When AI Climbs the Legal Stack: How Agentic Models Are Rewriting Law Firm M&A Strategy

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The Market Just Spoke

This week, Anthropic’s release of a legal plugin for its Claude Cowork platform erased £285 billion from legal software and publishing stocks in a single trading session . Thomson Reuters, owner of Westlaw, fell 19%. RELX, parent of LexisNexis, dropped 15%. LegalZoom plummeted 18%.

This is not a routine product launch. It signals that the large language model providers—until now content to power the legal tech stack—have begun climbing it. The implications for UK law firms, particularly those contemplating mergers or acquisitions, are profound and immediate.

What This Tool Actually Does

The Claude legal plugin is an agentic AI capability, not a chatbot. It operates with user consent to execute multi-step legal workflows: contract review clause-by-clause against configured playbooks, NDA triage with GREEN/YELLOW/RED flagging, compliance tracking, and templated response generation . Unlike previous AI tools that required lawyers to copy-paste outputs between systems, Cowork accesses document folders directly, executes tasks, and reports back.

Crucially, it is customisable. A firm can encode its own negotiation positions, escalation triggers, and risk tolerances into a local configuration file. The AI then applies that firm’s specific playbook, not generic commercial standards .

Why This Matters for M&A Strategy

I have spent three decades advising law firms on combinations. The due diligence questions we ask are about to change fundamentally.

Valuation of Target Firms

When we assess a target firm’s goodwill, we have traditionally examined WIP ageing, client concentration, and partner retainer rates. We must now add a fourth pillar: AI readiness.

A firm with documented playbooks, structured data, and digitised workflows will extract exponentially more value from tools like Claude Cowork than one operating on institutional memory and precedents scattered across personal drives. In an acquisition context, this gap represents hidden value—or hidden liability.

Consider two £5 million regional firms. Firm A has contract playbooks maintained in a central repository, standardised document templates with embedded metadata, and a clear data governance framework. Firm B has excellent lawyers but operates on ad-hoc processes and partner-specific styles. Post-merger, Firm A’s infrastructure can be AI-augmented within weeks. Firm B requires months of process documentation before AI tools can be safely deployed. That difference now materialises in the purchase price.

The Due Diligence Checklist

Effective immediately, we are adding the following to our standard acquirer due diligence protocols:

  • Playbook Inventory: Does the target firm have documented standard positions for routine contract types? Are these codified or tacit?
  • Data Architecture: How is precedent knowledge stored? Is it extractable, or trapped in unstructured documents?
  • Technology Debt: What is the cost of migrating the target’s workflow data into AI-compatible formats?
  • AI Risk Exposure: Has the target firm deployed unauthorised AI tools? Do they have client consent frameworks for AI-assisted work?

Sellers should prepare for these questions. Buyers should not complete a transaction without answers.

Integration Planning Reimagined

The first 100 days of a merger, which we detailed in our recent tactical playbook, now require an AI acceleration track.

Pre-merger, most firms focus on harmonising financial systems and partner compensation structures. Post-Claude Cowork, the priority shifts to unified knowledge management. If two firms merge but maintain separate precedent collections, AI tools cannot operate effectively across the combined entity. The merged firm will function at the speed of its slower, less structured half.

We now recommend that integration planning include an “AI readiness sprint” between announcement and completion. This sprint identifies which legacy firm’s systems, processes, and data structures will serve as the baseline for AI deployment post-merger. Attempting to merge two distinct AI configurations post-completion is technically possible but operationally costly.

Strategic Positioning: Build, Buy, or Configure

The legal AI market is bifurcating. At one end, general-purpose platforms like Claude Cowork offer configurable but undifferentiated capabilities. At the other, specialist tools like Harvey and Legora provide legal-specific workflows, market data integration, and regulatory safeguards .

For most UK firms below the top 50, the economics favour configuration over custom development. The Claude plugin is available now to all paid Claude users. It requires no technical implementation team, no API integration, and no capital expenditure beyond the subscription fee . This democratises access to capabilities that, six months ago, required six-figure software investments.

However, configuration is not strategy. Firms that deploy these tools without first documenting their own intellectual capital— their unique approaches to negotiation, their market positioning, their client service standards—will produce faster but undifferentiated work. The competitive advantage lies not in using AI, but in what you teach it about how you practise law.

The Regulatory Dimension

The SRA has not yet issued specific guidance on agentic AI tools. The Anthropic legal plugin includes a disclaimer that outputs should be reviewed by licensed attorneys and that the tool does not provide legal advice . This is prudent but insufficient.

Firms deploying these tools must establish clear protocols for human oversight, particularly where AI-generated outputs affect client risk exposure. The Legal Services Act requirements regarding competent delivery of services and client confidentiality apply regardless of whether a task is performed by a trainee, a partner, or an AI agent.

In merger contexts, this creates integration risk. If one legacy firm has deployed AI-assisted review processes and the other has not, the combined firm must establish unified standards before client work commences. Failure to do so creates regulatory exposure and professional indemnity complications.

The Talent Implication

Every technological shift in legal practice reallocates value between roles. The precedent-based work that occupied junior associates for decades—document review, due diligence verification, contract first drafts—is precisely what these tools automate efficiently.

This does not eliminate the need for junior lawyers. It elevates the threshold for what constitutes valuable training work. Firms that deploy AI for routine tasks must redesign their associate development programmes to provide meaningful, skill-building work that cannot be automated. Firms that fail to do so will find their training contracts uncompetitive and their partnership pipelines depleted.

In M&A contexts, this affects talent retention. A target firm’s associates may have accepted lower compensation in exchange for high-quality training opportunities. If post-merger AI deployment eliminates those opportunities without replacing them with equivalent developmental work, retention assumptions in the merger model prove optimistic.

Immediate Actions

For firms actively transacting or contemplating transactions, I recommend the following immediate steps:

  1. Audit your own AI readiness before examining a target’s. You cannot diligence what you do not understand.
  2. Insert AI provisions into sale and purchase agreements. Consider representations regarding data governance, AI tool deployment, and client consent frameworks. Warranties should cover undisclosed AI-related liabilities.
  3. Model AI-driven synergies conservatively. The productivity gains from these tools are real but not immediate. Implementation requires training, configuration, and cultural adaptation. Do not bank deal economics on six-month payback periods.
  4. Secure external expertise. Most law firm management teams have not previously evaluated agentic AI tools. Your traditional IT advisors may lack relevant experience. Engage specialists who understand both the technology and the specific operational constraints of legal practice.

A Final Observation

The legal technology market has experienced hype cycles before. This is different. When major AI providers move from supplying infrastructure to owning workflows, they alter the competitive landscape permanently .

For UK law firms, the strategic imperative is clarity of purpose. AI tools will not replace lawyers. They will, however, replace law firms that fail to integrate these capabilities into coherent service delivery models. Mergers and acquisitions remain the most efficient mechanism for achieving scale, geographic reach, and capability expansion. But the firms that thrive in this environment will be those that treat AI readiness as a core diligence criterion and integration priority—not as an afterthought to be addressed after the partners have reconciled their billing rates.

The market disruption we witnessed this week is not a threat to the legal profession. It is an accelerant for the separation of firms that have invested in scalable, documented, technology-enabled processes from those that have not. For acquirers and targets alike, the time to address that gap is before the transaction completes, not after.

For those Managing Partners seeking to develop a broader AI strategy beyond immediate M&A considerations, I am also able to introduce you to our dedicated AI consulting partners, who are advising firms on implementation roadmaps, vendor selection, and governance frameworks tailored specifically to the UK legal market.

I welcome the opportunity to discuss how these developments affect your specific strategic positioning.

Andrew Roberts
Managing Director, Ampersand Legal

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