Machine Learning for Law Firms: The Future of Time Recording

Published by Matthew Markham on Apr 02, 2020
Machine Learning for Law Firms: The Future of Time Recording

Artificial Intelligence (AI) has become an increasingly popular phrase in the commercial lexicon, along with other technological opportunities for law firms, from natural language processing to blockchain and quantum computing. While some of these tools are further away from reaching mass B2B adoption, an earlier version of AI, such as machine learning, has proven itself accurate and time-efficient in the completion of processes and interpretation of data. According to Statista, the AI market is predicted to see a 64% compounded annual growth rate (CAGR) from $1.62B in 2019 to $31B in 2025, the not too distant future. Even though still in its infancy, AI will change the face of law firms as we know them in the coming decade.

Machine learning, the increasingly accurate interpretation of data, is just the first step in the road to true AI, although it’s a tangible step, proving useful today. According to the well-known futurist Ray Kurzweil, machine learning and AI (along with other technologies), will generate as much output to GDP as manual labor by 2029. More information regarding that prediction and further background research here. For more information, here’s a link to the related Forbes article.

Extrapolation, pattern recognition and data collection are the three of main tenets of AI most relevant for law firms. We think of the technology as a gradual process, starting with robust data collection and standardization, followed by machine learning, and finally, true AI. True AI is a few years out at least, it’s hard to put an exact date on its emergence outside of theory, but what we can say for sure is that machine learning is available and adding value today. As an example, we apply machine learning to a scrubbed and anonymized database of legal bills that we’ve spent 15 years accumulating. Machine learning predicts appropriate billing codes for new legal invoice line items based on approvals and denials of line items from this large database, and of course, from ongoing feedback from our team. It’s getting better at predicting legal billing codes every day. Why is this feature important? Machine learning helps our law firm client's catch billing mistakes before they cost their firm revenue, profit and all associated time related to resolving any associated billing disputes with their clients. Machine learning can also be applied for our enterprise legal management clients to point out areas in their invoices where they’re being overcharged by their vendors, saving them ~6-11% per invoice. As of March 2020, our latest insurance client saw average invoice savings of 11.8% through machine learning-enabled legal bill review.

These are real dollars and cents, and while perhaps “small,” they very quickly add up. In the case of the last client mentioned, that’s ~$12 new dollars in profit per every $100 of invoices, on average. The same principle applies to law firms. Machine learning and artificial intelligence can undoubtedly navigate legal practice management from a cost center into a profit center. These points are mostly financial, but the time differences are also quite remarkable. In time recording, for example, machine learning-enabled natural language processing (NLP) can greatly reduce the time required for dictation. The modern technology available in speech-to-text formats is 95%+ accurate, and enough so that we’ve been comfortable demoing this capability on live calls, knowing an error would spell disaster. So far, so good. The existing market standards involve Dictaphones that are shared with paralegals or legal assistants for transcription, but we cut that part out, and enable these team members to work on more value add tasks in their law firms, maximizing time dedicated to billable hours and client service.

Usage of AI in law firms has even been discussed by legal technologist Richard Susskind – in his latest book, The Future of the Professions. Even though machine learning and AI may not be popular among senior lawyers, it is increasingly being adopted by emerging law firms as a competitive advantage, and we highly recommend giving Susskind’s book a read if this article caught your attention. Over the coming years, deep learning, a subspecialty of AI will prove to be an even more effective tool for time recording in law firms. For example, beyond just predicting billing codes, deep learning should be able to provide decision making feedback to maximize key performance indicators, such as profits or invoice compliance, as part of a sound legal practice management strategy. As part of that strategy, deep learning may tell a law firm partner to encourage morning billings, to get even more specific, as that could reduce error rates and maximizes client service capacity.

Finally, if you take nothing away from this article but this next statement, we’d be more than satisfied: AI and machine learning empowers lawyers and law firms, it does not replace them. We have seen countless cases of lawyers switching from private practice to in-house counsel roles, in large part due to the hassles of timekeeping and billing, and we believe technology can reduce that burden and make billing profitable.

If AI or machine learning is relevant to you or your company, we’d love to discuss how you can turn a new technology into your advantage. Feel free to reach out at [email protected]. or fill out our contact form.

Authored by:

Matthew Markham

Matt is an experienced writer, having learned his approach from time spent at Brown University and Oxford University's journalism course. He is the COO of Bilr, a leading legal billing application, and has authored a number of #1 Google ranked articles that have featured in CNBC, Forbes and Entrepreneur. His background originated in investment banking at Morgan Stanley, where he had first had experience looking at the inefficiencies of law in business today.

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