This newsletter is a key component of our proprietary AI Strategy Exchange program, which is offered in partnership with LawVision’s Strategic Pricing, Profitability and Data Science Principal Mark Medice. This newsletter is crafted to be succinct and focused, highlighting what we believe to be essential reading related to the latest news about AI strategy. We take the readings a step further by contextualizing their ideas within the legal sphere, tailoring insights specifically for law firm leaders.

July 3, 2024 | 🕐 5 Minute Read

Strategic AI: Getting Real with AI in Legal

This week, we review Harvey AI, which continues to impress with its capabilities yet remains enigmatic, raising questions in a recent Law.com article. Next, UK law firm Ashurst has documented significant productivity improvements through their legal technology automation efforts. Finally, we highlight a recent Wall Street Journal opinion piece that questions the sustainability of the current AI boom.

🚨 Must Read

The Hype Behind Harvey: How Firms are Using the GenAI Startup

Source: Law.com (requires login)

Our Take: This part two of a series explores the intricacies of Harvey AI, shedding light on its foundations and presenting key use cases in prominent law firms. AI technologies, like Harvey AI, often suffer from unnecessary mystique. The article argues that simplifying and clarifying AI can enhance its accessibility and usefulness. It highlights law firm use cases for Harvey AI, including workflow automation, legal research, and operating legal assistants like chatbots. International law firms like Gleiss Lutz, Reed Smith, Macfarlanes, Cuatrecasas, CMS, and Paul Weiss are testing this application.

Key Points: A balanced AI strategy is crucial, combining custom solutions aligned with your firm's goals and proven off-the-shelf tools to avoid over-reliance on vendors. While practical applications of Harvey AI look promising, we advocate for greater transparency in real-world deployments and vendor marketing. Demystifying AI through transparency and practical use cases enhances its accessibility and value. So, maintain a healthy skepticism about new tools until their results are proven, especially given current studies revealing AI's limitations alongside its potential.

🔎 Deeper Read #1

Can GenAI Really Cut Lawyers' Time in Half?

Source: LawFuel

Our Take: This LawFuel article explores critical questions about generative AI: will it boost productivity, and what are its implications for the future of legal jobs? It highlights studies by the UK law firm Ashurst, revealing significant time savings through legal tech AI tools. Trials demonstrated remarkable efficiency gains: 80% in drafting UK corporate filings, 59% in industry research reports, and 45% in drafting legal briefings. These results stemmed from global trials conducted between November 2023 and March 2024. Ashurst's trials also assessed the quality and accuracy of AI-generated content, which performed well but exhibited more variability than human output. Productivity boosts for certain tasks were noted to be up to 33%.

Key Points: These findings are compelling and demonstrate various approaches to leveraging AI technology to advance strategic goals. While the results are impressive, significant advancements take time and progress incrementally. Discussions about AI often focus on headline-grabbing themes like job displacement, but the reality is that AI integration is about transforming law firm business models, resourcing, pricing, rewards, firm structure, and capital allocation. Focus on the practical applications and design your strategy accordingly.

🔎 Deeper Read #2

The AI Revolution is Already Losing Steam

Source: The Wall Street Journal

Our Take: This Wall Street Journal opinion piece argues that the AI revolution is already losing momentum. It cites several factors: the slowing pace of improvement due to a lack of new data to enhance models, the high costs of building AI models compared to the limited returns, and the significant "last mile problem," where progress faces diminishing returns (i.e., five steps forward, four steps back). Additionally, the piece highlights the commoditization of AI, where competitive advantages diminish, and success depends more on cost-cutting than innovation. The high operational costs of running AI models, which far exceed revenue, and the slow and narrow adoption of AI applications despite widespread interest are also pointed out.

Key Points: While the article presents a skeptical view, it raises valid concerns that should not be ignored. However, this should not deter teams from diligently exploring and implementing AI technologies. The rapid gains seen in recent years may slow down as the technology matures, but this doesn't diminish the importance of continued effort, strategic thinking, and execution. The AI adoption and integration journey will likely be complex and non-linear, requiring thoughtful and sustained investment. While the AI hype may get the headline, the technology's long-term potential remains substantial. Firms should proceed with a balanced approach, recognizing challenges and opportunities, and commit to steady, strategic investments in AI capabilities.