AI’s Transformative Power: Insights from Legal Innovators Satish Nori and Damien Riehl

 Transforming the Practice: Efficiency, New Models, and Latent Markets

AI is not just about helping clients; it’s poised to fundamentally alter how lawyers work and value their services. Satish Nori introduces his concept of the “80/20 inversion.” He explains that lawyers typically spend “80% of their time on the ‘how’ of legal work” (administrative tasks, procedures) and only “20% of the time is spent actually doing the lawyering”. AI, he argues, can flip this, allowing lawyers to spend “80% of the work that we want to do and leave AI to do all the rest of it,” which could significantly reduce the high burnout rate in the legal profession.

Damien Riehl challenges the common perception of AI as a threat (scarcity, a “tsunami”) and instead encourages thinking about it as “abundance”. Drawing an analogy to Jevons paradox, where cheaper LED light bulbs led to increased energy consumption, he speculates, “What if legal work were too cheap to measure?”. He believes that by shrinking unit costs, AI can unlock the “92% of legal needs that are unmet”—a market economists would call “a latent market that is just waiting to be exploited”.

Regarding compensation, Riehl asserts that the traditional hourly billing model, where “the slowest lawyer wins the race,” is “100% affected” by AI’s time savings. While hourly lawyers may dislike efficiency, “contingency fee lawyers, flat fee lawyers, subscription fees… all of them” embrace it. Riehl frames this as a stark choice for law firms: become “law firm number one that’s done this and stealing all of your competitor’s lunch or do you want to be law firm number 20 that doesn’t know why the phone stopped ringing?”. Nori supports this by citing the $1 billion spent annually on legal services in New York City’s nonprofit sector, which still fails to help “at least half the people,” indicating a fundamental flaw in how the “solution” is valued.

Navigating the Ethical Landscape: Transparency, Trust, and Competence

The conversation also tackled the ethical dilemmas and perceived perils associated with AI in law.

On the question of transparency—whether an attorney must disclose AI use—Satish Nori dismisses it as a “distraction.” He likens it to not needing to disclose the use of Lexis or Westlaw. Nori argues that lawyers already have an ethical obligation to ensure truthfulness and accurate citations. The only ethical concern, he states, arises if a lawyer bills clients at the same hourly rate while AI performs the work in “one-tenth the time,” which is inherently “dishonest” and “already unethical”. Damien Riehl concurs, humorously stating, “do I disclose right now yes I did in fact I’m sorry client I did in fact use spell check… of course not”. He declares that “large language models are the air we breathe”.

Riehl further delves into the blurring lines between legal information and legal advice, noting that large language models “can apply the client’s facts to the law quite well”. He suggests that clients always retain agency and that what lawyers truly sell is “less advice mostly and more trust”. Riehl emphasizes the human element: “humans usually want humans to look them in the eye and say ‘Your problem is now my problem I’m going to help you through this'”. Nori builds on this by suggesting that trusted entities like courts, governments, and legal services organizations should develop and host AI tools on their websites. He highlights his own experience with “Roxan” in New York City, a tool that provided legal advice without being challenged, because, he posits, “there’s no market for that service” from traditional lawyers. Riehl supports this by arguing that the “unauthorized practice of law statute was not ostensibly to protect lawyers incomes it’s ostensibly to be able to protect the public,” but in reality, “it was never about protecting the public it was always about protecting our incomes”.

When considering what lawyers are ultimately good for in an AI-dominated world, Damien Riehl points to the unique value of human judgment derived from “closed door meetings” and personal experience, which is not part of AI’s data set. Clients seek lawyers not just for legal precedents but for “those closed-door negotiations”. Satish Nori, however, urges lawyers to be realistic about their self-worth, stating, “there is no profession that thinks more highly of themselves than lawyers I would argue”. He advises lawyers to be “honest about our true value and where we add value” to solve real problems effectively.

Finally, the potential for attorney competence to erode due to AI reliance was addressed. Nori counters this concern with a powerful maxim: “don’t be an enemy of the future you cannot stand in the way of progress”. He asserts, “you’re not going to lose your job to AI you’re going to lose your job to someone who knows how to work with AI”. Riehl takes this further, suggesting that in the near future, “maybe not using large language model can be the act of malpractice”. He believes lawyers have an “ethical imperative to avoid malpractice” by leveraging AI. He concludes with an optimistic outlook: “Yes AI will take your job but it will take the worst parts of your job leaving you with only the best parts of your job”.