Baker McKenzie's AI Strategy: How the World's Largest Law Firm Is Rethinking Client Intake

TL;DR#

Baker McKenzie AI is one of the most mature programs in the legal industry: the firm adopted a formal AI strategy in 2017, launched an AI-first machine-learning practice (BakerML, now Applied AI) in 2021 under founder Danielle Benecke, and in May 2026 began a phased rollout of the legal AI platform Legora to lawyers across a network the firm describes as more than 3,500 lawyers in 74 offices across 41 countries. Its innovation arm, Reinvent, led by Chief Innovation Officer Ben Allgrove, runs an exclusive collaboration with data-science company SparkBeyond and pursues what Allgrove calls a "multi-model, multi-vendor" approach to generative AI. Yet almost every publicized use case sits inside the lawyer's workflow — document review, legal research, drafting, and data extraction — not at the client's front door. The overlooked frontier for BigLaw AI client intake is the first conversation: how a prospective client and a new matter enter the firm. That first touch is still dominated by web forms, email, and phone, the very channels industry research shows leak the most prospects. Conversational AI intake is the modernization step even the world's most AI-forward firms have not yet taken. This is where a tool like Perspective AI's conversational intake captures the context a static form never asks for.

Who Baker McKenzie Is: Scale and Global Footprint#

Baker McKenzie is one of the largest law firms in the world by headcount and revenue, built on a genuinely global model rather than a single-country base. Founded in Chicago in 1949, the firm today operates as a Swiss Verein with, by its own May 2026 account, more than 3,500 lawyers working out of 74 offices in 41 countries — and industry rankings have repeatedly placed it among the very largest firms globally, with gross revenue in the multibillion-dollar range. Unlike New York- or London-anchored elite firms, Baker McKenzie's defining characteristic is geographic reach: cross-border transactions, multinational tax and employment work, and disputes that span jurisdictions.

That scale is exactly why the firm makes such a useful case study. Coordination across dozens of jurisdictions is Baker McKenzie's central operating challenge, and it is also the problem AI is best suited to attack — which is why the parts of the client relationship it has not yet automated are so instructive for the rest of the profession.

Baker McKenzie AI Strategy: A Decade of Legal Innovation#

Baker McKenzie's AI strategy is best understood as a decade-long compounding investment, not a reaction to the 2023 generative-AI boom. The firm has said its AI journey began in 2016, when it positioned itself early on the implications of machine learning for legal work, and it became one of the first global law firms to put a formal AI strategy in place in 2017. That early start is the through-line connecting every subsequent move.

The program runs through Reinvent, Baker McKenzie's innovation arm, led by Partner and Chief Innovation Officer Ben Allgrove. In 2021 the firm launched BakerML, an AI-first machine-learning practice founded by Danielle Benecke that brought lawyers, data scientists, and data engineers into one team; it has since been renamed Applied AI. Through Reinvent, the firm also struck an exclusive collaboration with data-science company SparkBeyond, focused on three areas: AI-powered legal services, machine-learning-driven pro bono and social-impact research, and using data insights to improve the firm's own internal operations.

Allgrove has publicly framed the philosophy as disciplined rather than hype-driven, describing the generative-AI approach as "multi-model and multi-vendor" to preserve agility as models and client demand change. That posture puts Baker McKenzie in the company of other global and elite firms building deliberate programs — a pattern documented across the market in the six data-backed shifts in law-firm AI adoption and mirrored by peers such as Kirkland & Ellis's client-intake AI strategy and Latham & Watkins's generative-AI deployment.

Where Baker McKenzie Has Deployed AI#

Baker McKenzie has deployed AI overwhelmingly inside the practice of law — the lawyer's own workflow — rather than at the client-facing edges of the firm. The clearest signal came in May 2026, when the firm announced a phased rollout of the legal AI platform Legora across six global practice groups: transactional; banking and finance; tax; dispute resolution; employment and compensation; and commercial. The firm named the initial use cases explicitly: large-scale document review and data extraction, document comparison and targeted search, multi-document editing, drafting and redlining, and checklist preparation.

To support adoption, Baker McKenzie layered in a flagship AI Accelerator Program — an intensive, in-person program for high-performing associates and counsel — and created a new Practice Innovation Lawyer role inside each global practice group. On the recognition side, an Applied AI–built tool that automates data-breach-notification analysis won "Best Use of AI" at the 2025 Legalweek Leaders in Tech Awards.

The firm has also been candid that AI is changing its cost structure. In early 2026, Baker McKenzie announced it would reduce a portion of its global business-services workforce — reported at up to roughly ten percent, an estimated 600 to 1,000 roles across know-how, research, marketing, and secretarial functions in London, Belfast, and offshore centers — and cited its increased use of AI as one factor, though legal-press commentators cautioned the picture is more complicated than AI alone. The reductions were reported not to affect attorneys.

Notice the pattern: every one of these initiatives points inward — document review, research, drafting, breach analysis, back-office efficiency. That is where value has been easiest to prove, and it leaves one high-value surface almost untouched.

The Overlooked Frontier: BigLaw AI Client Intake#

The frontier Baker McKenzie — and nearly every large firm — has not yet modernized is client and matter intake: the very first conversation with a prospective client. Intake is still run through web forms, "contact us" pages, general inboxes, and phone calls, and the data on how those channels perform is unflattering even for the most sophisticated firms. Independent research summarized by the American Bar Association's own Law Practice Magazine analysis of client intake and by widely cited secret-shopper studies is stark: a large share of email inquiries to law firms go unanswered, the average firm can take dozens of hours to respond to a web-form submission, and conversion odds fall sharply — by more than 70% in some analyses — when a lead waits more than five minutes for a first response.

For BigLaw AI client intake, the miss is not just speed — it is depth. A prospective corporate client rarely arrives with a clean, categorized request. They arrive with a situation: a cross-border acquisition with an unresolved tax question, a regulatory inquiry in three jurisdictions, an employment matter with reputational stakes. A static form asks for a name, a company, and a checkbox practice area. It cannot ask "what's driving the urgency?", it cannot surface a potential conflict early, and it cannot capture the scope and jurisdictional nuance that determine which partner should even see the matter. The firm has poured a decade into understanding documents with machine intelligence while the first human-to-firm exchange still runs on a form built for 2009.

This is the same gap other firms are now naming out loud. It shows up in why legal intake software is costing firms cases, in the shift from PDF intake forms to AI conversations, and in how global firms like DLA Piper are approaching AI legal intake. The macro backdrop reinforces the opportunity: Thomson Reuters' 2025 Generative AI in Professional Services report found that 26% of legal organizations were actively using generative AI, up from 14% a year earlier, with the large majority of professionals expecting it to become central to their workflow within five years. Adoption is accelerating — but it is concentrated on document work, leaving intake as open ground.

Why Conversational Intake Fits a Global Firm#

Conversational AI intake fits a firm like Baker McKenzie precisely because its problem is coordination across scale, and a conversation scales in a way a receptionist cannot. Instead of routing every prospect to a form or a general line, a conversational intake agent can conduct a structured but natural first interview — in the prospect's own words, at any hour, in any time zone — then capture and route the result to the right practice group.

Here is how the two models compare for a firm operating across 41 countries:

The mechanism matters more than the channel. What makes a conversation better than a form is follow-up: the ability to hear "we're being acquired and there's a data-privacy issue" and ask the next three questions automatically. That is the same capability Perspective AI built for customer interviews — an AI interviewer that probes and follows up — applied to the front door of a firm through a concierge agent that replaces the intake form. The analogy extends beyond legal: regulated industries are attacking the same "capture the context a form misses" problem, from Ethos and the AI life-insurance interview to Coalition's conversational security assessment for cyber insurance. Underwriting risk and qualifying a legal matter are both discovery problems, not data-entry problems.

What Other Large Firms Can Learn from Baker McKenzie#

The lesson from Baker McKenzie's AI strategy is that maturity on the practice side does not mean maturity on the client side — and the client side may be the higher-leverage place to move next. Three takeaways generalize:

1. Start early and compound. Baker McKenzie's advantage is not a single tool; it is nine years of governance, talent, and a multi-vendor posture that lets it swap models without re-architecting. Firms building a program now should invest in the operating model, not just the license.
2. Don't confuse internal efficiency with client experience. Automating document review lowers cost. Modernizing intake grows the top line — every unanswered inquiry is a matter that walked to a competitor. The two are different projects with different owners.
3. Treat intake as discovery, not data entry. The firms pulling ahead are reframing the first conversation as a qualification interview. That is the throughline in Skadden's conversational client discovery, in Reed Smith's GravityStack innovation model, and in the broader playbook for qualifying leads without losing the human.

For firms designing this from scratch, the practical starting point is the intake conversation itself — a topic covered in depth in how to design a client intake process that doesn't lose clients and echoed in how BigLaw is deploying AI at the delivery layer.

Frequently Asked Questions#

What is Baker McKenzie's AI strategy?#

Baker McKenzie's AI strategy is a decade-long, firm-wide program that began around 2016 and was formalized in 2017, making it one of the first global law firms to adopt an explicit AI strategy. It runs through the firm's Reinvent innovation arm and its Applied AI practice (formerly BakerML), pursues a deliberately "multi-model, multi-vendor" approach to generative AI, and in 2026 expanded to a phased rollout of the Legora platform across its practice groups.

Which AI tools does Baker McKenzie use?#

Baker McKenzie uses a mix of internally built tools and third-party platforms rather than a single system. Publicly, it deploys the legal AI platform Legora for document review, data extraction, drafting, and redlining; runs an exclusive data-science collaboration with SparkBeyond through its Reinvent program; and has built proprietary tools in its Applied AI practice, including an award-winning data-breach-notification analysis tool recognized at the 2025 Legalweek Leaders in Tech Awards.

Is Baker McKenzie the world's largest law firm?#

Baker McKenzie is consistently ranked among the largest law firms in the world and has often been the largest by headcount and global footprint. By its own May 2026 figures, the firm has more than 3,500 lawyers across 74 offices in 41 countries, and it reports multibillion-dollar annual revenue, placing it among the top global firms regardless of the exact ranking in any given year.

What is BigLaw AI client intake?#

BigLaw AI client intake is the use of artificial intelligence to run the first conversation between a large law firm and a prospective client or new matter. Instead of a web form or general inbox, an AI intake agent conducts a structured, natural conversation that captures the client's situation, urgency, scope, and jurisdiction, then routes a qualified summary to the right practice group — closing the gap between the profession's mature back-office AI and its outdated front door.

Did Baker McKenzie cut jobs because of AI?#

Baker McKenzie announced in early 2026 that it would reduce part of its global business-services workforce and cited its increased use of AI as one factor. Reports estimated up to roughly ten percent of business-services staff — an estimated 600 to 1,000 roles in functions such as research, know-how, marketing, and secretarial support — with attorneys reported to be unaffected. Industry commentators noted AI was likely one of several drivers rather than the sole cause.

Conclusion: Rethinking Client Intake at Global Scale#

Baker McKenzie AI is a case study in doing the hard part first. The firm spent nearly a decade building the governance, talent, and multi-vendor discipline to put machine intelligence inside the practice of law — document review, research, drafting, breach analysis — and it did so more deliberately than almost any peer. The irony is that the easiest remaining win sits at the opposite end of the relationship: the first conversation with a client. Intake is still a form, and forms cannot follow up, cannot probe, and cannot capture the "why" that decides which partner takes the matter.

That is the gap Perspective AI closes. By replacing the intake form with a conversational agent that interviews prospects the way a great intake lawyer would — in their own words, around the clock, with structured routing on the back end — firms turn a leaky front door into a qualification engine. If your firm has invested in AI for the lawyer's workflow but still meets new clients with a static form, the next step is to start a conversational intake study and see what a real conversation captures that a form never will. Explore how intelligent intake works, or compare the approaches before you commit.