AI Infrastructure & Platform Spending: The 2026 Growth Engine for Established Vendors

The growth story for enterprise software in 2026 is less about new money and more about a massive reallocation of existing funds. The scale is staggering: enterprise leaders expect an average of ~75% growth in LLM budgets over the next year. This isn't a marginal increase; it's a fundamental shift where AI budgets have graduated from "innovation fund" line items to core operating expenses. The mechanism is clear and brutal. As one CIO noted, the amount spent on AI in 2023 is now spent in a week. To fund this surge, CIOs are cutting low-ROI software, meaning new budget growth is modest.

The math reveals the tight squeeze. While overall software spending is projected to grow 15.2% in 2026, a significant portion is consumed by price increases. CIOs are setting aside roughly 9% of the IT budget for price increases on existing services. That leaves about 6% for actual new spending. Almost all of that remaining budget is flowing to AI. This creates a winner-take-most dynamic. Established vendors that can capture this reallocated budget will see explosive growth, while those that cannot will be left behind.

The shift is also a strategic pivot from "build" to "buy." After a wave of failed internal POCs, enterprises are now focused on commercial off-the-shelf solutions for predictable value. This favors established platforms with deep integration and proven ROI. The bottom line is that AI spending is becoming the only growth budget that matters. For established vendors, the opportunity is to be the vendor that gets stolen from, not the one doing the stealing.

The AI Infrastructure Buildout: A $230B+ Market

The real engine of AI spending isn't just software-it's the physical hardware that powers it. The market for AI infrastructure software alone is projected to balloon from nearly $60 billion last year to nearly $230 billion in 2026. This isn't a niche expansion; it's a fundamental retooling of global computing capacity. The driver is clear: AI hyperscalers are planning to spend more on data centers in 2026 than they ever have before. This record capital expenditure surge is the direct fuel for the entire AI stack.

For established hardware leaders, this is a massive, scalable opportunity. The key beneficiaries are the companies with dominant technology and full-stack solutions. Nvidia, Broadcom, and AMD are positioned to capture this spend. Nvidia's lead is built on superior GPU technology and a complete software stack, a combination that has made it the indispensable partner for the AI buildout. Even as it faces supply constraints, its Rubin platform aims to maintain that dominance. AMD is gaining traction as a viable alternative, with its software ecosystem seeing explosive growth, while Broadcom is carving out a different path by designing custom chips for hyperscalers. The bottom line is that the hardware market is a winner-take-most arena, and these established players are the ones with the scale and technology to win.

Platform Scalability: The Buy, Don't Build Advantage

The enterprise shift from building custom AI to buying commercial software is creating a powerful, scalable growth path for established vendors. This isn't just about selling more licenses; it's about embedding AI into the core of business operations, turning existing platforms into multi-billion dollar engines. The total addressable market for these platforms is expanding dramatically. For example, the category of AI application software-encompassing CRM, ERP, and workforce productivity platforms-is projected to more than triple to almost $270 billion by 2026. This is the new TAM for companies like ServiceNow, which is moving beyond IT service management into AI-powered customer service, effectively expanding its addressable market to $275 billion by 2026.

The catalysts for this acceleration are clear. Enterprises are moving past failed internal proof-of-concepts and are now focused on upgrading legacy systems. As AI becomes embedded in everyday operations, the key drivers are companies with strong recurring revenue models and those actively replacing outdated infrastructure. This creates a predictable, high-margin growth stream. According to analysts, software revenue growth could reaccelerate this year as enterprises resume spending after the AI-driven distractions of the past few years. The mechanism is straightforward: upgrade cycles and replacement of legacy systems are the primary catalysts tied to AI adoption.

This strategic pivot from "build" to "buy" is the critical inflection point. After a wave of failed internal POCs, CIOs are opting for commercial off-the-shelf solutions for more predictable implementation and business value. This favors established vendors with deep integration, proven ROI, and full-stack capabilities over niche point solutions. The result is a winner-take-most dynamic where market share capture accelerates. For established platforms, the opportunity is to be the vendor that gets stolen from, not the one doing the stealing. By embedding AI into their core offerings, these companies are scaling their growth by capturing a larger share of the AI budget that is now the only growth budget that matters.

Financial Impact and Valuation Catalysts

The budget shift translates directly into a powerful revenue growth engine for established software providers. The mechanism is durable and predictable: as AI becomes embedded in everyday operations, it drives renewals, upgrades, and the replacement of legacy systems. This isn't a one-time purchase; it's a continuous cycle that supports recurring revenue models. As Gil Luria of D.A. Davidson notes, the opportunity lies in companies that benefit from this embedded adoption, where software revenue growth could reaccelerate this year. For vendors with high-margin SaaS models, this creates a scalable path to expanding their total addressable market, as seen with ServiceNow's move into AI-powered customer service.

Yet this fundamental growth trajectory faces a current market headwind. Investor sentiment has turned negative, with a clear rotation out of Big Tech names. Microsoft's stock, for instance, touched a six-month low earlier this week, a sign of persistent technical weakness. The market's focus on AI's disruptive potential has overshadowed the steady, cash-generating growth of established software, leading to depressed valuations for many players.

The potential catalyst for a valuation reset is a shift in investor focus back to cash flow and sustainable growth. As the AI hype cycle settles, the market may begin to appreciate that AI is enhancing, not replacing, core enterprise software. This could improve valuations for companies demonstrating clear AI integration and the ability to command higher renewal prices. The bottom line is that while near-term sentiment is negative, the underlying growth story for established vendors is strong. They are positioned to capture a larger share of the AI budget that is now the only growth budget that matters.

Catalysts, Risks, and What to Watch

The strong growth thesis for established software vendors hinges on a few near-term events. The primary catalyst is a visible reacceleration in quarterly revenue growth. As AI spending materializes, we should see software companies report accelerating top-line results, confirming that the reallocated budget is flowing into their coffers. This is the first tangible proof that the "buy, don't build" shift is translating into sales.

The key metric to monitor is the pace of AI budget reallocation versus new budget creation. The current setup is tight: roughly 9% of the IT budget is set aside for price increases, leaving a narrow band for new spending. If the remaining budget growth slows, it would signal that the market is approaching saturation. The evidence suggests the AI budget is the only growth budget that matters, but its size is finite. A slowdown would challenge the scalability narrative and force vendors to compete harder for a shrinking pool of new dollars.

The primary risk is execution. CIOs are no longer just buying technology; they are being called to justify it. As one executive notes, CIOs will be tasked with creating enterprise AI value playbooks, featuring expanded ROI models. This creates a high bar for vendors. They must deliver measurable value-clear efficiency gains, growth acceleration, or innovation-to get renewed. The era of paying for potential is ending; the era of paying for proven impact has begun.

The bottom line is that while the structural thesis is robust, success depends entirely on vendors delivering. The market will reward those who can demonstrate their software is the essential, high-return platform that enables the AI transformation, not just a cost center. Watch for revenue acceleration, monitor the budget math, and listen for CIOs talking about ROI. These are the signals that will confirm whether the growth engine is truly firing.