Token-as-a-Service (TaaS) Procurement: An enterprise governance framework for consumption-based AI

Abstract

The rapid adoption of Large Language Models (LLMs) is transforming enterprise technology procurement from traditional software licensing toward consumption-based artificial intelligence services. Unlike perpetual licenses or Software-as-a-Service (SaaS) subscriptions, modern AI platforms increasingly employ token-based pricing models in which organizations procure computational intelligence according to usage. Existing procurement frameworks were developed for fixed commercial models and provide limited guidance for forecasting demand, negotiating consumption-based contracts, governing multi-vendor AI portfolios, and optimizing enterprise-wide token utilization throughout the AI lifecycle. This paper introduces Token-as-a-Service (TaaS) Procurement, a procurement paradigm that treats AI tokens as strategic enterprise resources requiring continuous commercial governance rather than one-time acquisition. To operationalize this paradigm, the paper proposes the Enterprise Intelligence FinOps (EIFO) framework, which integrates business demand management, token forecasting, commercial sourcing, supplier governance, runtime consumption monitoring, financial accountability, and continuous optimization into a unified enterprise operating model. The paper further develops quantitative models for enterprise AI cost estimation, procurement optimization, governance compliance, and business value measurement, demonstrating how procurement organizations can align AI investments with organizational objectives while maintaining commercial flexibility and governance oversight. By positioning procurement as a continuous enterprise capability rather than a transactional purchasing function, this research establishes a governance foundation for managing consumption-based AI services within evolving Large Language Model ecosystems.