For Solicitors & Law Firms

AI in legal work
carries real
professional risk

If your firm uses AI for document review, client communications, or research — and you serve Arabic-speaking clients — the liability exposure may already exist. We identify it before it becomes a complaint.

Get a Free Snapshot Report See the risks →
Live risk findings — bilingual legal AI
Critical
Contract clause omission — Arabic output dropped a limitation of liability clause present in the English source
Critical
Client identity confusion — AI addressed English-language client as male; Arabic-language client as female for the same query
High
Legal term mistranslation — "without prejudice" rendered incorrectly in Arabic, altering implied meaning
High
Regulatory reference gap — SRA guidance cited in English; absent from Arabic response to identical query
Findings from real evaluations — not hypotheticals

You are professionally responsible for AI outputs given to clients. A tool that performs accurately in English may produce materially different — and legally significant — results in Arabic. Independent evaluation is how you document that you checked.

Risk scenarios

Six ways bilingual AI creates legal exposure

These are not theoretical. They are categories of failure we identify in client systems across legal, financial, and compliance settings.

Critical risk
Clause omission in translation
AI systems summarising or responding to contracts may omit entire clauses when generating Arabic output — not because the clause was absent, but because the model's multilingual training weighted it differently.
Example pattern

English output includes indemnity cap at £500k. Arabic output for the same query omits the cap entirely. Client reads the Arabic version.

Critical risk
Regulatory reference asymmetry
A query about a legal matter in English may return references to applicable SRA codes or GDPR obligations. The same query in Arabic returns a substantively different — often shorter — response that omits those references.
Example pattern

English client is told about mandatory disclosure obligations. Arabic-speaking client receiving the same AI-assisted advice is not.

High risk
Legal term mistranslation
Common English legal phrases — "without prejudice", "on notice", "best endeavours" — do not have direct Arabic equivalents. AI systems often produce translations that carry materially different legal meanings.
Example pattern

"Without prejudice" translated as "بدون تحيز" (without bias) — a different concept with no legal protection implication in Arabic legal contexts.

High risk
Cultural deference affecting advice tone
AI models trained on Arabic text learn patterns of cultural deference. In legal contexts, this can cause the system to soften advice, avoid direct statements of risk, or frame obligations as suggestions when addressing Arabic-speaking users.
Example pattern

English response: "You must respond within 14 days or face default judgment." Arabic response: "It may be advisable to consider a response at your convenience."

Elevated risk
Inconsistent client identity handling
Bilingual AI systems may handle gendered language, honorifics, and client address forms inconsistently across languages — producing communications that feel culturally careless or are factually wrong about the client's identity.
Example pattern

A female client receives a correctly addressed English letter but an Arabic letter using masculine grammatical forms throughout.

Elevated risk
Jurisdictional conflation
When users write in Arabic, AI systems may draw on legal knowledge from Gulf or MENA jurisdictions rather than English law — producing responses that reference the wrong legal framework entirely.
Example pattern

Arabic query about employment termination returns guidance based on UAE Labour Law, not the Employment Rights Act 1996 that actually applies.

Our process

How an evaluation works

We assess your AI system against the specific legal scenarios and client types it encounters. Everything is documented, independent, and delivered in a format your PI insurer or regulator can review.

01
Scoping call — 30 minutes
We map the AI tools your firm uses, which practice areas they touch, and what languages your client base requires. This defines the test scope.
02
Scenario design — legal context
We design evaluation prompts drawn from real legal scenarios relevant to your practice — contracts, correspondence, compliance queries, client communications — in both English and Arabic.
03
Independent evaluation
We run structured tests against your system, scoring for accuracy, legal consistency, cultural appropriateness, and language parity. All findings are evidence-based with direct output examples.
04
Report — structured findings
You receive a written report documenting risk classification, specific failure examples, the gap between English and Arabic performance, and prioritised remediation recommendations.
05
Debrief and guidance
We walk through findings with the relevant person at your firm — managing partner, risk officer, or IT lead — and confirm next steps. No obligation to engage further.
Sample report extract
English response accuracy 94% — PASS
Arabic response accuracy 31% — FAIL
Legal clause parity 2 / 7 items matched
Regulatory reference parity Partial — 3 gaps
Cultural tone appropriateness Issues detected
Overall verdict NOT APPROVED

Critical risk identified: material clause omission in Arabic contract summary. Arabic-speaking clients may receive legally incomplete information.

Why this matters now

The regulatory direction is clear

The SRA has signalled that firms using AI must be able to demonstrate how they verified it was fit for purpose. Independent evaluation creates that paper trail.

63%
of UK law firms using AI tools are using them for client-facing work or communication
400k+
Arabic-speaking residents in the UK, many of whom require bilingual legal services
3–5×
performance gap between leading AI systems on English vs. Arabic legal tasks in our evaluations
Zero
of the AI vendors we have evaluated proactively disclosed their Arabic performance limitations to clients
"
The question is not whether you are using AI. The question is whether you can demonstrate that you took reasonable steps to verify it was suitable for the clients it was serving — in the language they were served in.
Dalīl Group — Evaluation principle for legal AI deployments
What you receive

Documentation your firm can use

Our reports are written to be understood by a managing partner, reviewed by a risk committee, and referenced in a regulatory response if required.

Written Evaluation Report
A structured PDF report classifying all identified risks, with direct evidence — actual AI outputs compared side-by-side in English and Arabic. No jargon. Suitable for non-technical partners.
PDF deliverable
Risk Register Extract
A formatted risk log you can insert directly into your firm's existing risk register — with risk owner, severity, likelihood, and recommended control for each finding.
Risk management
Remediation Recommendations
Prioritised, actionable steps — covering system prompting, vendor escalation, human review protocols, and when a system should not be used for Arabic-speaking clients until issues are resolved.
Actionable
Questions

What firms usually ask

No. We design evaluation scenarios based on the types of matters and client queries your system handles. We do not require access to actual client files, communications, or personal data. Our scenarios are crafted to reflect your context without using real client information.
Yes. Most of our evaluations are of third-party tools — off-the-shelf AI writing assistants, legal research platforms, or chatbot products integrated into firm workflows. We assess the system as your clients and fee-earners experience it, not as the vendor designed it.
We have no commercial relationship with any AI vendor. We do not resell, integrate, or receive referral fees from any AI product. Our revenue comes entirely from evaluation engagements. That independence is the basis on which you can use our report externally — it cannot come from a vendor self-assessment.
A Readiness Assessment takes 5–7 working days from scope confirmation. A full Bias & Reliability Audit takes 10–14 working days. Both include a debrief call. Timelines are confirmed in the engagement agreement before work begins.
Yes. We offer a Free Snapshot Report — a real evaluation of one scenario from your AI system, delivered as a formatted report. It costs nothing, requires no commitment, and gives you an accurate sense of our methodology and output quality. Mention "Free Snapshot" when you book an intro call.
The Free Snapshot is at no cost. A Readiness Assessment is £1,500. A full Bias & Reliability Audit is £3,500. High-Trust Pilot support is priced on application. All fees are fixed — no hidden extras. See our Pricing page for full details.
Start here

Start with a free evaluation of one scenario

We run one test from your AI system, document what we find, and send you a formatted report — at no cost and with no obligation. Most firms find that sufficient to make a decision about what to do next.

Request Free Snapshot Report View pricing →

Mention "Free Snapshot" in the enquiry form. No payment details required.