The enterprise AI market has no standard licensing model. This white paper maps every major vendor's pricing architecture and delivers a multi-vendor procurement strategy that maximises competitive tension while securing volume pricing across your AI portfolio.
Get instant access to the complete white paper, normalised cost comparison framework, and multi-vendor procurement playbook.
Comprehensive procurement intelligence covering every major enterprise AI vendor and pricing model.
Complete breakdown of how OpenAI, Anthropic, Google, AWS, and Microsoft structure their AI licensing — per-token, per-seat, consumption-based, and hybrid models compared side by side.
Our EC/kST (Effective Cost per 1,000 Standardised Tasks) methodology that enables genuine apples-to-apples comparison across vendors with different pricing units, tokenisers, and quality tiers.
Structural pressure points that create pricing leverage across AI vendors — from model-agnostic architecture to cross-platform arbitrage and strategic partnership positioning.
Detailed analysis of each vendor's commercial model including discount structures, commitment mechanisms, volume tiers, and the specific terms that drive negotiation outcomes.
Six common AI procurement traps — from the "land and expand" lock-in to shadow AI spend — with specific counter-strategies to avoid costly mistakes in a rapidly evolving market.
The three-tier portfolio model for structuring AI procurement across primary, secondary, and evaluation vendors — including a competitive tension execution playbook.
The enterprises that will pay the most for AI over the next five years are the ones making uncoordinated, single-vendor commitments today. Portfolio thinking isn't optional — it's the only strategy that survives a market this volatile.
— Redress Compliance, AI & Cloud Practice