AI infrastructure has crossed an important threshold. In recent client conversations, I no longer hear AI discussed as an experimental workload confined to data science teams. Instead, infrastructure leaders are being asked a much harder question: Can our infrastructure reliably scale AI from pilot to production without blowing up cost, operations, or risk?
That question is what led to The Forrester Wave™: AI Infrastructure Solutions, Q4 2025. This research evaluates the vendors shaping the next generation of AI-ready infrastructure and helps technology leaders make sense of a fast-moving, increasingly crowded market.
Why AI Infrastructure Decisions Feel Different
Unlike traditional infrastructure refresh cycles, AI infrastructure decisions compress timelines and amplify trade-offs. One client I spoke with invested heavily in GPUs to support early AI experimentation, only to discover that data pipelines, storage throughput, and power constraints quickly became the real bottlenecks. Another client selected an AI platform optimized for training but struggled to operationalize inference at scale across distributed environments.
These examples illustrate a broader shift: AI infrastructure is no longer just about compute. It’s about integrating systems that combine compute, networking, storage, software, and lifecycle operations into a cohesive platform.
What The Wave Evaluates — And Why It Matters
In this Wave, we evaluated vendors across current offering and strategy, with a strong emphasis on how well their solutions support real-world AI production needs. That includes:
Support for both training and inference workloads.
Operational readiness, including deployment models, observability, and lifecycle management.
Ecosystem alignment across silicon, software, and cloud services.
What stood out in this research is how clearly the market is segmenting. Some vendors excel at turnkey, vertically integrated AI infrastructure. Others differentiate through flexibility, ecosystem partnerships, or deployment choice across on-premises, cloud, and hybrid environments.
I also think it is important to note that I took a different approach to this version of the evaluation that is different from the 2023 version. Our clients have told us they want this evaluation to focus on the infrastructure solutions themselves, not the decisions higher in the stack to run their full AI stack. It is for this reason that our score scales and list of products evaluated doubles down on the infrastructure differentiation. Although we discourage year-over-year comparisons of Wave evaluations in general, this time around, that comparison may be particularly ill-advised.
From AI Experiments To AI Platforms
A recurring theme in my conversations with clients is the transition from “Can we run AI?” to “Can we run AI reliably, repeatedly, and responsibly?” That shift requires infrastructure teams to think beyond individual components and toward AI platforms.
The Wave helps leaders understand which vendors are best positioned to support that transition — whether the priority is speed to value, operational control, cost governance, or long-term architectural flexibility.
How To Use This Research
This Wave is not about picking a single “best” vendor. It’s about matching your AI ambitions to the right infrastructure capabilities. Infrastructure and platform leaders can use this research to:
Shortlist vendors aligned to their AI maturity and deployment model.
Understand trade-offs between integrated systems and modular approaches.
Pressure-test vendor roadmaps against their own AI scale expectations.
As AI moves from experimentation to execution, infrastructure choices will increasingly shape business outcomes. The Forrester Wave™: AI Infrastructure Solutions, Q4 2025, is designed to help leaders make those choices with clarity and confidence.
If you’d like to dig deeper into interpreting vendor positioning, mapping the findings to your environment, or discussing how to operationalize AI infrastructure at scale, I encourage you to schedule an inquiry call or a guidance session with me.
