Using AI for litigation workflows is no longer a theoretical discussion for law firms. It is already shaping how cases are analyzed, prepared, and argued. As adoption continues to expand, simply having AI isn’t the cutting-edge advantage it once was. Now, to stay ahead, litigation teams must focus on how they use AI—and what it takes to do so responsibly and effectively. This means law firms must find the best AI tools for litigation, optimize workflows, and expand use to drive value throughout the case lifecycle and beyond.
The new eBook, The future of AI in litigation, features perspectives from law firm leaders, legal technologists, and industry analysts. Each shares predictions and advice as they answer the question: How will AI transform litigation, and what should law firms do to prepare?
Taken together, their insights reveal a clear theme: The future of AI for litigation will not be defined by tools alone, but by decisions around platforms, governance, workflows, and people.
Here are six priorities firms should focus on as AI becomes embedded in litigation practice.
1. Start with the right technology foundation
Successfully using AI for litigation workflows starts with the right technology foundation. As new capabilities proliferate across the legal technology market, success depends less on investments in standalone AI tools and more on how AI capabilities are embedded into the platforms where litigation teams already work.
Litigation is inherently interconnected. Case assessment informs fact development. Fact development shapes deposition strategy and motion practice. Litigators build strong case strategies using work product including chronologies, witness profiles, deposition summaries, and issues developed by associates and paralegals.
Increasingly, industry leaders believe AI will only deliver meaningful value when it operates within those connected platforms and workflows. One of the clearest lessons emerging from early AI adoption is simple: Avoid fragmented tools. Layering standalone and point solutions onto already complex technology stacks often creates more friction than value.
Legal industry analyst Ari Kaplan shared his market observations, saying, “Firms are experiencing solution fatigue and looking to platforms where AI is embedded into daily work.”
Sharing a similar sentiment, Gyorgy Pados, practice technology associate director of White & Case advises, “Firms must move from fragmented point solutions to integrated, intelligent platforms with true interoperability. This unified approach allows data to flow seamlessly across matter management, billing, document review, and research.”
Looking to the future, the best AI tools for litigation teams will not only centralize the case management, strategy, and preparation process, but offer adaptability that lends itself to innovation. As Beau Wysong, senior vice president of global marketing at Opus 2 says, “In the future, AI-enabled platforms will not only unify data, workflows, and collaboration in the litigation lifecycle, but also enable firms to build upon that platform foundation to quickly deliver custom client solutions. Once established, these platforms will fuel innovation, becoming the default destination when users want to expand their AI use, experiment, or solve new challenges.”
2. Ensure governance and defensibility are built into AI workflows
As AI becomes embedded in litigation workflows, governance must be built into the technology from the outset. Courts, clients, and regulators increasingly expect transparency around how AI-assisted analysis is generated, validated, and relied upon in legal work.
For litigation teams, this means ensuring that AI outputs remain tied to the underlying case record and can be traced back to verifiable source material. Technology environments that support audit trails, explainability, and human oversight allow firms to use AI confidently while maintaining the rigor required in high-stakes disputes.
Ultimately, the responsibility for legal work product remains with the attorney. Laura Ewing-Pearle, Senior Manager of E-Discovery and Practice Support Technology at Baker Botts LLP, underscores that point: “Attorneys ultimately retain responsibility for all work product, whether human- or AI-generated.”
Strong governance therefore extends beyond internal policy. It depends on systems that allow lawyers to review, validate, and defend AI-assisted work as part of their broader case strategy. As Gyorgy Pados, Practice Technology Associate Director at White & Case LLP, emphasizes, “AI in legal practice must operate under the same standards of diligence and accountability as human work.”
Firms that embed governance and defensibility into their technology and workflows from the outset will be far better positioned to scale AI responsibly as its use continues to expand.
3. Invest in continuous AI enablement and education
In 2025, 81 percent of law firms adopted new AI, according to research from Ari Kaplan Advisors that explored AI for litigation management and case strategy. While it may seem that the playing field has been leveled, law firms that focus on AI adoption, education, and enablement can still gain a competitive advantage. After all, even the most advanced AI tools for litigation will fail to make a meaningful impact if they’re unused or misunderstood. As Shannon Lex Bales, Senior Manager of Litigation Support at Munger Tolles & Olson LLP, puts it, “Transformation happens through people, not platforms.”
Partners, associates, litigation support professionals, and paralegals can all benefit from AI. Achieving adoption across these roles requires AI implementation, training, and enablement that addresses the needs and concerns of the entire litigation team.
“Strong AI tool development and usage will necessitate having the partners sit at the table with the technology team to determine the best way to assist the firm’s users,” said Ewing-Pearle. “Successful integration also requires robust training, and regular evaluation of tools.” Adam Wehler, Director of E-Discovery Strategies and Litigation Technology at Smith Anderson, added, “Litigators must understand how data is created, analyzed, and challenged—not just oversee the technology.”
Melina Efstathiou, lead for disputes and investigations at Legal Data Intelligence, emphasizes the importance of broad accessibility and education, saying: “Lawyers must be fluent in AI literacy and governance, with training that is accessible, accredited, and designed to democratize expertise rather than gatekeep it.”
When firms invest in training and knowledge sharing, AI becomes a capability that strengthens the entire litigation team rather than a niche tool used only by a handful of early, tech-savvy adopters.
4. Demonstrate how AI creates client value
Beyond internal adoption, firms must also consider how AI is shaping client expectations. Client questions about law firm AI use are increasingly common. More broadly, AI has driven discussions about the business of law, including renewed interest in cost predictability, the billable hour, and alternative fee arrangements.
Richard Tromans, founder of Artificial Lawyer, frames the issue in terms of how law firms adapt their business models: “The real issue is not whether AI improves, but how the economics of legal work adapt … It would seem likely that as an industry we will have to move more towards fixed fees, scoped fees, and if all else is unworkable, then “value billing”—although that opens a can of very different “economic worms” to contend with.”
Pat Fanning, a partner and trial lawyer at Lathrop, also predicts a shift: “I remain convinced AI will usher in a new era where law firms increasingly price their litigation services based on case milestones or achievements rather than hours spent.”
Even if firms aren’t making changes to their billing approach, they must still be prepared to demonstrate how using AI for litigation translates to client value. If AI enables lawyers to analyze evidence faster or streamline aspects of case preparation, clients reasonably expect those efficiencies to drive results.
5. Expand AI use beyond administrative tasks
Much of the early adoption of AI in legal practice has focused on accelerating administrative tasks. This includes summarizing documents, organizing discovery materials, and assisting with research. While these capabilities can deliver meaningful efficiency gains, many experts believe the most significant value of AI will emerge from higher-level analytical use cases.
Kate Orr, the managing director of practice innovation at Orrick, says, “AI that quickly synthesizes complex records or generates targeted argument outlines isn’t about shaving minutes; it’s about creating space for the litigator to focus on the thorniest issues and nuances of the case.”
In litigation, these advanced applications include developing case strategy, identifying patterns across evidence, and helping lawyers understand complex fact patterns earlier in the lifecycle of a dispute. These capabilities allow litigation teams to move more quickly from information gathering to strategic analysis. As a result, lawyers can engage more deeply with the evidence and refine their theories of the case earlier in the process.
Josh Zylbershlag, Director of E-Discovery Services at Paul, Weiss, highlights this shift in how lawyers interact with case materials, saying, “AI’s ability to restore deep familiarity with case materials is perhaps its most compelling impact.”
When AI helps litigators understand the full case record more quickly, it strengthens their ability to test arguments, identify evidentiary gaps, and develop more informed strategies.
6. Elevate human judgment as AI becomes assumed
Perhaps the most consistent theme across the expert contributions is that AI will not replace litigators—but it will change what differentiates them.
As AI accelerates drafting, research, and motion preparation in addition to enhancing strategic insights, technical capability alone won’t define success. Instead, the differentiator will increasingly be judgment: knowing which arguments matter, how evidence should be framed, and when restraint is more persuasive than volume. Orr summarizes the relationship succinctly, saying, “AI will reshape litigation by amplifying judgment, not replacing it.”
In many ways, the growing presence of AI will place greater responsibility on litigators to guide how these tools are used. Future litigation leaders will need to combine legal craft with technological understanding, shaping AI-enabled workflows while retaining accountability for strategic decisions that ultimately determine outcomes.
Fanning highlights a similar effect on litigation practice saying, “Ironically, the more the litigation practice evolves toward AI, the more the individual attorney will need to depend on the age-old skills of oral advocacy, effective deposition taking, and possessing the wisdom to understand the arguments actually worth pursuing.”
In an environment where AI can accelerate research, drafting, and analysis, the law firms that stand out will not simply be those who use the technology—but those understand how and when to apply it.
Looking ahead
The future of AI in litigation will not be defined by technology alone. It will be shaped by the decisions law firms make today—how they select platforms, govern AI use, invest in their people, drive client value, advance AI use, and amplify human judgment.
The firms that approach AI as a strategic capability rather than a shortcut will be best positioned to meet rising client expectations, maintain trust, and deliver stronger outcomes in increasingly complex disputes.
The organizations that move deliberately—simplifying their technology environments, strengthening adoption, and aligning AI with the realities of litigation work—will not simply adapt to the next phase of legal technology.
They will define it.
Download the eBook to explore more insights and predictions from the experts.
