Enterprise AI & Agentic AI
What questions should procurement ask an AI systems integrator?
Procurement should ask four questions: What production outcomes have you delivered on similar estates and can we speak to the client? Who owns the prompts, retrieval indexes and evaluation sets if we exit? How is success measured, and what happens if the pilot misses the metric? And what run-state support is included after go-live? The answers separate a delivery partner from a staffing vendor.
Last reviewed 2026-08-31 · pronix.ai
Key takeaways
- Outcome-based acceptance criteriaFixed-scope pilots with explicit metrics — containment, handle time, straight-through rate — make delivery verifiable instead of open-ended.
- Exit cost belongs in the contractPrompts, retrieval indexes, evaluation sets and runbooks should be portable; lock-in shows up as migration effort later.
- Run state is not an afterthoughtEvaluation drift, content tuning and platform releases continue after launch; the contract should cover who operates what.
What the numbers show
First-party figures from Pronix research. Each links to the report or playbook that publishes it.
- 31%
- Retrieval, integration and evaluation infrastructure is now the single largest line in the enterprise AI budget at roughly 31% of spend.Source: State of Agentic AI in the Enterprise 2026 →
- 22%
- Foundation models and inference now absorb roughly 22% of enterprise AI budgets, down from about 38% in 2024. The money moved to retrieval, integration, evaluation and the people who tune them.Source: State of Agentic AI in the Enterprise 2026 →
- 24%
- Engineering and product talent absorbs about 24% of enterprise AI spend — more than the models themselves.Source: State of Agentic AI in the Enterprise 2026 →
External references
- ISO/IEC — ISO/IEC 42001 — AI management systems (2023)The certifiable management-system standard enterprise procurement increasingly asks about.
- NIST — AI Risk Management Framework (AI RMF 1.0) (2023)The govern / map / measure / manage structure Pronix uses to organise AI controls.