Legal and risk checklist for procuring conversational AI platforms

This legal and risk checklist for procuring conversational AI platforms is a concise, bottom-funnel guide procurement and legal teams can use to accelerate approvals while surfacing the contract-ready asks that mitigate organizational risk. Use this checklist to prioritize questions, clauses and operational controls that vendors should accept before you sign.

Quick summary: purpose and scope — legal and risk checklist for procuring conversational AI platforms

Purpose: provide a clear, actionable bottom-funnel checklist that drives procurement acceleration and reduces back-and-forth between legal, security and business stakeholders. Scope: typical commercial conversational AI platforms used for customer support, internal knowledge assistants, and automated workflows — focusing on privacy, data residency, incident response and exit rights.

This legal and risk checklist for procuring conversational AI platforms helps procurement teams translate compliance concerns into contract language and short vendor questionnaires. Keep this as a reference when assessing responses and negotiating DPAs, SLAs and termination provisions.

1) Lawful basis, consent and data minimization

Confirm the vendor supports your lawful-basis model and can document how data is collected and processed. Ask for evidence that the platform enables data minimization, consent capture where required, and configuration options to avoid logging or transcribing sensitive inputs.

• Ask: Can the vendor provide sample consent language and a data flow map showing where conversational logs are stored?
• Contract-ready ask: Include a clause requiring the vendor to support your lawful basis decisions, disable non-essential logging, and document retention periods.

2) Data Processing Agreement (DPA) & mappings

Require a clear DPA that maps roles and responsibilities, lists processing purposes, and commits to data subject rights cooperation. The DPA should enable straightforward compliance with access, rectification, deletion, and portability requests.

• Ask: Provide a copy of the standard DPA and examples of how they handle SARs (subject access requests).
• Contract-ready ask: Add explicit timelines for handling data subject requests and obligations to notify you of requests impacting your data.

3) Sub-processor inventory and flow-downs

Obtain a current list of sub-processors and the legal flow-downs that bind them to the same privacy and security obligations. Confirm change notification practices and the ability to object to new sub-processors during a defined window.

Include a conversational AI vendor due diligence checklist to track sub-processor certifications, locations, and the exact contractual flow-down language. That checklist makes it much easier to score vendors consistently during procurement rounds.

• Ask: Current sub-processor list, certifications (SOC 2 / ISO 27001) and contractual flow-down language.
• Contract-ready ask: Right to be notified of new sub-processors and to terminate or suspend processing if a critical sub-processor poses material risk.

4) Data residency, regional hosting and export controls

Verify where conversational data is stored and whether regional hosting options exist to meet compliance or sovereignty requirements. Confirm how data transfer mechanisms (e.g., SCCs) are applied for cross-border flows.

As a practical step, create a short evaluation playbook titled “how to evaluate data residency, breach SLAs and DPAs when buying conversational AI” so legal and IT score vendors against the same criteria for residency, transfer mechanisms, and contractual protections.

• Ask: Regional hosting locations, default storage region per tenant, and mechanisms used for international transfers.
• Contract-ready ask: Commitments on regional residency, permitted transfer mechanisms, and advance notice for migrating data across jurisdictions.

5) Incident response, breach notification timelines & SLAs

Ensure the vendor has a documented incident response plan and contractual breach-notification timelines that meet your regulatory obligations. SLAs should define availability, performance expectations and remedies for outages that impact critical workflows.

• Ask: Incident response playbook, historic security posture, and SLA definitions for uptime and support response times.
• Contract-ready ask: Maximum breach-notification window (e.g., 72 hours), defined remediation steps, and financial or service remedies for SLA failures.

6) Security controls, encryption and access management

Validate encryption at rest and in transit, role-based access controls, audit logging and admin separation. Request evidence of independent security assessments and certifications to substantiate vendor claims.

• Ask: Encryption standards, key management approach, and available authentication/integration options (SAML, SCIM).
• Contract-ready ask: Right to audit or receive third-party audit reports and commitments on encryption practices for customer data.

7) Acceptable use, content moderation and brand safety

Confirm the vendor’s approach to acceptable use and automated content moderation to protect brand safety. Understand controls for filtering or blocking harmful outputs and escalation paths for content incidents.

• Ask: Published acceptable-use policies, moderation tooling, and examples of how risky prompts are handled.
• Contract-ready ask: Obligations to prevent, detect and remediate outputs that violate your brand-safety standards and removal timelines for harmful content.

8) Model provenance, customization and downstream risks

Document the underlying model(s) used, whether models are multi-tenant or dedicated, and how fine-tuning or custom data is isolated. Assess downstream risks such as model hallucination and the vendor’s mitigation strategies.

• Ask: Which models power the service, isolation guarantees for custom training data, and accuracy/limitations disclosures.
• Contract-ready ask: Warranties or disclaimers about model behavior, limits on using customer data to improve public models, and obligations to segregate training data.

9) Termination, data export, and escrow

Clarify data export formats, timelines for data export after termination, and whether escrow or transitional services are available to ensure continuity. Define responsibilities for secure deletion unless retention is contractually required.

When negotiating exit terms, insist on contract clauses to require from conversational AI vendors: data export, escrow and termination — and define the formats and timelines you’ll accept for exports and certified deletion.

• Ask: Export formats, extraction process, and average time to deliver a complete data export.
• Contract-ready ask: Exit assistance, guaranteed export timelines, and certified deletion procedures after contract termination.

10) Governance, audit rights and insurance

Request governance documentation and audit rights that let you verify compliance. Confirm the vendor’s liability posture and insurance coverage for data breaches or service failures affecting your operations.

• Ask: Recent penetration tests, audit reports, and proof of cyber insurance coverage.
• Contract-ready ask: Audit windows, remediation commitments and minimum insurance thresholds tied to potential risk.

11) Practical RFP language & negotiation tips

Provide ready-to-use RFP snippets and negotiation priorities: insist on documented sub-processor flow-downs, defined breach timelines, region-bound hosting, clear export/termination rights, and a DPA aligned to your jurisdictional requirements. Prioritize ask items by legal and operational impact to speed procurement acceleration.

Treat this section as your conversational AI procurement legal checklist when drafting RFPs and scoring responses — it helps you convert risk items into negotiable contract language and redlines.

12) Quick checklist — one-page summary

This procurement checklist for AI conversation platforms condenses the most contract-critical asks into a one-page list you can paste into RFPs or vendor questionnaires for faster review cycles.

1. Lawful basis & consent controls documented
2. DPA with data subject rights and timelines
3. Sub-processor list & flow-downs
4. Data residency options & transfer mechanisms
5. Breach notification timelines & incident playbook
6. Encryption, access control and auditability
7. Acceptable use and brand-safety commitments
8. Model provenance and customization isolation
9. Termination, export timeline & escrow options
10. Audit rights, governance evidence and insurance

Use this legal and risk checklist for procuring conversational AI platforms as a living document: adapt items to your regulatory environment and business model, and convert high-priority asks into contract language early to minimize negotiation cycles.