AI infrastructure has reached a pivotal moment as organizations move beyond viewing it as an experimental workload limited to data science teams. In recent dialogues with clients, infrastructure leaders are increasingly faced with a pressing question: can our infrastructure scale AI from pilot to production without incurring excessive costs, operational disruption, or heightened risks? This inquiry has led to the release of The Forrester Wave™: AI Infrastructure Solutions, Q4 2025, a report that assesses vendors shaping the next generation of AI-ready infrastructure and aids technology leaders in navigating an evolving and competitive landscape.
Unlike past infrastructure refresh cycles, decisions surrounding AI infrastructure are characterized by compressed timelines and amplified trade-offs. One client who heavily invested in GPUs to support initial AI experimentation found that bottlenecks arose from data pipelines, storage throughput, and power limitations. Another client, while selecting an AI platform optimized for training, encountered challenges in operationalizing inference at scale across distributed environments. These scenarios exemplify a broader transition: AI infrastructure now extends beyond mere compute to encompass integrated systems that combine compute, networking, storage, software, and lifecycle operations into a unified platform.
The Forrester Wave evaluates vendors based on their current offerings and strategies, with a strong focus on how effectively their solutions address real-world AI production needs. Key considerations include support for both training and inference workloads, operational readiness—which entails deployment models, observability, and lifecycle management—and ecosystem alignment across silicon, software, and cloud services. Notably, the research highlights market segmentation, with some vendors excelling in turnkey, vertically integrated AI infrastructure while others distinguish themselves through flexibility, ecosystem partnerships, or diverse deployment options across on-premises, cloud, and hybrid environments.
This evaluation approach differs from previous assessments by emphasizing infrastructure solutions rather than decisions at higher levels of the tech stack. Clients have expressed a desire for results that focus on infrastructure differentiation, leading to a doubling down on the metrics and products evaluated. While year-over-year comparisons are generally discouraged in Wave evaluations, this iteration may be particularly ill-advised due to its unique focus.
A recurring theme in discussions with clients is the shift from simply asking, “Can we run AI?” to a more complex inquiry: “Can we run AI reliably, repeatedly, and responsibly?” This evolution necessitates that infrastructure teams consider AI platforms holistically rather than solely individual components. The Wave provides insights into which vendors are best positioned to facilitate this transition, whether the emphasis is on speed to value, operational control, cost governance, or long-term architectural flexibility.
This report is not designed to identify a single “best” vendor but rather to align AI ambitions with appropriate infrastructure capabilities. Infrastructure and platform leaders can leverage this research to shortlist vendors that match their AI maturity and deployment model, understand the trade-offs between integrated systems and modular approaches, and pressure-test vendor roadmaps against their own expectations for scaling AI.
As AI transitions from experimentation to execution, the choices surrounding infrastructure will increasingly influence business outcomes. The Forrester Wave™: AI Infrastructure Solutions, Q4 2025 aims to empower leaders to make informed decisions with clarity and confidence. For those interested in delving deeper into vendor positioning or operationalizing AI infrastructure at scale, scheduling an inquiry call or guidance session is encouraged.
For further insights into the AI landscape, organizations can explore the offerings of major players like Nvidia, OpenAI, and Microsoft, all instrumental in shaping the current infrastructure capabilities that support the burgeoning AI ecosystem.
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