Litigation Minute: Proof Required: Evaluating AI in Litigation Practice

What You Need to Know in a Minute or Less

In litigation, everything comes down to evidence—what you can prove, what you can verify, and what holds up under scrutiny. The same principle now applies to artificial intelligence (AI) adoption in legal practice. The critical questions are not about whether outside counsel use AI, but how they measure its value, whether their lawyers have mastered the necessary skills, and whether they can collaborate with you through AI-powered workflows.

Beyond Hours Saved: Building a Multidimensional Value Case

The 2025 Legal Industry Report surveyed over 2,800 legal professionals and found that individual lawyer use of generative AI increased from 27% in 2023 to 31% in 2024. Yet many corporate legal departments report that when they ask outside counsel about AI capabilities, the conversation focuses on tools rather than outcomes.¹ 

The key question is whether AI creates measurable value across multiple dimensions. Time savings alone does not tell the full story. Consider cycle time—not just task duration but how quickly work moves through completion and review. AI that compresses both execution and review cycles fundamentally changes matter velocity. Then there is adoption velocity: Is the solution used consistently across the team? Can the approach scale from securities litigation to commercial disputes? Quality metrics—error rates, revision cycles, client feedback—tell you whether efficiency comes at quality's expense. And finally, how is any time savings applied to enhance services to the client, and can this be quantified? 

The firms that differentiate themselves are not just deploying AI; they are building evidence across this spectrum. Not “we saved 1,000 hours last quarter” but “our discovery response cycle time decreased 60%, lawyer adoption reached 85%, the approach scaled across four practice groups, client satisfaction scores increased 15 points, and with the reduction in time we were able to offer guidance on a future product development roadmap.” This multidimensional proof transforms AI from a technology story into a business value story.

Why Validation is the New Core Competency

The 2025 Legal Industry Report found that 77% of lawyers using AI deploy it for legal research, with 82% reporting increased efficiency.² Research from Ari Kaplan Advisors found litigation professionals saying “[t]he days of first-year or junior associates conducting transcript analysis are over, and this type of work is best suited to generative AI.”³ This isn't about replacing lawyers—it's fundamentally changing what lawyers spend their time doing.

For junior lawyers, developing expertise when AI handles foundational work requires new capabilities: systematic citation verification to catch hallucinations, prompting AI to generate alternative positions, analyzing AI summaries to identify what was missed, and comparing outputs against internal guidelines to ensure consistency. These validation skills build judgment through rigorous quality control.

For all lawyers, the challenge is developing critical thinking about what AI tools are good at and where they fail. Understanding which tasks benefit from AI assistance and which call for human judgment requires experimentation and the discipline to deploy freed time toward strategic thinking rather than simply handling more volume.

The ABA Model Rules require lawyers to maintain technological competence, including understanding of AI tools.⁴ But competence is not just knowing how to use AI—it is developing critical thinking about tools’ effectiveness, knowing how to verify outputs, challenging assumptions, and improving upon AI-generated work.

Strategic Value: Beyond Efficiency to Partnership

Forward-thinking litigation practices are using AI in two complementary ways: providing better strategic intelligence internally and collaborating more effectively with clients.

On the intelligence side, litigation practices are leveraging AI to analyze their own institutional knowledge across departments or groups at scale.⁵ This means mining years of matter data to identify patterns in case outcomes, analyzing advice given across similar matters, extracting fees and settlement data to improve early case assessment, and combining internal experience with external knowledge about judges and opposing counsel to provide more informed strategic guidance.⁶ This institutional intelligence becomes a competitive advantage.

On the collaboration side, firms and clients are developing interoperability models where legal teams and client stakeholders establish joint workflows and solutions.⁷ Some litigation practices are creating matter-specific digital workspaces where all critical evidence, key documents, and strategic analysis exist in one AI-enabled environment accessible to both teams.⁸ Instead of providing segmented advice on individual matters, these models allow firms to save time on routine tasks, establish workflows across matters, and use their expertise to advise an enterprise more holistically.⁹ 

The strategic value comes from combining both approaches. When firms can bring institutional intelligence to early case assessment—showing clients what similar matters actually cost, timeframe, and what strategies proved effective—while simultaneously incorporating collaborative tools throughout the matter, the relationship transforms.¹⁰ 

Nearly half of general counsel now express a preference for working with law firms that use AI, with many general counsels citing the use of appropriate technologies as a criterion when selecting external legal partners.¹¹ For in-house counsel evaluating litigation counsel, the questions become: Can you bring institutional intelligence from your prior matters to inform our strategy and planning? Can we work together using AI-powered tools that keep us connected to case development? 

The Verdict

Whether documenting results, building capabilities, or creating strategic advantage, successful AI adoption in litigation shares a common trait: the ability to generate evidence of value. The firms that can show their work—with metrics demonstrating how AI-powered workflows deliver better outcomes, how their training ensures quality does not suffer, and how their strategic use of AI provides competitive advantage—are not just more efficient, they are positioning themselves as litigation partners who bring valuable capabilities worthy of a long-term relationship.