Law Firm Tool Procurement: Questions to Ask About AI and Security

Stop buying black‑box legal tech: the procurement questions solicitors must ask about AI and security

Hook: When you’re under pressure to onboard a new contract‑review tool, CRM or document automation platform, the last thing you need is uncertainty about who trained the model, where your clients’ data will live, or whether the vendor can prove what changed after a critical update. In 2026, those are procurement failures — and potential regulatory traps.

The most important points up front (inverted pyramid)

Before you run an evaluation workshop, get these four answers in writing: the vendor’s AI provenance (model lineage and data sources), their enterprise/FedRAMP credentials (if you need them), concrete data residency commitments, and machine‑readable audit logs that record prompts, outputs and model versions. If any of those are vague, escalate and pause procurement.

Why these four questions matter in 2026

• Regulators in the UK, EU and US increased scrutiny of AI provenance and model accountability in late 2025 — public bodies and large enterprises now expect traceability.
• FedRAMP and similar government/commercial frameworks are being used as a procurement litmus test for AI-enabled SaaS platforms; vendors acquiring FedRAMP approvals have made headlines in late 2025.
• Cross‑border data transfer rulings and updated transfer mechanisms mean data residency promises are central to GDPR/UK‑GDRP compliance and client confidentiality.
• Litigation, eDiscovery and regulatory audits increasingly demand immutable audit trails for AI‑assisted decisions and outputs.

A practical vendor evaluation questionnaire: what to ask and what to expect

This section is a working questionnaire. Use it in procurement packs, attach it to RFPs, or embed it into your security questionnaire. For each item, we include suggested evidence to request and red flags to watch for.

Section A — AI provenance (model lineage and training data)

1. Question: Provide the model lineage: base model name/version, fine‑tuning steps, and deployment identifiers for models that will process our data.
   • Evidence to request: Model card, versioned artifact IDs, release notes and cryptographic hashes for model binaries.
   • Acceptable answer: A clear model card with dates, training checkpoints and a signed attestation of the training process.
   • Red flag: “Proprietary” or “trade secret” answers without any audited lineage or independent attestations.
2. Question: Describe the provenance of training and fine‑tuning data. Were public, licensed or client datasets used? Any PII in training corpora?
   • Evidence: Dataset manifests, license terms, redaction policies, and results of data provenance scans.
   • Acceptable answer: A dataset inventory with labels (public/open, licensed, synthetic, client‑supplied) and a PII risk assessment.
   • Red flag: Vendor cannot demonstrate how PII was excluded or protected during model training.
3. Question: Do you apply watermarking, artifact‑level provenance or output‑level provenance (e.g., cryptographic watermarking or metadata tags) to generated outputs?
   • Evidence: Demo of watermark detection, schema for embedded provenance metadata, or signed output certificates.
   • Acceptable answer: Yes — outputs include verifiable metadata (model version, timestamp, request hash) and detection tools are available.
   • Red flag: No provenance on outputs or tools that only rely on vendor trust with no independent verification.

Section B — FedRAMP / enterprise credentials and compliance

Federal authorisations are often the baseline for enterprise procurement. If your firm handles government matters, or wants the highest maturity, ask these:

1. Question: Do you hold a FedRAMP ATO? At what impact level (Low / Moderate / High)? Please provide the System Security Plan (SSP), continuous monitoring artifacts and the ATO date.
   • Evidence: FedRAMP PMO listing, SSP (redacted where necessary), POA&M (Plan of Action & Milestones), continuous monitoring reports.
   • Acceptable answer: Vendor is FedRAMP authorised (state level), or provides a documented roadmap with milestones to obtain ATO within an agreed timeframe.
   • Red flag: Vague claims like “we meet FedRAMP requirements” without PMO listing or SSP.
2. Question: Provide current certification evidence: SOC 2 Type II, ISO 27001 scope, PCI DSS (if relevant). How frequently are audits conducted and by whom?
   • Evidence: Latest audit reports, assessor contact details, and scope definitions.
   • Acceptable answer: SOC 2 Type II covering relevant services, ISO 27001 with defined scope, independent attestations.
   • Red flag: Outdated, incomplete or self‑certified reports lacking independent assessor details.
3. Question: For non‑US customers: how do you support data protection adequacy and cross‑border transfer mechanisms (e.g., SCCs, Data Privacy Framework)?
   • Evidence: Standard Contractual Clauses (SCC) templates, Data Processing Addendum (DPA), and international transfer impact assessments.
   • Acceptable answer: Vendor uses up‑to‑date transfer mechanisms and provides documented transfer impact assessments under GDPR/UK‑GDRP.

Section C — Data residency, segregation and retention

1. Question: Where will our data be stored, processed and backed up? Can you guarantee in‑region storage for all PII and client work product?
   • Evidence: Data flow diagrams, signed commitments in the DPA, region selection options in the product UI.
   • Acceptable answer: Clear regions (e.g., EU‑West, UK‑South, US‑East) with the ability to pin tenant data to a region under contract.
   • Red flag: “Data may be processed globally” without options for regional tenancy.
2. Question: How is multi‑tenancy enforced? Describe logical and physical segregation, and how you prevent cross‑tenant leakage.
   • Evidence: Architecture diagrams, tenancy model, encryption key management details, tenant‑level access controls.
   • Acceptable answer: Strong logical segregation (namespace, RBAC), tenant encryption keys, per‑tenant audit trails.
3. Question: What default retention periods apply for logs, prompts, outputs and backups? Can we request deletion or export on termination?
   • Evidence: Retention policy, deletion SLA, deletion certificates, data export APIs.
   • Acceptable answer: Explicit retention windows with contractual deletion and export (e.g., 30/90/365 days) and certification of deletion.
   • Red flag: Indefinite retention or deletion “in accordance with internal policies” without contract terms.

Section D — Audit logs, observability and evidence for litigation

Law firms must be able to prove what happened and when. Ask these concrete questions.

1. Question: What events are logged by default? Do logs include prompts, full outputs, model version, user ID, timestamp, and request/response hashes?
   • Evidence: Sample logs (sanitised), schema documentation, export capability and query tools.
   • Acceptable answer: Logs capture all essential fields (prompt, redacted PII, full output, model/version, user attribution, IP and timestamps).
   • Red flag: Logs that only show user activity without linking outputs to model versions or timestamps.
2. Question: Are logs tamper‑evident and exportable? Provide details on hashing, WORM storage, and SIEM integration (Syslog, API, Splunk, Datadog).
   • Evidence: Hashing methods, export APIs, sample SIEM integration guides, SLA for log retention and exports.
   • Acceptable answer: Exportable logs, tamper evidence (hashes/WORM), and direct integration with common SIEMs.
3. Question: What is the retention policy for audit logs and how can we obtain them for eDiscovery or regulatory requests?
   • Evidence: Retention and preservation policies, eDiscovery export tools and forensic support options.
   • Acceptable answer: Contractual retention plus on‑demand preservation with forensic export formats and timestamps preserved.

Section E — Change management, model updates and release control

AI models change frequently. You must control how and when changes are introduced to your tenancy.

1. Question: How do you manage model updates? Describe your release cadence, canary testing, rollback procedures and communication plan.
   • Evidence: Change management policy, release notes, prior change logs, staging environment access for customers.
   • Acceptable answer: Scheduled releases with advance notification (e.g., 30 days for non‑critical changes), staging tests and a clear rollback SLA.
   • Red flag: “We push changes continuously” without customer opt‑out or staging/testing offers.
2. Question: Can we freeze model upgrades for specific environments (production vs sandbox)? If so, for how long and on what terms?
   • Evidence: Contract clause or admin controls to pin model versions, pricing or limits for version freezes.
   • Acceptable answer: Yes — customers can pin models for a defined term (e.g., 6–12 months) and opt into upgrades after testing.
3. Question: What validation and re‑testing do you perform after a substantial model change (e.g., safety, bias, accuracy, PII leakage tests)? Can we require requalification before accepting the change?
   • Evidence: Test suites, red‑team reports, bias and accuracy benchmarks, and customer sign‑off processes.
   • Acceptable answer: Comprehensive pre‑release testing with documented results; contractual right to require requalification for critical workflows.

Contractual protections and clauses to insist on

Technical answers must be backed by contract language. At procurement, push for:

• Data Processing Addendum (DPA) with explicit data residency, deletion, export, subprocessors list and breach notification timelines.
• Service Level Agreement (SLA) including uptime, support response times and measurable SLAs for log exports and deletions.
• Audit rights allowing you to commission an independent security or privacy audit annually (scope limited for IP protection).
• Right to freeze model updates and an agreed rollback/escape clause for safety/regulatory reasons.
• Indemnities and limitation of liability that cover data breaches, IP infringement and regulatory penalties resulting from vendor negligence.
• Transition and escrow clauses that ensure data and models can be ported on termination, including an export format and transitional support (see guidance on handling provider migrations: migration playbooks).

How to score vendors: a simple procurement checklist

Use a weighted scoring model to make decisions transparent. Below is a recommended weight allocation (adjust to your firm’s priorities):

• AI provenance & explainability — 25%
• FedRAMP / certifications & audit evidence — 20%
• Data residency & segregation controls — 20%
• Audit logs & eDiscovery support — 15%
• Change management & update controls — 10%
• Commercials, SLAs and contractual protections — 10%

Score each vendor 0–5 for every category, multiply by weight and compare totals. Prioritise vendors with clear, verifiable artifacts over those that promise future remediation.

Real‑world examples and 2025–2026 trends

Late 2025 saw several enterprise moves signaling what procurement teams should expect in 2026. Vendors acquiring FedRAMP approvals or announcing enterprise‑grade AI controls made headlines; for example, some AI vendors repositioned themselves after acquiring FedRAMP‑approved platforms to support government and regulated customers. These moves accelerated buyer expectations: organisations now routinely ask for FedRAMP/ISO/SOC attestation and detailed AI provenance in initial RFIs.

“Vendors are realising that FedRAMP and model provenance aren’t just for governments — they’re procurement table stakes for regulated commercial customers.”

Additionally, model provenance tooling (watermarking, model cards) matured in late 2025 and continues to be adopted in 2026. Expect vendors to supply machine‑readable provenance metadata and independent attestations as default evidence.

Red flags, hard stops and escalation steps

Be prepared to stop procurement if any of these apply:

• No audit logs or inability to export prompt/output history.
• Refusal to provide clear data residency commitments or insistence on global processing without options to pin data.
• Vague model provenance claims with no model card, lineage artifact or third‑party attestation.
• No contractual right to pause or roll back model updates for critical environments.
• Refusal to provide redacted SOC 2/ISO evidence or to allow limited independent audits.

If you hit a red flag, escalate to your Information Security Officer and legal counsel. Suspend pilot work and require a remediation plan with concrete milestones and independent verification.

Practical procurement timeline and responsibilities

Keep procurement fast but thorough. Here’s a sample 8‑week timeline for a mid‑sized firm:

1. Week 1: RFI + questionnaire issued to shortlisted vendors.
2. Week 2–3: Vendor responses reviewed by procurement, security and legal; request missing artifacts.
3. Week 4: Tech deep‑dive and staging access; initial security review.
4. Week 5: Compliance and privacy team review (DPA, SCCs, retention).
5. Week 6: Pilot with production‑like data in a pinned region; collect logs and evidence.
6. Week 7: Contract negotiations (SLA, audit rights, termination/transition clauses).
7. Week 8: Final sign‑off or remediation hold with a go/no‑go decision.

Assign clear roles: Security (technical artifacts), Legal (contract clauses), Privacy (data residency & DPA), IT (integration), and Practice Lead (usability & risk tolerance).

Actionable takeaways — what to do today

1. Update your standard security questionnaire with the AI provenance, FedRAMP and audit log sections above.
2. Require machine‑readable provenance metadata and exportable tamper‑evident logs as baseline deliverables.
3. Insist on contractual rights to freeze model updates and independent audit rights in your DPA/SLA.
4. Use the weighted scoring model and stop procurement if core proofs (logs, regional tenancy, model lineage) are missing.
5. Run a 2‑week staged pilot in a pinned region before deploying any AI tool on client matter data.

Future proofing: what to expect in 2026 and beyond

Expect three durable shifts this year:

• Standardisation of model provenance: regulators and industry groups will push for machine‑readable model cards and output provenance metadata as a procurement requirement.
• Enterprise‑grade authorisations: more AI vendors will seek FedRAMP/ISO/SOC attestations; procurement will treat those as differentiators.
• Greater contractual control: customers will demand rights to pin model versions, require revalidation, and secure audit & export rights — vendors will include these as optional enterprise tiers.

Final checklist (copyable)

• Obtain model card + lineage for all AI components.
• Verify FedRAMP/ISO/SOC reports and request SSP/POA&M where appropriate.
• Confirm data residency, export, and deletion SLAs in writing.
• Require detailed, tamper‑evident audit logs (prompt/output/model/version/user/timestamp).
• Include contractual rights: update freeze, independent audit, transition support.
• Run a production‑like pilot in a pinned region before rollout.

Closing thoughts

Procurement in 2026 is no longer just price and features. For solicitors and small law firms handling sensitive client data, the deciding factors are transparency, traceability and contractual enforceability. Ask vendors precise questions — demand evidence — and insist that answers are backed by auditable artefacts. Doing so protects your clients, reduces regulatory and litigation risk, and keeps your firm competitive when AI becomes integral to legal work.

Call to action

Need a tailored vendor questionnaire or a procurement review for a specific AI tool? Contact solicitor.live to get a custom evaluation pack and a 30‑point security checklist that you can use in your next RFP. Protect your clients — and your firm — before the next contract is signed.

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