightening their portfolio of initiatives, focusing on a handful of high‑impact use cases, such as AI copilots for customer‑service agents, predictive maintenance for industrial equipment and intelligent routing for logistics fleets. In that sense, the AI boom is not just lifting IT spending next year; it is forcing a more strategic, outcome‑driven approach to every technology dollar that gets approved.
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Grant Mercer covers market dynamics, business trends, and the economic forces driving growth across industries. His analysis connects macro movements with real-world implications for investors, entrepreneurs, and professionals. Through his work at The Daily Overview, Grant helps readers understand how markets function and where opportunities may emerge.
