The Future of Technology in Litigation Support: Why AI Is Becoming Co-Counsel


The most disruptive force in modern litigation is not a new statute or procedural rule.
It is the quiet rise of AI-powered litigation support solutions—systems that are fundamentally reshaping how cases are built, evidence is managed, and clients are served.

From my vantage point as Moses Cowan, the profession is operating in two timeframes at once. Courts and counsel still move at a human pace. Meanwhile, software can read millions of documents in hours, surface issue frameworks in seconds, and detect risk patterns no trial team would ever spot at 2 a.m.

That divide is closing rapidly. A recent global survey shows that legal organizations actively integrating generative AI jumped from 14% in 2024 to 26% in 2025, with 45% expecting AI to become central to their workflow within a year. ([Best Law Firms][1]) The future of litigation support is not theoretical. It is already underway.


Why AI-Powered Litigation Support Is the Defining Trend

Litigation support once meant war rooms, banker’s boxes, and spreadsheets.
Today, it means platforms capable of ingesting massive volumes of email, chat data, databases, and cloud files—then classifying, clustering, and prioritizing the most relevant material in a fraction of the time.

The global eDiscovery market alone is projected to reach $18.7 billion in 2025, with growth expected to exceed $39 billion by 2032. ([Fortune Business Insights][2]) This trajectory reflects a simple reality: nearly every dispute now turns on electronically stored information. AI is no longer optional. It is infrastructure. ([Grand View Research][3])

Industry sentiment confirms this shift. Seventy-seven percent of litigation support professionals identify AI adoption as the most consequential trend of the next five years, and 43% expect firmwide AI usage to increase again in 2026. ([U.S. Legal Support][4]) This is not hype. It is consensus.


From Paper Chase to Pattern Recognition: A Practitioner’s View

I trained in an era when “litigation technology” meant faster printers and better databases.

Today, I treat AI as a junior associate that never sleeps—exceptionally fast, tireless, and often brilliant at identifying patterns across massive datasets, but still in need of careful supervision. AI is literal. Sometimes wrong. And entirely dependent on the judgment of its human operators.

In one matter, my team confronted a dense web of emails, text messages, and transaction records that would have taken months to manually untangle. Using an AI-driven review engine, we clustered communications by date, actor, and subject. The system surfaced a small set of “anchor threads” that reframed the case narrative.

We still read every critical document. We still verified every inference. But we began with signal instead of noise.

That is the real value of AI in litigation support: not replacing judgment, but reordering attention.


Litigation AI as an Operating System, Not a Gadget

The firms that will lead are not those that merely “buy AI.”
They are the ones that treat AI-powered litigation support as a foundational operating system for case work.

That system has four essential layers:

  • Evidence intelligence
    Tools that enrich documents with entities, timelines, themes, and sentiment while maintaining live, auditable chronologies.
  • Strategy augmentation
    Systems that summarize depositions, stress-test theories, and model likely opposing arguments.
  • Process automation
    Structured workflows for discovery drafting, privilege logs, status reporting, and motion support.
  • Governance and auditability
    Clear records of model selection, prompt usage, validation steps, and human review before any court-facing use.

This is not a single product. It is a litigation technology stack supporting every phase of a dispute—from intake and early case assessment through discovery, motion practice, settlement analysis, and trial preparation.


Market Signals from 2025: This Is Already Happening

The broader market confirms what practitioners are seeing firsthand.

Major law firms are now appointing Chief AI Strategy Officers and forming permanent AI governance teams to redesign litigation support and legal service delivery. ([Reuters][5]) These are not experimental roles. They are executive decisions.

At the same time, legal-tech litigation is emerging. A recent lawsuit alleges improper use of proprietary legal databases to train AI models, underscoring the growing tension between innovation and intellectual-property protection. ([Reuters][6])

Meanwhile, adoption is already outpacing policy. Thirty-one percent of legal professionals report using generative AI at work, even as many firms lack formal usage guidelines. ([Federal Bar Association][7]) Demand is ahead of governance—but governance is catching up.


Ethics, Risk, and the Expanding Duty of Technological Competence

AI introduces powerful efficiencies—and real risks.

Hallucinated citations, biased datasets, and insecure deployment can compromise a case or breach client trust. In response, courts and regulators are emphasizing:

  • Verification — AI outputs must be checked against primary sources.
  • Transparency — Judges increasingly expect disclosure of AI use.
  • Confidentiality — Sensitive data must remain in secure, controlled environments.

This is not a departure from professional responsibility. It is an extension of it. The duty of competence has always required lawyers to understand the tools they use. The tools are simply more advanced.


A Practical Roadmap for Litigation Teams

For litigators, in-house counsel, and legal-operations leaders, the path forward is pragmatic:

  1. Launch a focused pilot
    Start with a high-ROI use case such as AI-assisted document review.
  2. Define data and security boundaries
    Decide what data can leave your environment—and what cannot.
  3. Build human-in-the-loop controls
    Mandate human review for privilege decisions, settlement analysis, and court filings.
  4. Train people, not just platforms
    Teach attorneys to supervise AI outputs, not passively accept them.
  5. Measure performance
    Track efficiency gains, error reduction, and client outcomes.

Done correctly, AI becomes less visible—but more essential—a silent backbone of modern litigation practice.


Litigation Support as a Living System

The future of litigation support will not belong to any single platform.
It will belong to ecosystems: interoperable tools, structured data, and teams skilled at orchestrating both.

From where I stand, litigation teams are evolving into systems designers as much as advocates. We will continue to argue law and facts. We will also design workflows, validation protocols, prompt libraries, and governance frameworks.

Tomorrow’s litigation department will resemble a control room, not a file room—dashboards tracking risk, timelines, AI queues, and strategic inflection points. Technology hums quietly in the background. Human judgment remains decisive.

Handled with discipline, AI-powered litigation support solutions will not diminish the lawyer’s role. They will sharpen it.


FAQs: AI and the Future of Litigation Support

Will AI replace junior litigators?
No. AI replaces low-value tasks, not legal reasoning. Junior attorneys will reach higher-order work faster, not disappear.

What is the safest way to begin using AI in litigation?
Start with narrow, supervised applications—summaries, clustering, chronologies—with mandatory human review.

Can smaller firms compete without big-law budgets?
Yes. Subscription-based AI litigation platforms level the field. Standardization and smart deployment matter more than scale.


Cowan Consulting, LC is a boutique professional services and consulting firm founded by Moses Cowan, Esq. Moses Cowan is a polymath and thought leader in law, business, and technology, dedicated to advancing innovative solutions at the intersection of legal strategy and emerging systems. Follow this blog at www.cowanconsulting.com/WP and learn more at www.mosescowan.com.