Legal AI is moving fast in 2025. New tools promise speed and scale, yet firms still carry the same duties to clients. You need to protect privacy, cut risk, and pick tools that actually help fee earners.

This guide gives you 10 clear questions to ask any legal AI provider in first meetings, tenders, or pilots. It covers GDPR, security, accuracy, citations, bias controls, workflow fit, data ownership, costs, and support. Trends to watch this year include privacy by design with anonymisation, human in the loop for sensitive work, tight integrations with document and case systems, and independent security certifications like ISO 27001 or SOC 2 Type II. Use these questions as a simple checklist to compare vendors side by side.

Compliance, privacy, and security: protect clients and your firm

Strong compliance and security are non negotiable in legal work. You handle personal data, trade secrets, and case strategy. A slip puts clients, matters, and your reputation at risk.

For UK and EU firms, GDPR is the baseline. Cross border practices may also touch HIPAA or other sector rules. Look for clear data residency options, strong encryption, role based access controls, audit logs, backup, and disaster recovery. Good vendors show proof, not just promises. Bring your DPO or IT security lead in early so you do not miss hidden gaps.

Is your legal AI compliant with GDPR, and can you keep our data in the UK or EU?

Ask whether the vendor acts as a processor or controller. Request a Data Processing Agreement. Confirm you can keep data in UK or EU data centres, and ask how they handle cross border transfers.

• Ask for the lawful basis used for processing.
• Request a full list of sub processors.
• Check retention rules and how quickly they report incidents.

A strong answer includes clear residency choices, a signed DPA, named sub processors, and transparent transfer terms. Vague statements or refusal to sign a DPA are red flags.

How is client data protected at rest and in transit, and who can access it?

You want TLS for data in transit and AES 256 for data at rest. Ask about key management and who holds the keys. Check role based access control, least privilege, SSO, and MFA. You also need detailed audit logs.

• Confirm privileged access is limited and monitored.
• Ask how access is revoked when staff leave.
• Request diagrams showing the security model and data flows.

Strong vendors provide access reviews and proof of regular audits. You should see how they detect and respond to suspicious activity.

Which security certifications do you hold, and can we see recent audit reports?

Ask for current ISO 27001 and SOC 2 Type II reports. Ask about penetration testing, vulnerability scans, patching cycles, and third party checks.

• Can you view summary audit results under NDA?
• What was in scope and when was the last audit?
• What remediation plans are in place for findings?

A mature provider shares scope, dates, and plans without fuss. No independent audits, or expired certificates, create unnecessary risk.

What are your data retention, deletion, and training policies for our data?

Clarify default retention and secure deletion timelines. Ask how the right to be forgotten is handled. Check whether your prompts or documents are used to train models by default, and if you can opt out.

• Look for privacy by design and anonymisation where possible.
• Ask for configurable retention by matter type.
• Confirm deletion also covers backups within a stated window.

This protects clients and reduces regulatory headaches later.

Accuracy, transparency, and risk management: avoid errors and bias

Lawyers must trust outputs, check sources quickly, and defend their work if challenged. AI should help your judgement, not replace it. Focus on outcomes that matter in practice: citations to primary law, measured accuracy for common tasks, bias controls, and clear audit trails.

What sources power the AI, and are outputs reviewed by qualified lawyers?

Ask which legal databases, case law, statutes, and treatises inform the system. Check jurisdiction coverage and how often content is updated. For legal tasks like clause drafting or risk summaries, ask whether qualified lawyers review prompts, templates, or model behaviours.

• Good answers name authoritative sources and update cycles.
• High risk use cases should include human review before release.
• Ask for examples by practice area and jurisdiction.

This helps you judge whether the tool fits your matters, not just a marketing demo.

How do you measure accuracy and reduce hallucinations, and will you give citations?

Ask for task level metrics across research, summarisation, clause extraction, and drafting. You want known error rates and how they were validated. Retrieval augmented generation with citations to primary sources helps reduce made up claims.

• Request confidence scores and links to cited sources.
• Ask how the tool flags uncertainty or missing context.
• Red flags include no metrics or refusal to show how citations are produced.

If you cannot check the source trail in seconds, your lawyers will not trust it.

How do you handle bias, explainability, and full audit trails?

Bias creates legal and ethical risk. Ask how the provider tests for bias, what fairness checks they run, and how they reduce biased outputs. You also need explainability and a proper trail.

• Can the tool show why an answer was given and which sources were used?
• Do you get a full audit trail of prompts, versions, user, time, data accessed, and approvals?
• Are model and policy updates logged for review?

This protects you if questions arise later, and it supports internal quality control.

Integration, deployment, and total cost: fit your workflow and budget

A tool that sits outside your workflow will gather dust. You want smooth integration with document and case systems, SSO, simple user provisioning, and policy checks that match your firm.

Deployment choices, data isolation, and exit options matter as much as features. Be clear on pricing, onboarding, support hours, SLAs, and disaster recovery. Plan a short pilot with firm success measures so you can make a clear call.

How will the AI integrate with our document and case systems without heavy IT work?

Ask for native connectors or stable APIs for tools like iManage, NetDocuments, SharePoint, and your case management platform. Check SSO and MFA, and ask for SCIM for user management.

• Look for automatic tagging, version control, and policy enforcement.
• Request a sandbox and sample integrations.
• Ask for migration support so you do not tie up your IT team.

The best vendors reduce manual effort and fit into how your lawyers already work.

What deployment options exist, and how is our data isolated from other clients?

Compare SaaS, private cloud, and on prem options. Ask about single tenant or multi tenant, network isolation, and logical separation. Confirm that your data will not train shared models unless you opt in.

• Check data export formats and exit plans.
• Ask how quickly they can purge your data on exit.
• Request a walkthrough of isolation controls and monitoring.

You should be able to leave cleanly, with your data intact and no lock in.

What does pricing include, and what support and SLAs do we get?

Clarify how pricing works, whether by user, document, or usage. Ask about overage fees. Confirm what onboarding includes, time to go live, and training for fee earners and support staff.

• Get uptime targets, support hours in UK time, and response times.
• Ask for disaster recovery RPO and RTO.
• Check how model updates are rolled out and how changes are communicated.

Look for a clear roadmap, a named account manager, and practical guidance on safe use.

Quick comparison checklist

Use this simple table to line up vendors side by side.

Area	What to ask for	Evidence to expect
GDPR and residency	DPA, UK or EU data options, transfer terms	Signed DPA, list of sub processors, SCCs
Security controls	TLS, AES 256, RBAC, SSO, MFA, audit logs	Diagrams, access reviews, audit snapshots
Certifications	ISO 27001, SOC 2 Type II, test cadence	Recent reports, pen test results, remediation
Retention and training	Configurable retention, deletion, opt out of training	Policy docs, backup deletion window
Sources and coverage	Jurisdictions, updates, human review	Source list, update schedule, reviewer details
Accuracy and citations	Metrics, RAG, confidence, error rates	Benchmarks, sample outputs with citations
Bias and explainability	Bias tests, traceability, audit trail	Reports, logs, change history
Integration	Connectors, APIs, SSO, SCIM, sandbox	Live demo in your stack, pilot environment
Deployment and isolation	SaaS, private, on prem, isolation model	Architecture overview, export and exit plan
Support and SLAs	Onboarding, training, uptime, UK hours	SLA document, roadmap, named contacts

Conclusion

Choosing legal AI is easier when you ask the right questions. Focus on compliance, accuracy, workflow fit, and the true cost of running the tool. The best providers share evidence, not just claims, and they support human oversight on sensitive work.

Next steps: shortlist three vendors, run a 30 day pilot with clear success criteria, involve IT, risk, and your DPO, then capture lessons learned. Create a simple scorecard using the 10 questions and score each answer with proof attached. You will make a fair call, protect clients, and pick a tool your lawyers trust.