Key Takeaways
- Thomson Reuters’ CoCounsel Legal can reduce average litigation research time from 17-28 hours to 3-5.5 hours, with a June 2026 Forrester study commissioned by Thomson Reuters projecting 400% ROI over three years and a 25% increase in attorney matter capacity without additional headcount.
- Lexis+ AI enabled Rupp Pfalzgraf to draft complex federal court motions in a quarter of the usual time; a June 2025 Forrester study commissioned by LexisNexis found the platform generated $1.2 million in benefits and a 284% ROI over three years for corporate legal departments.
- Accuracy constraints remain a live risk: one study found Lexis+ AI accurate on roughly 65% of legal research queries while Westlaw AI reached about 42%, with 57% of lawyers citing hallucination as their primary barrier to adoption. AI adoption in law firms jumped from 19% in 2023 to 79% in 2024, according to the Clio Legal Trends Report, a pace that has outrun most firms’ ability to govern what they’ve deployed. The efficiency case is clear enough: platforms like Thomson Reuters‘ CoCounsel Legal and LexisNexis’ Lexis+ AI are compressing research cycles that once took days into hours. The harder question is whether firms are building the workflow discipline to make those gains stick.
Assessing Firm Readiness
The starting point is infrastructure, not software. Outdated or siloed systems cap AI’s impact before a single query is run. Firms should audit whether key files and communications are readily accessible, whether current tools integrate with one another or depend on manual data entry, and which processes consume disproportionate time. Document review, particularly in eDiscovery and compliance audits, is consistently the highest-cost target, which makes it the logical first area for AI investment.
A May 2025 American Bar Association guide notes that this readiness assessment also establishes the business case for AI spend, giving leadership a defensible rationale before committing to enterprise licensing costs.
Choosing the Right Platform
Legal AI tools trained on authoritative legal data perform differently from general-purpose models, and the choice of platform carries real downstream consequences for accuracy and liability. The three platforms drawing the most enterprise attention are CoCounsel Legal, LexisNexis‘ Lexis+ AI and Harvey AI.
CoCounsel Legal integrates with Westlaw and Practical Law, covering deep research, document analysis, drafting and agentic workflows. Lexis+ AI, launched in June 2025, adds conversational search and document summarisation within the LexisNexis environment. Harvey AI, which raised $200 million at an $11 billion valuation in March 2026, runs models fine-tuned on legal data and is designed around a zero-training-on-customer-data architecture, a feature that addresses the client confidentiality concerns that have slowed enterprise AI adoption in regulated practices. As legal teams weigh these options, the evolution of Harvey and competing agent platforms is worth tracking closely.
Integration matters as much as capability. Platforms that embed directly into existing tools reduce friction significantly. Spellbook, for instance, integrates into Microsoft Word for contract drafting, avoiding the context-switching that erodes time savings. Implementation costs for enterprise AI solutions typically run at a significant share of the first-year license fee, a figure firms should model before committing.
Training for Adoption
Technical capability without workflow integration produces shelf-ware. The firms seeing the most durable gains are those that have structured AI literacy into how legal work is assigned and reviewed, not just offered optional training sessions.
As of January 2026, attorney AI training covers contract review, legal research, document automation and AI ethics, typically without requiring technical coding skills. Practical programmes focus on high-impact use cases first. For litigation research, attorneys learn to formulate natural-language queries that allow AI platforms to surface relevant case law, precedents and citations faster than keyword search. CoCounsel Legal’s AI-Assisted Research, for example, can identify relevant case law for a motion to dismiss without the manual triage of dozens of results; its context-aware summarisation compresses the output further. Lexis+ AI’s Brief Analysis feature distills large document sets into structured overviews.
Rupp Pfalzgraf’s integration of Lexis+ AI cut the time to draft complex federal court motions to a quarter of the previous standard. Harvey AI, in its deployment with A&O Shearman, reports an average saving of 2-3 hours per week on routine tasks, including a 30% reduction in contract review time and a 7-hour average saving on complex document analysis. For context on how AI is compressing contract review cycles more broadly the pattern across multiple firms is consistent.
The ethical dimension of training is not optional. Every attorney using these tools needs to understand that AI output requires verification against primary sources, not because the tools are uniformly unreliable, but because the consequences of undetected errors in legal documents are severe. The American Bar Association’s position is that prior positive experience with a tool may reduce, but does not eliminate, the verification burden.
Measuring Returns
The productivity numbers from commissioned research are notable, though the commissioning structure deserves acknowledgement. A June 2025 Forrester study commissioned by LexisNexis found Lexis+ AI generated $1.2 million in benefits and a 284% ROI over three years for corporate legal departments, reaching payback in under six months. A June 2026 Forrester study commissioned by Thomson Reuters projected CoCounsel Legal delivering 400% ROI over three years, driven primarily by a 25% increase in attorney matter capacity without adding headcount.
Time savings are the primary mechanism. AI-assisted litigation research compresses the average matter from 17-28 hours down to 3-5.5 hours. A July 2025 Thomson Reuters report puts the average annual value of these savings at $19,000 per attorney, with a projected $20 billion in annual value unlockable across the U.S. legal profession if adoption continues at its current pace. Firms that have moved beyond pilot deployments typically see measurable impact within 90 days of full licensing. The pattern of rapid ROI matches what other AI billing efficiency studies have found across the profession.
Accuracy Limits and Risk
The ROI projections assume the output gets used correctly. One study comparing legal AI platforms found Lexis+ AI accurate on roughly 65% of queries, still generating a material volume of false statements, while Westlaw AI reached about 42% accuracy with a higher error rate. Those figures sit alongside the 57% of lawyers who cite hallucination as their primary barrier to adoption. Security concerns and general trustworthiness each register at 55%.
The practical response is a consistent human-in-the-loop verification step: AI handles initial synthesis and summarisation; a qualified attorney checks outputs against primary sources before anything enters a document or argument. This is not a temporary workaround pending better models, it reflects the profession’s irreducible accountability structure. AI accelerates the research and drafting cycle; it does not absorb the liability that attaches to the work product.
Originally published at https://autonainews.com/how-cocounsel-legal-slashes-litigation-research-hours-by-80/
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