Agentic AI Contracts Create Unpredictable Financial Risks for Enterprises

Traditional procurement models relied on per-seat licensing, but agentic AI shifts the burden toward usage-based billing where vendors hold all the cards. Because pricing logic and billing definitions frequently reside in vendor-controlled documentation rather than the signed contract itself, organizations often discover their liability only after the invoice arrives. Without hard caps or audit rights, enterprises have little recourse when automated workflows inflate costs beyond original forecasts.

John Donovan, principal research director at Info-Tech Research Group, warns that once AI workflows are deeply embedded, the technical switching costs become prohibitive, effectively stripping companies of their negotiating leverage. To counter this, Info-Tech proposes a four-phase governance framework that mandates clear definitions, consumption throttles, and specific dispute mechanisms. Leaders must decode the underlying pricing logic and conduct forecast simulations to establish financial guardrails before the contract is finalized. By formalizing these protections early, organizations can avoid the trap of intelligence-driven pricing models that prioritize vendor revenue over enterprise cost stability.