Your Next Hardware Refresh Won't Look Like the Last One.

For years, businesses approaching a hardware refresh faced a fairly predictable decision: purchase new servers, storage, and networking equipment, depreciate that investment over several years, and repeat the process when the next refresh cycle arrived.

But 2026 isn’t a normal infrastructure buying cycle.

The explosive growth of artificial intelligence is changing how infrastructure is purchased, where technology investments are directed, and, most importantly, who gets priority when demand exceeds supply.

For businesses approaching a hardware refresh, the question may no longer be simply whether cloud infrastructure is more convenient than purchasing hardware.

It may be: Does purchasing and maintaining your own infrastructure still make financial sense in a market increasingly being shaped around AI?

AI Is Competing for the Same Infrastructure You Need

AI may feel like a separate technology initiative, but underneath it is an enormous physical infrastructure buildout.

AI requires processors, memory, storage, networking, power, cooling, and data center capacity. And the companies building the world’s largest AI environments are buying those resources at extraordinary scale.

TechTarget reported that combined capital spending by Alibaba, Alphabet, Amazon, Apple, Microsoft Azure, and Meta reached approximately $137 billion in Q1 2026, up from $83 billion in Q1 2025 and $51 billion in Q1 2024.

That investment has consequences far beyond companies actually deploying AI.

InfoWorld reports that major cloud providers are purchasing enormous quantities of GPUs, memory, and other hardware for AI workloads, contributing to scarcity and higher costs throughout the technology supply chain. That means traditional businesses looking to refresh servers or expand their existing infrastructure are competing indirectly with some of the world’s largest technology companies.

AI doesn’t have to be part of your IT strategy for AI to affect your IT budget.

Hardware Pricing Is Already Feeling the Pressure

The traditional hardware refresh model relies on a relatively simple assumption: technology gets better, and the cost of comparable capacity generally becomes more attractive over time.

That assumption is becoming harder to make.

According to TechTarget, memory and SSD prices have risen dramatically as hyperscale data centers invest heavily in AI computing systems. The publication notes that organizations that purchased systems just a year or two ago expecting to expand memory and storage in 2026 are instead finding those upgrades significantly more expensive.

It’s reported that memory prices increased by 80%-90 % between Q4 2025 and Q1 2026, with supply expansion potentially taking years to catch up.

And this isn’t limited to memory.

AI infrastructure requires enormous investments in compute, storage, networking, data centers, cooling, and electricity. Major U.S. technology companies could spend roughly $650 billion on AI-related infrastructure in 2026, compared with approximately $410 billion in 2025.

For businesses planning a traditional infrastructure refresh, those numbers matter.

Your Next Hardware Refresh Could Look Very Different

Imagine your organization normally replaces infrastructure every three to five years.

Historically, you might wait until the final year of that lifecycle, request updated pricing, secure a capital budget, place an order, and migrate to the new environment.

That strategy assumes three things:

The equipment will be available.
The price will be reasonable.
And you will have time to make the decision.

Those assumptions are becoming riskier.

AI demand is currently outstripping supply for data center and compute capacity. And memory manufacturers can’t simply turn on additional capacity overnight. Bringing a new semiconductor fabrication facility into volume production could take at least two years.

That makes infrastructure planning increasingly important.

Waiting until your hardware reaches end of life to decide what comes next could leave you making one of your largest IT investments at exactly the wrong time.