Artificial intelligence is fundamentally altering enterprise software by shifting pricing models away from seat-based access and toward work completed. This transition from Software-as-a-Service (SaaS) to Outcome-as-a-Service (OaaS) reflects a new reality where software no longer merely enables labor but increasingly performs and orchestrates it.
As software autonomy grows, traditional “per-user” models can underprice complex use cases or overprice simple ones. While companies like Intercom and platforms like Zendesk are already deploying outcome-based pricing for automated customer support resolutions, the legal and operational hurdles for broader adoption remain significant.
Our latest white paper provides a comprehensive framework for navigating this shift. Key considerations for enterprise leaders and legal counsel include:
The Hybrid Architecture: In most enterprise settings, the most robust transactional structure can be a hybrid model consisting of a recurring platform fee plus variable charges for tightly defined, auditable outcomes.
Enforceable Billing Units: A primary contracting challenge is transforming a value proposition into an objectively determinable event that can be verified via a stable system of record.
Regulatory & Accounting Compliance: OaaS models must navigate FASB/IFRS standards for revenue recognition and meet growing regulatory expectations for truthful AI disclosures and substantiated efficacy claims.
Change Management: Because AI performance is not static, contracts must include “re-baselining” triggers and robust change-control protections to address model drift or substitutions.
Risk Allocation: Sensible defaults should place benchmark performance risk on the vendor while keeping business value realization and input quality as shared or customer responsibilities.
Successfully implementing OaaS requires front-loading the design of measurement systems and governance records rather than treating billing as a downstream accounting problem. By prioritizing transparency, auditability, and interoperability, organizations can align their commercial interests with the actual value AI delivers.
Download the white paper [here].