AWS Secures Top Strategy Ranking in Forrester’s AI Infrastructure Report

The analyst designation, formally dated December 16, 2025, lands as enterprise IT teams wrestle with inference cost overruns and chip-allocation queues. For buyers weighing model deployment platforms, the quadrant placement matters far less than what the underlying scorecard actually measures.

Strip the quadrant, read the criteria

Forrester's evaluation ran across current offering, strategy, and customer feedback. AWS posted a perfect 5.00 in 16 criteria and topped the strategy axis. The vendor's framing — proprietary silicon (Inferentia, Trainium) running alongside NVIDIA GPU instances — is positioned as an anti-lock-in architecture. Whether that dual-track compute story holds in production is a separate question the Forrester evaluation does not adjudicate.

The criteria tell the operational story. Forrester analysts observed that AWS fits companies with "high-volume or elastic inference workloads that prioritize cost efficiency but still need access to GPUs for peak performance scenarios." High-volume inference. Elastic scaling. Cost-weighted compute. Occasional GPU peaks. That is a narrow but defensible profile. Organizations running sparse or exploratory workloads are not the target — and the scorecard does not pretend otherwise.

The disclosure that travels with every badge

Forrester's own standard language underpins every Wave report: the firm does not endorse any company, product, brand, or service. Ratings reflect analyst judgment at a point in time and are subject to change. The announcement here originated on AWS's own news channel, not an independent editorial outlet. That is not corruption. It is the disclosure a skeptical reader needs before treating the quadrant as gospel.

What to pull before procurement signs

The real question is not the badge but the invoice. Enterprises evaluating AWS for inference should pull three things before signing: instance-hour pricing for Inferentia and Trainium against equivalent NVIDIA SKUs at their actual utilization bands, SageMaker integration overhead against their existing MLOps stack, and reserved-capacity terms. Analyst rankings reset every quarter. Infrastructure bills compound monthly. Any architect who treats a Wave placement as a multi-year commitment should be asked to defend it on a spreadsheet, not a slide deck.