Spotlight

Report:

The Forrester Wave™: AI Infrastructure Solutions, Q4 2025

How does Forrester define the AI Infrastructure Solutions market in 2025?

AI infrastructure solutions provide the foundational compute, network, and storage capabilities required to run AI workloads including training, fine-tuning, and inference. Enterprises are multiplying their AI infrastructure investments and looking critically at systems beyond just basic GPUs and high-performance servers. They seek infrastructure that follows the OASIS Framework and enables workload- and outcome-specific design choices. The evaluation focuses on infrastructure itself rather than capabilities further up the stack, representing a notable change from the 2023 version. Success requires architecture for workload-specific demands, engineering efficiency across the full stack, and sustainability with operational maturity and long-term flexibility.

Key Facts for The Forrester Wave™: AI Infrastructure Solutions, Q4 2025 in 2025

How did the AI Infrastructure Solutions market evolve in 2025?

What product features are required to be included in this year's evaluation?

What are the common features of top products in the AI Infrastructure Solutions space?

No common features specified.

Scope Exclusions

Inclusion Criteria

Vendors must, among other requirements:

Offering Strengths — Relative Weighting

Strategy Strength — Relative Weighting

FAQs

Q: What does this research cover?

A: This research evaluates 13 AI infrastructure solution providers, focusing on the infrastructure layer — compute, network, and storage — and how it enables AI workloads. The evaluation examines vendor capabilities across training, fine-tuning, and inference workloads, with emphasis on workload-specific design, engineering efficiency across the full stack, sustainability, operability, and long-term flexibility. Vendors are scored on current offering capabilities and strategic vision.

Q: Who should use this research?

A: AI infrastructure solutions customers should use this research to inform purchase decisions and ensure their infrastructure choices translate into production-grade, sustainable value. It is particularly relevant for organizations accelerating AI initiatives who need to understand how different vendors address workload-specific demands (training, fine-tuning, inference), engineering efficiency across compute/network/storage/orchestration, and sustainability/operability/flexibility requirements. Buyers should adapt findings based on their specific priorities using Forrester's interactive provider comparison experience.

Q: What are the mandatory features of vendors included in this market?

A: To be included in this Forrester Wave evaluation, vendors must: 1) Provide broad, enterprise-level support with all core functions and demonstrated track record for large enterprises, 2) Manufacture/build AI infrastructure or provide hosted AI infrastructure services based on their own IP, 3) Offer solution as standalone product with own SKU and pricing (not just free feature), 4) Generate at least $100 million in annual revenue from AI infrastructure solutions in past four quarters, and 5) Have significant mindshare among Forrester's enterprise clients as a frequently considered vendor for purchase decisions.

Q: What are some reasons for not being included in this report?

A:

  • Annual revenue from AI infrastructure solutions below $100 million threshold
  • Lack of enterprise-level support capabilities or track record
  • Solution only available as bundled feature without standalone SKU/pricing
  • Does not manufacture/build infrastructure or provide hosted services based on own IP
  • Insufficient mindshare among Forrester enterprise clients
  • Does not natively provide all core functions for AI infrastructure space
  • Focus on capabilities above infrastructure layer rather than core compute/network/storage

Q: What should buyers consider when evaluating products in this market?

A:

  • Architecture for workload-specific demands rather than generic computational needs - align hardware, interconnects, and data pipelines to specific AI workload types (training, fine-tuning, inference)
  • Engineering efficiency across entire stack - ensure compute, network, storage, and orchestration are coordinated to maximize GPU utilization and avoid bottlenecks
  • Sustainability and power management - evaluate energy-efficient accelerators, liquid cooling capabilities, and thermal optimization for data center constraints
  • Operational maturity - assess integrated observability, security controls, and management capabilities
  • Long-term flexibility - avoid vendor lock-in by ensuring ability to adopt next-gen accelerators and hybrid models without disruptive replatforming
  • Workload-specific performance - validate solution handles your specific mix of training, fine-tuning, and inference requirements
  • Total cost of ownership - consider not just hardware costs but utilization rates, power consumption, and operational efficiency

Q: How has the AI Infrastructure Solutions market evolved in 2025?

A:

  • Businesses accelerating AI initiatives with multiplied infrastructure investments in past couple years
  • Shift from generic GPU focus to workload-specific infrastructure design (training, fine-tuning, inference)
  • Growing emphasis on full-stack efficiency across compute, network, storage, and orchestration
  • Increased focus on sustainability including energy-efficient accelerators, liquid cooling, power-aware scheduling
  • Need for architectural flexibility to avoid vendor lock-in and support next-gen accelerators
  • Integration of observability and security controls for data sensitivity
  • Movement toward OASIS Framework for infrastructure foundation
  • Recognition that models alone don't matter - infrastructure systems are critical

Q: What differentiates Strength of Offering vs. Strength of Strategy?

A: Strength of Offering focuses on current capabilities including architecture, infrastructure components (compute, network, storage), workload support (training, inferencing, development), operational features (management, fault tolerance, efficiency, security, scalability), and deployment options. It evaluates what the vendor delivers today. Strength of Strategy evaluates future direction including vision for AI infrastructure evolution, innovation in hardware/software development, product roadmap clarity, partner ecosystem breadth, pricing models, and supporting services. It assesses where the vendor is headed and their ability to execute on future plans.

Reference

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