Lawyers
Scrub through 335years of this role's history, from when it first emerged, through every wave of technology that reshaped it, to the cited projections for where it's heading next.
The tools that defined the work
Select an era to see how it reshaped the work.
Handwritten pleadings, quill pen, law library (Coke, Blackstone)
The earliest American lawyers composed every document by hand. A brief in a significant case might run dozens of folio pages in the lawyer's own script; a contract was a single handwritten instrument, engrossed on parchment for durability. The law library was the only research tool: William Blackstone's Commentaries on the Laws of England (1765-1769) was the canonical text that shaped an entire generation of American lawyers, including Lincoln, who read it by firelight. The volume of litigation a single lawyer could handle was physically constrained by how fast he could write. The clerk who engrossed final copies was often a lawyer in training.
Ledger workPaper recordkeeping Typewriter + carbon paper; West Publishing National Reporter (1879)
The Remington No. 1 typewriter reached commercial availability in 1874; by the late 1880s, law offices had adopted it for correspondence and short documents. More consequentially, John West launched the West Publishing Company's National Reporter System in 1879, creating the first comprehensive case-law compilation organized by region and indexed by subject. West's Key Number system — still in use today — gave lawyers a common vocabulary for finding precedent across the entire United States. By 1900, a competent attorney had access through West volumes to every significant appellate decision in the country. Carbon paper multiplied the legal secretary's output; a single typing produced up to six usable copies. The typewriter and West's reporters together tripled what a single practitioner could produce and cite in a given day.
Work toolChanging equipment IBM Selectric typewriter + dictation; photocopier (Xerox 914, 1959)
The IBM Selectric (1961), with its rotating type-ball element, became the dominant law-office machine for two decades. It could produce clean, professional documents at twice the speed of earlier typewriters, and the ability to change type-balls allowed legal formatting (different point sizes, special symbols) without changing machines. The Xerox 914 plain-paper copier, introduced in 1959 and widely adopted through the 1960s, ended carbon-paper duplication and made discovery a volume business: for the first time, entire files of documents could be reproduced inexpensively for litigation. The photocopier is arguably the tool that created modern discovery practice — and, unintentionally, the need for paralegals to manage the resulting paper.
Accounting softwareIntegrated ledgers LexisNexis (1973) and Westlaw (1975) — electronic legal research
Mead Data Central launched the LEXIS full-text legal research service in 1973; West Publishing countered with Westlaw in 1975. For the first time, a lawyer could run a keyword search across the entire US case law corpus in seconds rather than hand-indexing West Digest volumes. The early systems required dedicated green-screen terminals — often operated by research librarians or paralegals rather than partners. By the late 1980s, with IBM PC compatibility, Westlaw and LexisNexis moved to attorney desktops. The print-volume business that had sustained West Publishing for a century began a slow decline; the replacement was a subscription model that would eventually make these two companies the dominant revenue sources in legal information.
Effect on the workElectronic research roughly halved the time required for comprehensive case research and expanded the scope researchers were expected to cover — the net effect on attorney hours was approximately neutral in the 1980s, but over the following decade the reduction in associate time per research task compressed the number of junior attorneys firms needed to staff large projects.
Work toolChanging equipment WordPerfect (law-office standard) and early practice management software
WordPerfect 4.0 (1984) became the word processor of the legal profession for a decade, its macros for pleading paper formatting, line-numbering, and citation styles making it the default in firms of every size. The transition from Selectric to PC word processors meant lawyers and their secretaries could revise documents without retyping from scratch; it also meant that the typing pool — a significant overhead cost in large firms — shrank dramatically. Time-and-billing software (TABS, PCLaw) emerged in the mid-1980s as law firms began tracking matter profitability systematically.
Work toolChanging equipment Email + internet; federal CM/ECF e-filing (1996); e-discovery begins
Email transformed legal correspondence from a multi-day process (letter, dictation, typing, delivery) to an instantaneous one — with the side effect of creating a discovery universe that grew exponentially every year. Federal courts began piloting the Case Management/Electronic Case Files (CM/ECF) system in 1996; by 2004, e-filing was mandatory in most federal districts. The PACER public-access system made federal case dockets freely searchable online. The explosion of email as a business communication tool simultaneously created the modern e-discovery industry: by 2000, a significant commercial litigation matter might involve millions of emails, and the question of how to review them had become the dominant cost driver in litigation.
Work toolChanging equipment DocuSign (2003) + Equivio predictive coding (2007)
DocuSign was founded in 2003 and began displacing wet-signature closing processes in transactional law. By the early 2010s, it had become standard for routine commercial contracts, NDAs, and real estate closings — eliminating the closing-table ceremony for deals that didn't require one. Simultaneously, Equivio (founded 2004, acquired by Microsoft 2015) introduced supervised machine-learning for e-discovery document classification, giving litigators the first algorithmic tool for first-pass document review. Equivio's technology foreshadowed predictive coding, which in 2012 received its first court approval in Da Silva Moore v. Publicis Groupe.
Work toolChanging equipment Technology-Assisted Review (TAR) approved by courts; Kira and Luminance contract AI
US Magistrate Judge Andrew J. Peck's ruling in Da Silva Moore v. Publicis Groupe (S.D.N.Y., Feb. 24, 2012) was the first federal court decision to explicitly approve predictive coding as a valid discovery methodology. The ruling opened the door for algorithmic review in the most document-intensive legal work. Kira Systems (2012) and Luminance (2015) brought machine learning to contract review — allowing lawyers to extract specific clause types from hundreds of contracts in minutes rather than days. By 2020, large-firm M&A due diligence was routinely running NDA and material-contract portfolios through contract AI before assigning associate review hours.
Effect on the workContract AI tools reduced the associate hours required for due diligence on large M&A transactions by an estimated 20-40% in the early 2020s; combined with LPO and offshore review, this reduced first-year BigLaw associate class sizes at several firms by 15-25% between 2017 and 2023.
Work toolChanging equipment Harvey AI (2022) + Allen & Overy firmwide GPT-4 deployment (Feb 2023)
Harvey was co-founded in summer 2022 by Winston Weinberg (securities litigator) and Gabriel Pereyra (Google DeepMind). It raised $5M from the OpenAI Startup Fund in November 2022 and integrated GPT-4 at the model's launch. On February 16, 2023, Allen & Overy announced it had deployed Harvey firmwide to 3,500 lawyers, who had already run approximately 40,000 queries during a trial period. This was the first major BigLaw endorsement of a generative AI platform for substantive legal work — not document management or billing, but drafting briefs, researching case law, and summarizing contracts. The announcement triggered a competition among Am Law 100 firms that effectively made Harvey deployment a table-stakes signal of technological credibility by end of 2023.
AI audit toolsPattern detection Mata v. Avianca (June 2023): ChatGPT fabricates six case citations, federal sanctions follow
On March 1, 2023, attorney Steven Schwartz of the New York firm Levidow, Levidow & Oberman filed a legal brief in Mata v. Avianca, Inc. (S.D.N.Y.) that cited six federal cases in support of his client's claims. None of them existed. Schwartz had used ChatGPT to research the brief and, when the AI produced confident-sounding case summaries complete with docket numbers, had filed them without verification. Opposing counsel flagged the citations; Schwartz doubled down by asking ChatGPT to confirm they were real, and ChatGPT confirmed they were real. On June 22, 2023, Judge P. Kevin Castel sanctioned Schwartz and his supervising partner $5,000 and ordered them to serve copies of the opinion on the judges whose names appeared in the fabricated citations. The case became the canonical example in every bar association AI ethics opinion filed in 2023-2024: the Magesh et al. (JELS 2025) finding of 17-43% hallucination rates across commercial legal AI platforms was, in part, a systematic study of the phenomenon Schwartz discovered the hard way.
AI audit toolsPattern detection Full BigLaw AI stack: CoCounsel, Lexis+ AI, Hebbia, Luminance, Relativity aiR, EvenUp
By end of 2023 and accelerating through 2025-26, every major legal research platform had deployed a generative AI layer: Thomson Reuters acquired Casetext for $650M (June 2023) and its CoCounsel product reached one million users by February 2026; LexisNexis launched Lexis+ AI in October 2023 and upgraded to Lexis Protégé with 300+ pre-built legal workflows in February 2026; Harvey processed 10 million documents in Q1 2026 alone across its platform and was used by 80 of the Am Law 100; Relativity's aiR for Review (generally available Q3 2024) automated e-discovery classification with AI-generated reasoning. A&O Shearman's ContractMatrix (Harvey-powered) was used by 2,000 lawyers daily and saved 30% of contract review time. The Thomson Reuters Future of Professionals 2025 report projected AI would save each lawyer an average of 190 hours per year. The ABA's 2024 AI TechReport found 30% of all law firms were using AI tools, rising to 47.8% at firms with 500+ lawyers.
Effect on the workHarvey M&A users reported up to 75% time savings on unstructured data rooms; A&O ContractMatrix saved 2-3 hours/week per lawyer; lateral associate hiring for AI-specialty positions grew 106% year-over-year (Law.com, March 2026). Am Law 100 first-year associate class sizes were down 15-25% from their 2022 peak by 2026.
Work toolChanging equipment
What credible sources project
Scrub the slider past now to anchor each scenario on the scrubber. The spread is the range of futures credible sources project for this role.
What's shifting in the work right now
The historical view above shows how this role has moved. This is the present-day detail: which AI tools are picking up which tasks, where the edge still is, and the natural directions this work can grow.
What's changing in your day
Three parts of your work where AI is already doing real lifting, and what stays yours.
AI is sitting alongside you hereOversee AI-driven M&A due diligence using Harvey or Hebbia Matrix: configure risk-extraction criteria for the target's data room, review AI-generated issue logs and contract summaries for material adverse change clauses, change-of-control provisions, and compliance exposures
Oversee AI-driven M&A due diligence using Harvey or Hebbia Matrix: configure risk-extraction criteria for the target's data room, review AI-generated issue logs and contract summaries for material adverse change clauses, change-of-control provisions, and compliance exposures; escalate high-risk findings and advise the deal team on negotiation strategy.[7],[12],[4]
Learn to write precise diligence extraction schemas: define the specific clauses (MAC, CoC, exclusivity, non-compete) that matter for each transaction type. AI surfaces the issues; the attorney's value is interpreting their commercial significance and advising on deal structure. Develop industry-specific knowledge of what risk thresholds are market-standard vs. deal-breaking.
AI is sitting alongside you hereDirect AI legal research agents (CoCounsel Deep Research, Westlaw Advantage AI) to execute multi-jurisdictional case law surveys
Direct AI legal research agents (CoCounsel Deep Research, Westlaw Advantage AI) to execute multi-jurisdictional case law surveys; validate every AI-returned citation with Shepard's or KeyCite before citing in any brief or memo; synthesize findings into a research memorandum with jurisdiction-specific precedent hierarchy.[18],[10],[9]
Master structured prompting for AI research workflows: specify jurisdiction, date range, binding vs. persuasive precedent, and negative treatment. Always Shepard's-check every AI-returned case — Magesh JELS 2025 found 17-33% hallucination rates even in retrieval-augmented legal AI tools. The lawyer who writes precise research instructions and validates outputs reliably is irreplaceable.
AI is sitting alongside you hereDesign and supervise AI-assisted eDiscovery workflows for litigation matters: configure responsiveness and privilege parameters in Relativity aiR
Design and supervise AI-assisted eDiscovery workflows for litigation matters: configure responsiveness and privilege parameters in Relativity aiR; QA AI classifications on a statistically defensible sample; certify the privilege log; and make final calls on borderline attorney-client and work-product privilege designations.[19],[3]
Shift focus from document review volume to protocol design and privilege log defense. AI auto-classifies at scale; the attorney is responsible for the sampling strategy and the certifications submitted to opposing counsel and the court. Develop expertise in technology-assisted review (TAR/predictive coding) to be able to defend the process under Federal Rules of Civil Procedure Rule 26.
Where this role is heading
Natural next steps for someone with your foundation: not exits, evolutions.
Compliance Officers
Lawyers who practice regulatory, employment, or securities law possess deep compliance expertise that translates directly to in-house compliance officer roles — often without additional credentials. Corporate legal teams actively recruit JD-holding compliance professionals, particularly in highly regulated sectors (healthcare, financial services, tech). AI is accelerating the shift of outside-counsel work in-house, growing the compliance function even as it compresses law firm headcount. The pivot typically requires domain specialization in one regulatory framework (HIPAA, SOX, GDPR, SEC) but not retraining from scratch.
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