AI procurement control guide

Build enforceable AI procurement governance with evidence, clauses, and monitoring

Use this guide to implement an AI procurement control system that screens suppliers, embeds regulator-aligned clauses, and keeps obligations measurable across the contract lifecycle.

Updated with EU AI Act provider-deployer accountability references, OMB Appendix C expectations, UK CCS procurement guardrails, and EU Data Act switching obligations.

Reference Zeph Tech research: supplier withdrawal drills, GPAI transparency requirements, and safety-impacting AI oversight patterns.

Executive overview

Traditional vendor management fails for AI systems because providers retain control over models, data pipelines, and safety updates. Regulation (EU) 2024/1689 assigns joint accountability to providers and deployers, requiring access to technical documentation, logging, and post-market monitoring signals. OMB M-24-10 demands evidence packs and independent evaluation support from suppliers before agencies deploy safety-impacting AI. UK Crown Commercial Service guidance emphasises ethics, explainability, and continuous assurance in AI procurements.

This guide builds a control framework that begins at intake and extends through renewal, ensuring every supplier contract can be defended during regulator inspections or customer audits. It complements the safety evaluation and monitoring guides by ensuring supplier obligations feed your internal evidence chain.

Intake and classification

  • Central request portal. Capture intended use, autonomy, data categories, affected populations, model provenance (GPAI vs bespoke), and integration points.
  • Risk triage. Apply decision trees that identify Article 5 bans, high-risk categories, workforce impact triggers, or sector-specific obligations (financial services, health, defence).
  • Screening outcomes. Route high-risk or safety-impacting requests to enhanced diligence and evaluation; low-risk automation follows a lightweight path with periodic re-attestation.
  • Record linkage. Tie requests to the AI inventory, evaluation plans, and monitoring owners to avoid duplicated purchases and to track supplier performance over time.

Due diligence and evidence collection

  • Questionnaires mapped to standards. Align with ISO/IEC 42001 governance clauses, NIST AI RMF controls, and OMB Appendix C expectations. Require suppliers to disclose model lineage, training data governance, and evaluation coverage.
  • Artefact requirements. Collect model cards, data sheets, Annex IV technical documentation, security attestations (SOC 2, ISO/IEC 27001), and independent evaluation reports. For GPAI providers, request AISIC benchmark outcomes and transparency reports.
  • Workforce and ethics review. For employment or safety-critical systems, require alignment with Department of Labor AI principles and UK ethics guidance. Document contestability channels and worker notification plans.
  • Risk register. Log findings, severity, and remediation commitments. Escalate blockers to procurement governance boards and defer award until critical items close.

Contract controls

  • Transparency deliverables. Schedule delivery of Annex IV-equivalent documentation, model update notices, evaluation reports, and safety filter performance metrics.
  • Audit and access. Reserve rights to inspect systems or commission third-party assessments, including cooperation with EU market surveillance or U.S. inspectors general.
  • Incident response. Mandate 24-hour notice for events meeting Article 62 or OMB Section 7 thresholds. Include joint investigation procedures, evidence preservation, and customer notification obligations.
  • Performance and safety SLAs. Define measurable service levels for accuracy, latency, safety filter efficacy, human oversight hooks, and change-management lead times. Include credits or termination for repeated violations.
  • Switching and portability. Enforce EU Data Act Article 23 switching rights: export tooling, configuration, embeddings, and fee caps during transition. Require cooperation during regulator-ordered withdrawal.
  • Subprocessor governance. Demand visibility into subcontractors, data residency, and security controls. Require advance approval for material changes.

Ongoing monitoring and renewal

  • Quarterly reviews. Assess performance, incident history, roadmap changes, and compliance posture. Compare against evaluation findings and monitoring dashboards.
  • Change control. Require pre-production testing for major model updates. Tie supplier change logs to your own monitoring thresholds and incident triggers.
  • Scorecards. Maintain supplier scorecards covering regulatory alignment, safety evidence, security posture, workforce impact controls, and exit readiness.
  • Renewal gating. Condition renewals on closing high-severity findings, delivering updated documentation, and demonstrating adherence to KPIs and SLA performance.

Implementation sprint (45 days)

  1. Days 1–10: Launch intake portal, publish triage decision tree, and train procurement staff on risk categories.
  2. Days 11–20: Release standard questionnaires and artefact lists; align with legal on default clauses and escalation rules.
  3. Days 21–35: Pilot the control set with two suppliers, run tabletop exercises for incident handling and switching, and refine scorecard metrics.
  4. Days 36–45: Finalise dashboards, integrate with the AI inventory and monitoring systems, and schedule quarterly governance reviews.

Upon completion, procurement can demonstrate consistent controls, evidence-backed decisions, and readiness for regulator or customer scrutiny.

Appendix: control artefacts

  • Procurement policy referencing EU AI Act, OMB M-24-10, UK CCS guidance, and sector mandates.
  • Intake decision tree with prohibited-practice and high-risk indicators.
  • Standard questionnaires, contract clause library, and remediation templates.
  • Supplier scorecards, quarterly review notes, and renewal readiness reports.
  • Switching runbooks, data export tooling references, and communication plans.
  • Audit trails linking supplier artefacts to evaluations, monitoring dashboards, and incidents.

Keeping these artefacts current ensures procurement decisions remain defensible and aligned with evolving regulatory expectations.