The legal industry is undergoing a transformation as large language models (LLMs) powered by artificial intelligence become integral to the practice. Law firms, especially those in Big Law, are rethinking traditional billing models like the billable hour in favor of technology-driven efficiencies. This shift presents an opportunity for the legal sector to evolve into a software-as-a-service (SaaS) model, where firms develop custom LLMs that they can license to clients and other law firms. Although this concept might seem unconventional, it aligns with current trends and market demands, suggesting it might soon become a viable option.
Prominent law firms are already hiring experts in artificial intelligence to assist in this transformation. Firms such as Dentons and Gunderson Dettmer are combining legal expertise with technological proficiency to craft in-house solutions. Similar moves are being observed among corporate giants like JP Morgan Chase & Co., Deloitte, and McKinsey & Co., which have developed proprietary chatbots for internal applications. These efforts reflect how the overarching trend towards AI-enabled solutions is pressing legal professionals to explore new business models (see full article on Bloomberg Law).
- Legal AI companies like Harvey and Leya are rapidly advancing their models by focusing on legal-specific data, often recruiting former Big Law attorneys to help improve the AI’s performance through new datasets.
- While AI enterprises work externally, the most precious data lies within the law firms themselves. Legal documents, case histories, and research accumulated over decades present invaluable resources for fine-tuning LLMs.
To fully utilize these resources, Big Law firms could create LLMs that exemplify their unique legal methodologies and strategies. One fundamental shift would be transforming lawyers’ tacit knowledge and decision-making skills into structured data, suitable for training AI. Capturing the intricate processes that experienced partners use, such as strategic planning and task allocation as they navigate complex legal scenarios, would propel AI to a new level of operational intelligence.
Despite these prospects, the road to a SaaS model is not without hurdles. Technologically, AI still lacks the precision for autonomous tasks such as legal research and document review, although recent advances offer a glimmer of hope for overcoming these issues. Ethical considerations also loom large, notably whether it’s appropriate for firms to train LLMs with past client work products. As firms encounter increased efficiency from AI, as well as economic pressure from reduced billable hours, the rationale for embracing a SaaS model becomes more compelling.
In conclusion, Big Law firms can position themselves at the forefront of this technological evolution by beginning to lay the groundwork now: retaining critical data, converting processes into structured content, and addressing ethical considerations around data use. Firms which act early may find themselves leading the industry into a future where legal services are not just supported by technology, but delivered by it.
For further insights, Oliver Roberts at Holtzman Vogel provides a detailed analysis in the Bloomberg Law article.