🤖 Copilot legal skills · 📋 Client AI duty · 💷 $8.8bn Legora

Microsoft has just put 20-odd legal skills into the software your firm already pays for, and the Law Society of England and Wales now expects you to tell clients when AI touches their matter. California has gone further and turned citation-checking into a statute with your name on it. This week: what shipped, what it costs, and the parts of the demo nobody records.

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⚖️ The duty

Two jurisdictions moved the line this week: one by guidance, one by statute. Both proceed on the assumption that the lawyer, not the model, signs the work.

📋 Law Society: tell clients how you are using AI

A 58-page practice note from the Law Society of England and Wales says solicitors should give clients appropriate information about their AI use, and can ask clients to disclose AI-generated material passed on to them. Paid tools face the same scrutiny as free chatbots: terms of service, how data is stored and shared, where the provider operates, and whether the tool knows your jurisdiction. The sharpest line: an AI system cannot reliably validate its own results, so relying on AI to verify AI outputs will not satisfy your professional obligations. This is guidance, not a new rule — but it is now what the profession's body says it expects.

Source: Law Gazette

⚖️ California from 2027: check every citation, then disclose the AI

SB 574, signed on 30 September, takes effect on 1 January 2027 and adds a personal citation-verification rule for California filings plus a set of AI duties, including disclosure of generative AI use to the court. Fabricated citations were already sanctionable; the change is that verification is now statutory, and longstanding language in the sanctions statute makes firms jointly liable for their lawyers absent exceptional circumstances. The unsettled part will matter to litigators: whether the rule reaches citations to the factual record, and whether AI-assisted review upstream of a brief triggers disclosure. Arnold & Porter's advice is to pick a firm-wide position before a judge picks one for you.

Source: Arnold & Porter (eData Edge blog)

🌍 Master of the Rolls: English law's edge may not survive the LLMs

In a valedictory speech, Sir Geoffrey Vos warned that England and Wales' status as the jurisdiction of choice for commerce is not guaranteed once AI mediates the work: the law baked into dominant LLMs, most of them domiciled in the US or China, will be a starting point at least. He promised a new statement on the legal status of agentic AI and flagged continuing LawtechUK taskforce work on digital documentation. This is an argument from a retiring senior judge, not a ruling — but it tells you where the judiciary thinks the competitive risk sits.

Source: Law Gazette

🛠️ What shipped

The connector stories belong together: research, case facts and governed workflow records all arriving inside the platform lawyers already work in.

🤖 Microsoft ships 20+ legal skills for Copilot — and lifts the bar for specialists

Microsoft has added more than 20 purpose-built legal skills to Copilot: first-pass contract review, drafting and proposed redlines through tracked changes in Word, plus obligations tracking and cross-agreement comparisons in Copilot Cowork. Partners are being announced thick and fast — Harvey, Legora, DeepJudge, Bloomberg Law, iManage, Relativity among them — as plugins that will be accessible through Copilot, so treat availability as rolling rather than shipped. A Clyde & Co consultant's question is the one for your next renewal: what can a specialist do that Microsoft cannot, and is the difference worth another platform, another integration and another invoice? Microsoft's own counsel says an hour of first-pass review can drop to minutes, which is a vendor anecdote, not a measured result.

Source: The Global Legal Post

🔎 Protégé answers with your case facts attached

The LexisNexis–EvenUp integration announced in September is live. Inside EvenUp's Companion, a lawyer can call LexisNexis Protégé and get an answer grounded in Lexis case law and statutes that already has the facts of the matter attached. In a walkthrough run by both companies, a Florida permanent-injury threshold question came back with the statutory thresholds applied to that plaintiff's injuries; each statement carried a linked citation, and the authority list underneath carried Shepard's signals. Worth knowing before you take a trial: RELX's venture arm is an EvenUp investor. The gaps are as instructive as the feature — drafting over the connection and the reverse trip from Protégé back into EvenUp are still roadmap, and you need subscriptions to both products.

Source: LawSites / LawNext

🧩 Autologyx connector lets Harvey write back into governed workflows

Autologyx's MCP connector is live in Harvey's Connector Library, letting users read and update workflow records, documents and tasks, and — with the right permissions — create records that trigger existing governed processes. Mary Technology also announced an integration the same day, bringing its factual investigation work into Harvey so a team's earlier findings on the evidence travel with the matter instead of sitting in another tab. The pitch is that AI should act inside your processes rather than beside them. Only Autologyx is described as available; permissions and audit behaviour are vendor-stated, and that is precisely where firms will test it.

Source: Legal IT Insider

📚 Research inside the drafting window: Harvey connects to Midpage

The Midpage connector is live in Harvey's Connector Library, putting US case law, statutes, regulations and agency materials inside Harvey Assistant threads, with cited sources in the output. The vendor's own use cases are the honest ones: pull authority into a research memo, find supporting passages while drafting, and check that the authorities you cited exist and support the point. Both subscriptions are required. And the citation check still ends with a human opening the case — the connector speeds up finding, not judgment.

Source: LawSites / LawNext

🧭 The workflow

Governance sold as a service, and a talent pipeline that starts before law school ends.

🧭 Goodwin turns AI approvals into a product

Goodwin AI Governance bundles the firm's judgement into a programme with three moving parts: routine AI uses keep moving under current guidance, exceptions get an answer from a lawyer, and those answers become the rule next time. It targets boards and private equity portfolios, where the governance questions differ from a single operating company's. The framing rests on a Deloitte figure Goodwin quotes — 74% of organisations plan to deploy AI agents within two years, 21% have a mature governance model — which gives the gap a number if not a client. This is an announcement with no implementation detail or outcomes; the approval-queue bottleneck it describes will still be familiar.

Source: Goodwin

🎓 Weil will pay law students to build AI for two summers

From 2027, Weil's two-summer programme puts first-year students with its LASER engineering and research team for 10 weeks on live matters — building legal software, contributing to academic research on AI and law, and paid in line with Weil's summer associate programme in New York. Those accepted receive offers to return for the 2L summer in 2028. The chief AI officer's framing is deliberately unglamorous: the aim is not to make them engineers but to make them lawyers who ask better questions. There is no outcome data yet; the contrast with bolt-on training for existing associates is the point.

Source: The Global Legal Post

💷 The economics

A billing dataset, a valuation, and an argument about who pays for the queue.

🕰️ The billable hour persists: 48% of small and midsize firms bill only hourly

8am's SMB Law Billing and Payments Report, drawn from more than 60,000 firms on MyCase and LawPay, finds 48% bill entirely by the hour and only 10% entirely on flat fees, with 42% mixing the two. Total billings rose 5–8% a month in H1 2026 against H1 2025 while hourly rates held flat at every firm size except midsize, which raised them 4.3%, and hours per case barely moved. The driver was better capture of time already worked — 3–5% more earned per hour billed. The report reflects 8am's own customer base and says it is not representative of the whole US market. Still worth a look before you price AI efficiency into a fixed fee.

Source: ABA Journal

💷 Legora raises $550m at $8.8bn, seven months after the last $550m

Legora closed a $550m Series E at an $8.8bn post-money valuation, up from $5.6bn at its previous round in March, led by Atreides with Fidelity, Capital Group and J.P. Morgan joining the cap table. The company says annual recurring revenue went from $1m to $100m in under 18 months and now exceeds $200m, with more than 1,000 staff and 140,000 users at 2,400 firms — all company-supplied numbers. The money goes to US expansion and the agentic operating system. Call it conviction or call it a bubble; either way it is the balance sheet behind a platform plenty of firms have just standardised on.

Source: Legal IT Insider

🌊 Agentic flooding: when AI makes the queue longer, not shorter

Furlong argues AI has broken the equilibrium between the effort it takes to file a claim and the effort it takes to process one: longer, error-strewn submissions from people who would never previously have filed, landing at agencies and tribunals that must assess them. His fix is an AI intake filter with no decision-making power at all — summarise the claim, identify the issues, test it against verified rules, then hand it to a human. The agentic-flooding paper he cites examined 84 potential cases across 11 jurisdictions and does not assert causation. The diagnosis is still the useful part.

Source: Jordan Furlong (Substack)

💬 Community Spotlight

⚖️ California's AI disclosure: template it, or fight it?

A California practitioner asks what everyone with a January deadline is asking: does every filing now need an AI footnote? Most commenters think the statute largely restates existing duties, and several plan a blanket disclosure in the document template rather than adjudicating each use. A contract lawyer working with California firms reports two extremes — a footer reading 'generative AI may have been used in preparing this document', and a full ban on AI drafting for court documents with usage logs. The sharpest objection is structural: there is no safe harbour or good-faith standard, so nobody knows what counts as meaningful disclosure.

Dissent runs both ways. Some argue the requirement is performative because signing a filing already certifies it, and that the disclosure will become boilerplate nobody reads; others say the point is not that AI is dirty but that unverified output gets sanctioned. The definitional fog is practical rather than philosophical: Word, Grammarly and spell-check now all sit somewhere on the line, and several posters expect a few disciplinary cases before courts settle on standard wording.

Key Takeaways:

• Template it, don't adjudicate it: several firms plan a standing disclosure line in filing templates rather than deciding case by case.
• Two extremes reported: a footer saying AI 'may have been used', versus a ban on AI drafting for court documents plus usage logs.
• No safe harbour or good-faith standard — commenters expect a few disciplinary cases before courts settle on standard wording.
• 'Used to create content provided to the public' baffles practitioners: does discovery under a protective order count?
• The performative objection: signing a filing already certifies accuracy, so a mandatory disclosure risks becoming boilerplate nobody reads.

Source: r/LawFirm

💬 More from the community

📝 The checklist before you trust an AI contract summary

Pre-flight list from one practitioner: get the exact clause wording rather than a paraphrase, check the tool followed definitions and cross-references, and confirm it flagged what is missing — no limitation clause, no indemnity. The hardest part is verifying whether it found everything you asked for. A second model can raise questions, but agreement is not proof; the fix is a coverage log of what was checked and what still needs a human.

Source: r/legaltech

🎙️ The AI notetaker question nobody asks: what record are you creating?

Turning on an AI notetaker creates something that did not exist before: a verbatim, searchable transcript of every call, including the offhand 'I wouldn't put that in writing' moments. Once a dispute is foreseeable you usually cannot simply delete it, so retention must be decided before the pilot. The questions that matter: which meetings are excluded, how long transcripts live versus minutes, and who can delete.

Source: r/legaltech

📄 Document agents: great at 50,000 emails, lost on a bent fax

Commenters sort the problem by document type rather than by vendor: agents do well pulling names and dates out of 50,000 emails, and badly on scanned PDFs, handwritten marginalia, old faxes and anything half-sideways, where the model starts inventing page numbers. The practical takeaway is to route work by source quality instead of assuming one tool handles an entire collection — and to keep eyes on the messy end of it.

Source: r/LawFirm