Published OnSeptember 10, 2018The legal AI evolution began several years ago. Firms that are not preparing to adopt AI applications will likely miss out on a competitive advantage.
The legal AI evolution began several years ago with the advent of predictive coding. In 2007 and 2008, predictive coding was used to scan large eDiscovery data sets to determine relevance and privilege. Predictive coding was based on mathematical algorithms that could learn from examples and training cycles. With computer training cycles, the error rate was 2 or 3% — much lower than human-reviewed documents. This same technology could be used in law firms to increase accuracy, reduce client costs, manage records, provide clients with case estimates more quickly, and develop a faster, more compelling ECA strategy. The Law Firm Information Governance Symposium published several reports in 2018, one of which was titled “AI in an Information Governance World.”
This report explores AI and machine learning for law firms in depth. Can AI benefit law firms? Can it benefit their clients? Does it break any ABA legal and ethical rules? Will clients accept the use of AI? Will the courts? Will opposing counsel? Will AI requirements be included in outside counsel guidelines?
AI Evolution in Law Firms
Law firms have become noticeably more interested in AI applications and how they might affect firms’ revenue streams while also benefiting their clients. However, many firms remain hesitant to adopt this new technology. Although firms want their clients to view them as modern and up-to-date, it’s been my experience that they don’t want to be on the technological cutting edge.
However, AI/machine learning offers many benefits to both law firms and their clients. A few benefits include more-accurate client document intake, correct attorney billable tracking and billing, automated information governance (IG), tighter security and stricter adherence to OCGs.
New Uses for AI in Law Firms
Predictive security — AI can be trained to recognize and maintain the client’s required level of security, placing specific access controls on the data and detecting and preventing breaches using predictive analytics. Predictive analytics harnesses data to predict future actions — a tool that could help firms foresee and stop hacking before it happens.
Predictive categorization — A computer using AI/machine learning could determine the owner of incoming or newly generated documents and categorize them accordingly. Predictive categorization could dramatically improve accuracy while also expediting the document-intake process.
Predictive information governance — Predictive governance is on track to eventually replace human IG professionals completely. Document retention/disposition is a notoriously inaccurate and inefficient process. Much like document review, human-based categorization and management of millions of records is highly individualistic and dependent on the human’s frame of mind and experience.
Legal and Ethical Rules of Using AI in Law Firms
Attorneys must be technologically competent when representing clients. Could attorneys become sufficiently competent in AI/machine learning theory to meet their professional obligations? In the past, attorneys mainly needed to be familiar with keyword use, metadata preservation and mobile devices. In the last few years, they’ve also needed to achieve basic competence in ESI, encryption, cloud services, predictive coding and social media. But, for instance, courts took years to accept predictive coding for document review, and they will be similarly slow to accept AI.
The Downside of Technology Conservatism
The AI revolution will help law firms enhance IG quality, reduce the time to delivery of legal products and services, and deliver those products and services at a lower price. Firms that are not preparing to adopt AI applications will likely miss out on a competitive advantage and lose clients who consider them behind the times.