AI litigation platform Crimson has today (8 January) published its Litigation AI Playbook 2026, setting out how artificial intelligence is now being used across the lifecycle of disputes, examining its impact on early case assessment through advocacy, pricing, professional conduct and judicial expectations.
Over the past year, Crimson’s CEO Mark Feldner says the company spoken with more than 200 litigation partners, innovation managers and knowledge lawyers across different firms and jurisdictions about what effective AI use looks like in practice.
A central theme of the playbook is that AI in disputes has moved beyond isolated productivity tools. Where earlier use cases focused on discrete tasks such as summarisation or first-draft text, the report finds that AI is increasingly deployed at the level of the matter as a whole, helping lawyers organise evidence, arguments and strategy across an entire case file. And it examines what that means in terms of training, costs and advocacy.
Early case assessment and client clarity
According to the playbook, early case assessment emerges as the single more frequently cited AI use case in contentious work. AI systems are now used to structure and analyse large volumes of material at the outset of a dispute, allowing lawyers to focus more quickly on judgment, strategy and advocacy rather than manual collation and review.
The report finds that this has practical consequences for both cost and scope management. With clearer chronologies, issue maps and early drafting, litigation teams can give clients a more grounded view of prospects, timelines and likely costs at an earlier stage. This in turn supports clearer conversations about settlement options and risk before proceedings escalate.
Managing correspondence at scale
Email and correspondence management is another area where AI is becoming embedded in day-to-day disputes work. The playbook notes that litigation teams routinely deal with industrial-scale correspondence, including communications with clients, opposing counsel, courts and internal teams across jurisdictions.
AI tools are being used to optimise search and retrieval, summarise correspondence in context, and maintain command of the factual record. The principal benefits identified are time saved on administrative effort and stronger factual control when communicating with clients and counsel, rather than automated decision-making.
Expert evidence and technical material
In complex litigation and arbitration, expert evidence often requires sustained engagement with documents, data and evolving party positions. The report finds that AI now supports both lawyers and experts in preparing, digesting and explaining complex case files.
Rather than replacing expert judgment, AI is described as reducing friction in preparation, document review and reference checking. This leaves more time for expert reasoning and explanation, and makes expert material easier for courts and tribunals to follow and assess. The report highlights clearer technical insight, faster turnaround times and lower costs as downstream effects.
Advocacy, hearings and persuasion
The playbook also addresses AI’s role in hearings, trials and submissions. It notes that when cases reach a final hearing, AI tools are increasingly used to organise transcripts, evidence and submissions in a way that allows advocates to locate and analyse material in real time. AI allows teams to search across days of evidence for a particular concession and help to map what has been said in the courtroom.
According to the report, this does not change who makes decisions in the courtroom. Instead, it allows decisions to be made from a position of greater clarity and organisation, improving judgment under pressure and supporting more disciplined preparation.
Pricing, fees and client expectations
Despite productivity gains, the report finds no wholesale departure from the billable hour. Hourly billing remains dominant in disputes, with AI primarily reshaping costs rather than fee models. AI is most often used to reduce time spent on document-heavy and non-billable work, while core legal analysis remains billed hourly.
“The firms we surveyed report that efficiency gains at this stage largely accrue internally: less write-off, more productive senor time, and greater capacity across the team, without necessarily changing the headline fee for the client,” the playbook finds.
However, the playbook notes growing pressure for transparency. Early case assessment and disclosure exercises are identified as the clearest candidates for fixed or capped fees, as AI improves predictability and visibility over scope. Clients increasingly expect a clear explanation of how AI is used, what benefits it delivers, and how confidentiality and quality are protected
Trust, governance and professional duties
Client trust and professional conduct feature prominently. The report emphasises that AI use in disputes is acceptable when it operates within defined guardrails aligned with existing duties around confidentiality, privilege and accountability.
Common client questions addressed in the playbook include whether AI creates risk for privileged materials, how AI affects charging, whether disclosure to courts or tribunals is required, and what happens if AI produces an error. In each case, the report stresses that lawyers remain fully responsible for outputs, verification and advice.
There is a really helpful chapter on client trust and communication, setting out how to discuss AI with sophisticated disputes clients in a way that supports long-term trust.
Strong RFPs speak in the language of disputes rather than generic innovation claims; they demonstrate purposeful adoption rather than experimentation; and they connect capability to team quality, allowing associates to move more quickly to substantive work.
“If a mandate is won, AI use should be addressed at the outset of the matter alongside scope, team structure and pricing,” the report finds.
Talent, training and recruitment
Beyond efficiency, the playbook highlights AI’s growing role in recruitment and training. Law firms are using AI capability as part of their employer proposition, with modern tooling increasingly seen as basic infrastructure by junior lawyers. Clio’s recent report on What Gen Z Lawyers Want in 2025 made the point that young lawyers expect modern tools that steamline workflow and reduce workload. Clio’s recent report on What Gen Z Lawyers Want in 2025 made the point that young lawyers expect modern tools that steamline workflow and reduce workload. “This expectation travels fast,” the playbook says. “Associates compare notes across intakes and practice areas, discuss the tools they use on Legal Cheek and RollonFriday, and increasingly consider technology adoption when deciding where to apply.”
At the same time, the report identifies the need to rethink training pathways. Where the early stages of a litigation career revolved around footnotes, bundles and first drafts – and those tasks built discipline and familiarity with documents – AI removes some of that manual work. The question then arises as to how we expose juniors to the substance of a case more quickly while still building the same depth of skill.
The administrative work that used to dominate the early years will become lighter and more manageable, allowing juniors to develop judgment through case analysis much earlier. “The result is an acceleration in judgment formation that once took years,” the playbook says.
The risk is that critical thinking slips, and the report urges training and reinforcement of habits around checking details and providing explanation. At the heart of this will be close mentoring to enable juniors to understand the reasoning behind changes in drafts and how to weigh the strength of an argument against procedural reality and client objectives. There is a helpful list of what good training looks like today.
Judicial and arbitral perspectives
Judicial attitudes to AI are described as, at the end of 2025, having settled around one central concern: the accuracy of authorities placed before the court. Across guidance and decisions during 2025, judges consistently emphasised the need to verify sources, and threatened sanctions for lawyers who fail to do so.
In arbitration, the report notes (and lists) a growing body of “soft law” guidance from institutions and practitioner groups. While approaches vary, common themes include human responsibility, transparency and the need to assess AI-assisted evidence on a case-by-case basis
From experimentation to discipline
The playbook concludes that leading disputes teams have largely moved past the question of whether to use AI. The focus is now on disciplined implementation: defined baselines, approved use cases, audit trails, verification and clear human accountability. According to the report, this approach delivers practical benefits for both lawyers and clients, including earlier clarity, more consistent execution and greater time for judgment and advocacy.
Our opinion – definitely worth a read.
To read the report click here: https://www.crimson.law/resources/ai-litigation-playbook-2026
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