In recent years, the procurement of AI staff vendors has been shifting from an experimental phase to standard enterprise procurement. The problem is that most organizations still evaluate them through the same framework as traditional SaaS tools. However, this approach is no longer sufficient because AI systems are not deterministic software, but dynamic systems that generate decisions, work with sensitive data, and may change their behavior over time without explicit product changes.
For this reason, the logic of procurement is shifting from questions like “how much does it cost” and “what is the API availability” to questions like “how does the system think”, “what data does it use”, and “how does it behave in unpredictable situations”.