<\/p>\n
Firms from elite global practices to specialist boutiques are deploying vendor tools, bespoke platforms and proprietary systems to automate drafting, review and research \u2014 reporting efficiency gains while emphasising sandboxing, retention controls and mandatory human verification as regulators and clients press for stronger governance.<\/p>\n<\/div>\n
The legal profession\u2019s cautious, centuries\u2011old rhythms have been ruptured by a new force: artificial intelligence. According to a recent industry overview, routine tasks that once consumed vast swathes of associates\u2019 and paralegals\u2019 time \u2014 drafting, document review, e\u2011discovery triage and research \u2014 are now routinely delegated to machine models that can cluster documents, surface issues and produce first drafts in minutes rather than hours. Firms that move fastest report measurable efficiency gains, but those claims are almost always accompanied by an insistence on human oversight and governance. (National Law Review; firm innovation pages.)<\/p>\n
A cluster of firms has emerged as exemplars of how to deploy AI at scale. In May 2025 Adams & Reese announced it had adopted Everlaw as its exclusive e\u2011discovery platform, saying the cloud\u2011native, AI\u2011enabled tools have accelerated document review, improved data management and reduced case turnaround times. The firm and Everlaw executives described faster analytics, automated timeline building and summarisation capabilities \u2014 concrete efficiencies, the announcement framed, that are already lowering costs and improving client responsiveness. (National Law Review; Adams & Reese announcement.)<\/p>\n
Some legacy global firms have pursued vendor partnerships as their primary route to capability. Allen & Overy was an early and high\u2011profile adopter of Harvey, rolling the system out through its Markets Innovation Group and trialling it with thousands of lawyers; the firm says the tool has been used for multilingual drafting, contract analysis and research while every AI output is audited by humans. DLA Piper likewise positioned a 2023 rollout of Casetext\u2019s CoCounsel as essential to staying competitive, describing AI adoption in blunt terms: that the market is an \u201carms race\u201d and no firm wants to be left behind. (National Law Review; Allen & Overy announcement; DLA Piper announcement.)<\/p>\n
Other firms have blended vendor technology with bespoke internal systems. Baker McKenzie describes a period of piloting large language models to generate drafts and assist with legal research while emphasising client\u2011by\u2011client sandboxing to meet bespoke data\u2011security needs. Dentons has taken the step of building a client\u2011secure GPT\u20114 environment \u2014 fleetAI \u2014 developed with third\u2011party partners to ensure uploaded client data would not be used to train external models and that retention rules and deletion policies are enforced; public reporting around the launch stressed staff training, governance and the need to verify AI output. (National Law Review; firm statements and press coverage.)<\/p>\n
Some firms have chosen fully proprietary routes. Cooley publicises a suite of in\u2011house platforms \u2014 including Vanilla, a secure cloud system aimed at private funds, and Cooley GO with its embedded Cooley GObot chatbot \u2014 positioning these tools as client\u2011facing, quality\u2011led innovations governed by principles of ethics and transparency. Cooley\u2019s materials describe the platforms as designed to streamline investor onboarding, compliance and practical guidance for startups, and the firm has been explicit about publishing a manifesto that sets out those commitments. (National Law Review; Cooley innovation materials.)<\/p>\n
Specialist and practice\u2011led experiments are also common. Wilson Sonsini added an AI\u2011enabled, fixed\u2011fee commercial contracting offering to its Neuron platform after in\u2011house testing that the firm said achieved roughly 92% accuracy in identifying issues and applying its playbook positions; the model is presented as a lawyer\u2011in\u2011the\u2011loop tool to speed contract lifecycle tasks. Employment boutique Fisher & Phillips helped design and now uses Casetext\u2019s CoCounsel to compress legal research tasks from hours into minutes. Elsewhere, firms such as Gunderson Dettmer, Macfarlanes, Holland & Knight, Cuatrecasas, Orrick and the Big Four\u2011aligned KPMG Law have each taken different paths \u2014 from bespoke chat apps and amplified internal workflows to ABS\u2011enabled, hybrid operating models that combine non\u2011traditional ownership with aggressive technology deployment. (National Law Review; Wilson Sonsini announcement; firm statements.)<\/p>\n
That diversity of approach underlines the twin promises and pitfalls of legal AI. Vendors and early adopters trumpet time and cost savings and increased throughput; press releases and corporate pages point to measurable productivity improvements and new fixed\u2011fee offerings that can accelerate clients\u2019 time to revenue. But these same announcements repeatedly attach caveats: models are sandboxed for particular clients, outputs are subject to human verification, data\u2011use and retention policies are prescribed, and training and governance are elevated as equally important investments. As DLA Piper\u2019s chair of AI practice, Daniel Tobey, put it in the firm\u2019s 2023 statement about CoCounsel: \u201cThis is an arms race, and you don\u2019t want to be the last law firm with these tools. It\u2019s very easy to become a dinosaur these days.\u201d (Firm announcements; Wilson Sonsini testing; DLA Piper statement.)<\/p>\n
The regulatory and ethical questions are now the most consequential. Firms and platforms are experimenting with notice obligations to clients, deletion and retention windows, and controls to prevent inadvertent model training on confidential information \u2014 measures that aim to reconcile commercial advantage with professional duties. Reports about secure, client\u2011only environments and enforced deletion windows have become a centrepiece of vendor\u2011and\u2011firm narratives because they respond directly to lawyer concerns about privilege, confidentiality and model leakage. At the same time, independent testing and transparent governance frameworks are still uneven: accuracy claims vary by task and by how tightly a model has been aligned to a firm\u2019s playbook. (Firm statements and coverage; industry materials.)<\/p>\n
For now the prevailing model is augmentation: AI as a tool that amplifies lawyers\u2019 capacity rather than replaces professional judgement. But the pace of change \u2014 multiple vendor partnerships, bespoke platforms, fixed\u2011fee automation and Big Four entrants built on hybrid ownership structures \u2014 suggests an inflection point is approaching. If the next phase is shaped by reproducible, regulated, client\u2011facing automation, the profession will have to reconcile new business models, supervision rules and training requirements with longstanding duties to clients and courts. Firms that transparently marry technical controls with clear governance, and that treat human review as non\u2011negotiable, are most likely to shape how that future unfolds. (National Law Review; Cooley materials.)<\/p>\n