Why buyers lose
Why Google Cloud negotiations require specialist advisory.
Google Cloud Platform has invested heavily in enterprise capabilities, Vertex AI, BigQuery, Anthos, Google Workspace, and a rapidly expanding portfolio of managed services. But GCP's commercial model remains less mature than AWS or Azure in key areas: committed use discount structures, enterprise agreement terms, and support tier pricing can vary significantly based on relationship context, competitive dynamics, and the commercial sophistication of the buyer's negotiating position.
Committed Use Discounts (CUDs), GCP's primary mechanism for reducing compute costs, are structured differently from AWS Reserved Instances, with resource-based and spend-based variants that carry different flexibility and risk profiles. Google's enterprise agreement terms, while negotiable, are often presented by GCP account teams as largely standard. They are not. Discount authority within GCP's sales organisation is significant, particularly for accounts where competitive displacement of AWS or Azure workloads is realistic.
GCP's aggressive push into AI and machine learning, through Vertex AI, Gemini, and AI-optimised TPU infrastructure, creates specific procurement challenges around usage-based pricing, model inference costs, and the governance of AI workloads at enterprise scale. Our advisors have structured enterprise AI agreements with GCP that include performance SLAs, cost caps, and contractual protections that GCP's standard terms do not provide.
