By Phil Shellhaas, Executive Vice President of Legal Solutions
Looking Back: The Evolution of Legal Technology
Reflecting on my career, I’m reminded of the countless changes in technology and their impact on our ability to serve law firms and corporate legal departments. There were moments when new tech felt truly groundbreaking. I remember the first time we started scanning documents instead of Copy – Label – Copy x 2—“Paper is dying,” we said. For those who recall the Bates stamper days, you’ll know the anxiety of skipping an integer and leaving a 10,000-page gap in your sequence. These memories are more than nostalgia; they’re lessons in how slowly the legal industry adopts change, even when the benefits seem obvious.
The Rise of Text Analytics and the Billable Hour Barrier
Over the past year, I’ve been pondering these experiences as generative AI takes center stage. It feels different from the first wave of analytics in the late 1990s, when platforms like Attenex, Content Analyst, Equivio, Stratify, and eView emerged. These tools introduced clustering, near-duplicate analysis, and “find similar”—precursors to categorization and predictive coding. I remember attending Legal Tech (now Legal Week) in NYC in the early 2000s, where every vendor was advertising e-discovery. By 2010, “predictive coding” was everywhere. The technology was advancing rapidly, but adoption was slow. Why? The billable hour. Increasing review speeds by 3x threatened the core business model of many firms.
One story stands out: In 2006, I was demonstrating an online review platform at an AmLaw firm. After impressing the attorneys with our printing capabilities, I showcased our new clustering feature, promising a jump from 50 to 150 documents reviewed per hour. The partner stopped the demo, ended the meeting, and politely walked me out. The message was clear: “Don’t speak that nonsense in these walls.” That moment left a dent, and I still joke about it today.
Predictive Coding Finds Its Place—Thanks to Case Law
Despite resistance, predictive coding eventually gained acceptance. It’s now widely used, especially after landmark rulings like Judge Andrew Peck’s opinion in Da Silva Moore v. Publicis Groupe (S.D.N.Y. 2012), which formally endorsed computer-assisted review. Judge Peck wrote:
“Computer-assisted review is an available tool and should be seriously considered for use in large-data-volume cases where it may save the producing party (or both parties) significant amounts of legal fees in document review. Counsel no longer have to worry about being the ‘first’ or ‘guinea pig’ for judicial acceptance of computer assisted review.” (NatLawReview).
Other cases, like Rio Tinto PLC v. Vale S.A. (S.D.N.Y. 2015), cemented technology-assisted review (TAR) as “black letter law,” with courts across the country permitting its use for document review. Protocols for TAR have been refined in cases like In re Broiler Chicken Antitrust Litigation (N.D. Ill. 2018), which laid out comprehensive validation and sampling requirements for TAR workflows.
Managed Review and the ALSP Shift
A fundamental change occurred as firms, under corporate pressure, stopped performing large document reviews themselves and engaged providers like Trustpoint for managed review services. This was a subtle resistance to technology and an alternative since the lawfirms were largely losing the business due to cost. Engaging a managed review provider still achieved plenty of billable hours for the attorneys in the firms overseeing the matter. Now, ALSPs use these tools in most reviews, especially for early case assessment, reducing data sets with advanced analytics.
Attorneys Get Savvier and the Curriculum Catches Up
Attorneys have steadily improved their knowledge of these tools, and providers like Trustpoint advise and consult along the way. In the early days, few understood text analytics; law schools didn’t teach electronic discovery until well after the 2006 Federal Rules of Civil Procedure even contemplated it. The technology was advancing, but the constituents who could use it were often “putting their head in the sand”.
Generative AI: The Tipping Point
Today, generative AI is everywhere—commercials, advertisements, conversations, and pundits. We’re immersed in Gen AI and its impact on legal practice. It feels like we’re at a tipping point for adoption in discovery and investigations. There will be no tolerance for ignoring the productivity gains these tools offer.
Anecdotes Meet Analysis: The End of Lawyers?
Years ago, Richard Susskind wrote “The End of Lawyers?”—a provocative book about legal process outsourcing and the rise of routine tasks being handled by offshore lawyers. While those businesses grew, large firms were largely unaffected. Susskind argued that lawyers must adapt, focusing on skills that cannot be replaced by technology or lower-cost workers. Today, we see echoes of this in the hybrid model: technology handles routine review, while subject matter experts provide strategic advice.
Case Law and Generative AI: Risks and Rewards
Recent headlines highlight lawyers sanctioned for using public AI tools to write briefs with fake citations. But positive case law is emerging, and it will grow as adoption increases. Document review is an obvious area for AI-driven productivity and cost savings, but strategy and advice remain the domain of attorneys. It will also become more utilized at the early phases of a matter to help reduce datasets at the outset of an investigation or litigation.
The Future: AI Embedded at the Source
Trustpoint has seen early adopters using the Relativity One aiR suite of Gen AI tools, with positive results. Relativity Fest announcements confirm that Gen AI tools will move further “left” on the EDRM, to the point of ingestion. As data volumes expand, productivity gains offset the explosion of sources—from word processing to audio, video, and chat.
Looking ahead, these tools will be incorporated into corporate document and communications platforms, identifying relevant information before it’s even exported. This could profoundly change the world in which many of us have made our living.
Conclusion
If history has taught us anything, it’s that legal tech adoption is shaped by more than innovation alone. The billable hour, client expectations, and evolving case law all play a role. As generative AI becomes mainstream, the legal industry must balance productivity gains with ethical and procedural rigor. Stay tuned—this time, it truly feels different.
References:
- Da Silva Moore v. Publicis Groupe, S.D.N.Y. 2012 (NatLawReview)
- Rio Tinto PLC v. Vale S.A., S.D.N.Y. 2015
- In re Broiler Chicken Antitrust Litigation, N.D. Ill. 2018
- Richard Susskind, The End of Lawyers? Rethinking the Nature of Legal Services