Litigation Enters Its Agentic AI Era - The National Law Review

Generative AI moved into legal practice faster than almost anyone expected, most visibly through tools that draft documents, review contracts, and accelerate research. The early skepticism was not misplaced. It was the profession doing what it is trained to do: asking what happens when the tool is wrong. That question has not gone away. It has become the defining one. The capabilities reshaping legal work so far are only the first stage of a larger shift.

The emergence of agentic AI signals a shift from systems that produce static outputs to those that actively support attorneys in real time. Agentic AI works alongside the attorney as events unfold, taking direction and surfacing what matters in the moment. Nowhere does that distinction count for more than in litigation, where the stakes are high, the setting is adversarial, and the most consequential decisions are made in real time, not at the desk afterward.

From Output to Active Participation

At its core, generative AI is reactive: it produces briefs, outlines, or summaries in response to prompts. These tech solutions have already transformed deposition preparation. Rather than manually reviewing documents across fragmented systems, attorneys now operate in integrated environments where case materials are ingested, organized, and analyzed holistically. AI surfaces key facts, identifies thematic connections, and generates deposition questions aligned with defined legal strategies, driving not only efficiency, but tighter alignment between preparation and case objectives.

Agentic AI expands this capability by working alongside attorneys as events unfold. It delivers context-aware, results-focused assistance in real time. This is an especially meaningful distinction in high-stakes, fast-paced litigation, where timing and adaptability are critical.

Depositions as the Agentic Inflection Point

Depositions sit at the intersection of structure and unpredictability. While attorneys can prepare extensively, success in a deposition ultimately depends on how effectively they respond in the moment. Agentic AI is uniquely suited to this challenge.

Operating alongside live testimony, agentic systems can monitor exchanges in real time, track whether key topics have been addressed, flag inconsistencies with prior statements, and surface lines of discussion that warrant deeper inquiry. Querying the system during a deposition is not a departure from how attorneys already work; it is an extension of it. A litigator consults an outline or scans prior testimony before moving to the next line of questioning. Asking an agentic system whether a topic has been fully covered, or whether an answer contradicts an earlier statement, fits the same rhythm: a beat between questions, not an interruption of them. The difference is that the system can check a single answer against thousands of pages of records in the time it takes to glance at a notepad.

After the deposition, these systems integrate transcripts, notes, and AI-generated insights into a unified workflow, reducing lag between execution and analysis and enabling faster, more informed decisions on next steps.

Together, generative and agentic AI fundamentally reshape deposition work. Attorneys are no longer reliant solely on instinct and post hoc review. Instead, they benefit from strategic preparation paired with continuously updated insights as testimony unfolds.

Improving Litigation Workflow

Litigation provides a compelling proving ground for AI systems to function not as passive tools, but as active collaborators. Traditional litigation workflows were linear: preparation, execution, analysis, each phase largely discrete, with limited feedback loops.

Agentic AI moves litigation toward a more dynamic model. Preparation and execution operate in tandem, informed by real-time insight, with AI serving as the connective infrastructure that keeps information synchronized and decisions actionable throughout the process.

Technology Coupled with Experience and Trust Wins

Through research and conversations with legal teams, a consistent pattern has emerged: they are choosing the tools they would stake their matter on, and they are choosing for reliability, not novelty. What they want is the system that behaves the same way every time, without surprises. A firm's first obligation is to its client, which makes an unpredictable tool a risk before it is ever a gain. And that standard rewards experience. Reliability is not a feature you ship; it is a record you accumulate, built over years of accurate work, deep expertise, and partnership with the firms that depend on you. A new entrant can match the technology. It cannot manufacture a track record or the trust that comes with it. The providers who have earned reliability, expertise, and a long relationship with law firms will supersede the ones arriving with neither.

Reliability answers part of the question. Accountability answers the rest. In a profession built on liability, the gate on adoption is not whether the technology works, but whether a human can stand behind it when it fails. An AI cannot be sued, sanctioned, or disbarred, so responsibility stays with a person. The tools that earn a place in legal work are those built around that fact: the system surfaces, the attorney decides. And it does not change as the technology improves. Accountability moves up, not away, from the work to the professional who signs off on it. Capability describes what a tool can do. Accountability determines what the profession will allow it to do.

Rethinking the Legal Services Business Model

The rise of agentic AI also challenges the assumption that greater efficiency will reduce demand for legal services. In litigation, the opposite is likely to be true.

Disputes are increasing in both volume and complexity. Norton Rose’s 2026 Litigation Trends Survey, Perspectives from Corporate Counsel, found that 82 percent of corporate counsel managed at least one high-stakes lawsuit in the past year, yet only 29 percent feel very prepared to manage litigation in the year ahead. Half expect verdict amounts to rise, underscoring heightened risk exposure. These findings build on the firm’s 2025 survey, in which more than 80 percent of respondents reported that settlements have become more difficult to reach, citing rising legal costs, regulatory pressure, and escalating settlement demands.

With the United States legal services market estimated at $380 billion in 2026 and projected to reach $437 billion by 2031, litigation services, including depositions, records analysis, and case preparation, remain essential. Increasingly, competitive advantage will hinge not on whether these services are offered, but on how effectively, reliably, and intelligently they are delivered.

Agentic AI enables legal teams to manage complexity at scale. It allows firms and litigation support providers to handle more matters, extract deeper insights, and deliver more consistent outcomes without a proportional increase in costs. In this sense, generative and agentic AI serve as force multipliers, not substitutes, for professional judgment.

The Emerging Divide

As with previous waves of legal technology, adoption of agentic AI will be uneven. Some firms will integrate these solutions deeply into deposition practice and broader litigation strategy, while others will continue to rely on more traditional, static approaches. For legal services providers, this creates a new axis of competition, and it will not be won by whoever deploys the most AI. It will be won by whoever is trusted to deliver it reliably.

Market differentiation will increasingly depend on the ability to embed AI into live workflows, not merely to accelerate document production, but to support better-informed, real-time decision-making. Clients will come to expect not just efficiency, but responsiveness and insight throughout the litigation process. The firms that pull ahead will be the ones that use AI to sharpen the judgment their clients are paying for, not to replace it. Real-time insight is the tool, while the lawyer's judgment remains the product.

Looking Ahead

The trajectory is clear. The first wave of AI in law focused on what machines could produce. The next will be defined by their participation in the matter. But participation is not the same as winning. Capability will be everywhere, and the moment it is, it stops being a differentiator. What separates the leaders is older and harder to copy: a record of reliability, the expertise behind it, and a human who stays accountable when it counts. Agentic AI is reshaping litigation. Who it rewards will be decided by trust.