Topic starter
25/06/2026 12:41 am
TL;DR: AI in vendor and internal software needs explicit procurement scrutiny around opt-in use, data training, documentation, retention, monitoring, and downstream cost exposure, according to Delinea. Procurement teams cannot treat AI as a feature toggle; they need governance gates that surface hidden data, control, and accountability risks before renewal or expansion.
Editorial analysis by NHI Mgmt Group, based on content published by Delinea: “Essential AI questions for a comprehensive vendor security assessment”.
Key questions
Q: What breaks when AI features are enabled without explicit opt-in?
A: When AI features are enabled by default, security teams lose a clear approval boundary for data use, access scope, and business ownership.
Q: Why do vendor AI assessments need questions about training data and retention?
A: Because training use and retention determine whether customer inputs and outputs stay bounded to the buyer’s intended purpose or become part of a supplier’s wider learning and logging system.
Q: What do security teams get wrong about AI in procurement?
A: They often focus on model capability and ignore governance boundaries.
Practitioner guidance
- Require explicit AI opt-in before activation Do not accept default-on AI features or ambiguous banner-based enablement.
- Validate training and reuse boundaries Ask whether customer inputs, prompts, outputs, or derived data are used for training, fine-tuning, or model improvement, and require a clear tenant-specific answer for each workflow that may process sensitive data.
- Set retention and monitoring expectations Confirm how long prompts, inputs, and outputs are retained, who can access them, and whether the tool supports logging and review of AI activity for audit and incident response.
Bottom line: AI-enabled vendor software creates governance risk when teams cannot tell whether features are opt-in, how data is reused, or how long prompts and outputs are retained.
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25/06/2026 9:39 am
AI procurement is now an identity governance problem, not only a security questionnaire problem. The article shows that questions about training, retention, monitoring, and enablement determine whether a vendor’s AI feature is controlled or simply embedded. That puts procurement decisions squarely inside governance, because the buyer is authorising how data and access are handled before the product is widely adopted. Security teams should treat AI approval as a lifecycle decision with policy, evidence, and review points.
A few things that frame the scale:
- Only 44% of organisations have implemented any policies to manage their AI agents, despite 92% agreeing that governing AI agents is critical to enterprise security, according to the 2026 Infrastructure Identity Survey.
A question worth separating out:
Q: Should organisations re-evaluate AI-enabled software at renewal as well as purchase?
A: Yes. AI features evolve after initial approval, and the commercial and governance terms can change as usage expands. Renewal reviews are the right point to confirm whether the original assumptions about data handling, monitoring, pricing, and control are still true.
👉 Read our full editorial: AI vendor security assessments need explicit governance questions