Four converging pressures are reshaping the economics of infrastructure ownership. Understanding their full impact can change how you decide what still belongs in-house—and what doesn’t.
One of the more underreported consequences of the artificial intelligence (AI) boom has been its impact on conventional enterprise infrastructure.
For years, IT executives could rely on a relatively predictable rhythm of hardware purchases, refresh cycles, and procurement lead times. On-premises infrastructure was never effortless to manage, but its patterns were, at the very least, well-established. Even the “hidden costs” that shaped on-prem’s total cost of ownership (TCO)—stuff like power, cooling, staffing, licensing, security, and recovery—though fragmented and easily overlooked, were grounded in familiar assumptions.
That is, of course, until recently.
McKinsey is calling the race to scale AI “one of the largest infrastructure build-outs in modern history.” As a result, hardware costs have risen precipitously in recent years, even for companies without an ambitious AI initiative on their roadmap. A routine refresh budgeted around familiar prices and delivery windows may now cost substantially more, take longer to arrive, or both. For many IT leaders, the resulting sticker shock is enough to disrupt upcoming refresh budgets and schedules before an order is even placed.
Higher acquisition costs and muddled procurement timelines are but the vanguard for a much broader, much more complex market shift. For many enterprises, VMware licensing and portfolio changes have recast the economics of systems already in place, while the pressure to move AI initiatives from pilot to production is introducing requirements that simply did not exist when the hardware was purchased. Meanwhile, cyber threats are continuing to evolve in sophistication, simultaneously raising the already high standards—and stakes—for security and recovery.
As the economics of infrastructure ownership continue to shift, business leaders and IT decision-makers must now be ready to make long-term choices amid conditions they can neither predict, control, nor afford to wait out. 11:11 Systems calls this convergence “The Great Infrastructure Reset:” a perfect storm of interconnected market pressures making infrastructure decisions more expensive, interdependent, and difficult to forecast.
Rising infrastructure costs and capacity constraints
McKinsey estimates global data-center spending could reach $7 trillion by 2030. AI infrastructure projects are consuming more of the components enterprises rely on for routine refreshes. Hewlett Packard Enterprise (HPE) CEO Antonio Neri says DRAM and NAND memory now account for more than half the bill of materials in a traditional server, with elevated prices expected well into 2027.
Even companies with no AI hardware on the roadmap may pay more for ordinary servers or storage. Buying early brings spending forward; waiting can leave aging systems on a supplier-driven schedule. Procurement timing now carries a cost of its own.
VMware licensing and platform changes
Hardware retains value only while the software supporting its workloads remains viable. Broadcom’s shift toward subscription licensing and a consolidated VMware portfolio has changed the assumptions under which many environments were purchased. Perpetual licenses can keep operating after support expires, but technical support and most updates require active coverage.
Renewal can raise recurring costs or require a broader bundle. Migration may keep old and new environments running in parallel. Either path pulls infrastructure and recovery work forward, changing TCO even when the hardware does not.
Accelerating AI adoption
Gartner forecasts worldwide AI spending will reach $2.59 trillion in 2026. Infrastructure represents more than 45% of the market, revealing where supply and engineering capacity are moving.
But a pilot only really needs to show the model works. Production, on the other hand, must fit the controls surrounding critical systems. Shared infrastructure often sits beyond the innovation budget, so costs surface when pilots multiply and compete with existing workloads.
Evolving cyber threats and resilience requirements
IBM’s 2026 Cost of a Data Breach Report places the global average at $4.99 million. Meanwhile, AI-enabled malicious breaches averaged $6 million. A destructive attack can compromise production systems and the mechanisms expected to restore them. Credible recovery therefore requires an isolated, independently managed environment and a tested path back to service, adding a separate cost to TCO.
Case Study: How Marketron changed what it needed to own
Marketron, a SaaS provider serving more than 7,000 media organizations, faced approximately $300,000 in capital spending every three to four years for hardware refreshes. Remote data centers added a separate operating burden.
After finding the pricing and architecture of major hyperscale clouds poorly suited to its requirements, Marketron moved the workloads to 11:11 Cloud. Moving them ended the recurring hardware maintenance cycle and gave its IT team a more stable platform for improving application availability and performance.
Marketron did not adopt cloud as a blanket replacement for on-premises infrastructure. Instead, the company transferred hardware lifecycle and facility operations to a provider while retaining responsibility for its software. A workload-level decision changed what the company needed to own without forcing its applications into an unsuitable model.
Time to reassess what belongs in-house—and what doesn’t
As the pressures behind The Great Infrastructure Reset converge, each pressure enters the budget from a different direction. These days, a refresh plan built around familiar costs can falter as hardware prices and lead times move. A VMware decision can reshape workload placement just as AI adds new capacity demands and cyber risk raises the standard for recovery. What still works in one part of the environment may create cost, risk, or constraint somewhere else.
Your team may still be fully capable of building and managing its next environment. What’s changing is whether the realities of The Great Infrastructure Reset will allow you to do so on the timeline and budget you intended.
Reconsidering ownership does not require a wholesale move away from on-premises infrastructure. Enterprises can retain it where economics or control requirements justify the commitment and use a provider where clearer pricing and greater flexibility reduce exposure. 11:11 Systems, with its award-winning resilient cloud platform, supports both choices within one coordinated strategy, so every workload does not have to follow the same path.
Is your infrastructure under pressure?
In the midst of The Great Infrastructure Reset, enterprises must determine where their current infrastructure strategy still fits—and where today’s conditions require a different approach—before outside pressure builds and crucial decisions are rushed. Refresh, platform, AI, and resilience decisions must now be evaluated together, while leaders still have the time and flexibility to choose deliberately.
With The Great Infrastructure Reset Impact Assessment, your organization can begin to gauge whether the combined pressure on its current plans is limited, moderate, or high. Participants can then schedule a separate, no-cost assessment with an 11:11 expert for a deeper review of its most urgent pressure points, the deadlines and dependencies behind them, and where action may be needed first.
