In the previous lesson, we opened our miniseries on Legal AI, looking at why clients are potty for it and identifying its big deficiency. Now, in this “Great British Bake Off” inspired lesson, we move on to one of the most frequently asked questions: How will legal AI, law firms and their attorneys all co-exist in the new ecosystem?
Let’s say you’re a talented baker, you’re expecting guests for the holidays and you need to bake a cake. As a good host, you know your guests, their preferences and needs. So let’s get baking. Happily you don’t have to grow any wheat flour, wait for chickens to lay eggs or light a fire. You have the basic assets and tools at hand, so you can go ahead and apply your talent to create your cake — in your way — for your guests.
Legal AI, LPM, Lean Adviser and the other transformative solutions all work the same way. They are all built on a generic “cake mix” basis. They are “white label” products which law firms can adapt in their own image and brand accordingly. Some magic circle firms are investing in their own proprietary AI solutions, others will rent and modify, but the raw ingredients are just that, raw.
Likewise at the lawyer level, attorneys can harness these assets to their own talent in service of the client’s problems. This is the key to understanding the future of lawyering. There will be a job for humans, but it just won't be the same job. The decades of partners building a book by getting teams of associates doing research, writing memos and doing doc reviews are coming to an end. There will still be lawyers and books of business, but lawyers will have to work in harness with legal AI.
The role of the lawyer will be defined precisely along the principles of Lean LPM (legal process management). The future lawyer will be an experienced and savvy interface between the client and the machine. Here’s our predictor sheet as to what the job of an attorney will look like:

  1. Specialize in the client, to understand their culture, products, people and processes (as now);
  2. Consult with the client to help them identify the real problem (as now);
  3. Understand the client’s risk appetite, manage their expectations and get aligned on what good will look like to them (as now);
But then

  1. Formulate the right questions to input into legal AI;
  2. Analyse the output from legal AI, sense check it and adapt it for your operational needs;
  3. Create a project plan and get client buy-in;
  4. Monitor your execution of the plan, detect and correct error estates; &
  5. Learn and improve, just like your self-learning legal AI.