Will AI Disrupt Global Law Firm Rankings?

 Will AI Disrupt Global Law Firm Rankings?


Ranking law firms is a very serious business.

Law firm rankings or league tables are generally perceived as a vital indicator of status, achievement, capability, stability, and so on. They represent a plethora of characteristics about the presumed overall worthiness of a law practice. Clients are influenced by where a potential law firm ranks, and aim to select one accordingly. Fresh law school graduates frequently use ranking lists to decide where to apply for their starting job.

However, the various ranking services use a wide array of metrics. Little if any standardisation or even concurrence exists regarding which metrics ought to be used.

Results according to method?

Sometimes metrics are ostensibly transparent and consist of strident quantitative measures. These include the number of lawyers employed, profit per partner, revenue per partner, and other countable elements. For example, the annual Global Law Firms 200 listing produced by Law.com states that they undertake their ranking by collecting stats of “the world’s largest firms by revenue, headcount, and profits per equity partner.”

But there are also less quantitatively buttressed measures that are primarily qualitative; client testimonials, opinion surveys, and the like. Rarely is just a single metric utilised. Instead, a broadly based composite is devised. The result tends to produce rankings based on a proprietary and at times byzantine methodology.

For example, the U.S. News – Best Lawyers ranking is vaguely described as using an “evaluation process that includes the collection of client and lawyer evaluations, peer review from leading attorneys, and review of additional information provided by law firms as part of the formal submission process.”

The popular and revered Vault Law 100 rankings similarly indicate that they create a shortlist of ‘top law firms’ by reviewing responses to past surveys and published rankings (their own and others), as well as consulting other legal publications and professionals. They ask their shortlisted firms to complete an online survey of their associates. The final rank is based on the average score of these surveys. Vault overtly indicates that their approach is subjective: “Remember that in the Top 100, Vault is not assessing firms by profit, size, lifestyle, number of deals, or quality of service; we are ranking the most prestigious law firms based on the perceptions of practicing lawyers at peer firms.”

The odds are that approaches to rankings will continue somewhat unabated and will, like a meat grinder, be used axiomatically to routinely churn out updated sets of rankings year after year.

That said, new methods will emerge, shaped around gradual evolution in the legal profession and present-day practices. Consider a novel ranking scheme discussed by researchers Leonardo Ribeiro and Daniel Figueiredo: it involves examining the potential of ranking law firms and lawyers’ case effectiveness using statistics. ‘Can the network structure alone reveal the most effective and also influential lawyers in the labor court of the state of Rio de Janeiro?’ they asked in the Journal of Brazilian Computer Society in 2017. Applying a modified version of an algorithm used by Google to rank websites they sought a method for discovering effective and influential lawyers based on how many times they had defeated their peers in court.

In short, innovative technology, such as large-scale databases and algorithms, is likely to inexorably provide new ways to calculate rankings. One technology that could have a similarly demonstrative impact on law firm rankings is Artificial Intelligence-based Legal Reasoning (AILR).

AI’s impact on the practice of law and on ranking law firms

Artificial Intelligence (AI) is gradually becoming a handy tool for aiding lawyers in myriad ways, including being able to find viable solutions to vexing legal problems. There are AI-based e-Discovery apps that can rapidly search legal documents and ferret out crucial legal discoveries for a given court case. There are Natural Language Processing (NLP) front-ends available for lawyers to use when accessing voluminous datasets of prior legal cases. The AI-based NLP can ease the burden on non-tech-oriented attorneys and accelerate a review of legal precedents.

AI will enable faster lawyering, make it more productive, improve its quality, lower its cost, and have other similar substantive impacts, as I argued in the Robotics Law Journal in 2020. This will have considerable impacts on law firms.

Just imagine a law firm that is well-armed with appropriate AILR versus a law firm that eschews its use by remaining rooted in everyday conventional means. The AI-infused law firm can potentially do as much if not more legal work than the unarmed law firm, at least on a per-lawyer basis.

How would these two firms compare in league tables? If a metric such as the number of lawyers is used to rank them, the results would potentially miss the mark because the headcount is an insufficient measure of efficiency. Depending upon the multiplying factor of AI-using lawyers, the tech-savvy law firm could have fewer lawyers but be more productive than the firm with more professionals on the payroll. Law firms rankings will inevitably be revamped to reflect the AI-infusion advantages.

Surveys will likely begin to include questions about whether a given law firm is using AI. Clients are bound to express favoritism toward AI-using law practices as the expectation is that AILR will decrease the cost of legal services and boost responsiveness and the speed of their legal guidance. Law firms that drag their feet on AI are likely to be perceived as stodgy and outdated and slide down the rankings accordingly.


Admittedly, we have not reached this point yet. The factoring of AI into rankings is still in its early days.

Nonetheless, in the future AI will become a cornerstone for practicing law and will ultimately be disruptive to the existing lawyering practices. This disruption will transform ranking services’ structures and methods to include AI adoption factors. Expect a shake-up in how law firms are stacked and racked in the eyes of the legal community and the general public at large.


Image credit: mohamed_hassan, under Pixabay licence.

Lance Eliot

Dr Lance Eliot is CIO/CTO at Techbrium Inc., overseeing all digital systems efforts. Previously, he was a CIO at a major Venture Capital firm, a global retail services company, and a top tier home healthcare firm, and has been a successful entrepreneur having launched, run, and sold several startups. He is a frequent speaker at major industry events, author of over twenty books and three hundred articles, and a recognized thought leader on the subjects of Artificial Intelligence, Machine Learning, and also Autonomous Vehicles. He had been a professor at USC and UCLA, and holds a PhD from the University of Southern California.

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