In the rapidly evolving landscape of AI and law, expertise is not just claimed—it’s flaunted. Yet, how much of it is substantiated? One day you’re a contract law expert, the next you’re supposedly an AI guru. This rapid badge acquisition doesn’t just stretch credibility—it threatens the integrity of legal advice.
I am stressing this factor because mastering AI is not about learning a new subset of law; it’s about fundamentally changing our mindset and understanding how technology transforms practice.
To me, this is highly relevant for at least for three reasons:
- Depth of Understanding: AI isn’t a simple add-on; it demands a deep dive in prototyping, risk assessment, and technical dialogue—concepts unfamiliar to many lawyers. I recall a famous partner who didn’t know what MVPs and beta tests were, even while touting their firm’s prowess in tech and AI.
- Lack of focus. The goal isn’t just to become an AI expert. It’s about integrating AI with litigation, AI and contract law, AI and ESG. The AI revolution is not merely expansive—it’s invasive.
- Market Misconceptions: The presence of many experts led clients and institutions to believe that the legal field is more advanced in AI than it actually is. From my experience, there is still a long way to go.
Ok, assuming that expertise is an issue, and we need to identify an expert, how can we do it? How can we spot the acumen?
Here are my suggestions:
- Experience Over Exposition: Genuine experts have already a track record in AI projects, not just theoretical knowledge. If they’ve never navigated an internal policy or a risk assessment, their expertise is questionable at best. And – as a client – you may be their guinea pig.
- Foundational Knowledge: True AI proficiency requires an understanding beyond the surface. It’s about appreciating the nuances of data that fuel AI technologies. A lack of focus on data is a clear red flag.
- Depth vs. Breadth: There’s a significant difference between merely using AI tools (mostly in a basic way) and understanding AI principles and dynamics. Note that AI is not only generative AI. And generative AI isn’t only Chat GPT.
- Network of Connections: AI experts in the legal field often collaborate with developers, engineers, and designers, not just lawyers. I also stress that – while a lawyer can certainly become an AI expert, the traits that make a great lawyer—such as perfectionism, aversion to failure and competitiveness—can be detrimental in a flexible, prototype-driven environment.
- Love for Process Management: A sincere enthusiasm for process management (and hopefully statistics) is crucial for navigating effectively the realms of AI. If the professionals you are speaking with are not product or efficiency driven- start being skeptical.
As legal professionals, our challenge is to remain adaptable, curious, and informed. Above all, we must prioritize delivering the best service to our clients.
Our assumptions could potentially be their greatest harm.
