Priori sat down with Shmuli Goldberg, VP of Marketing at LawGeex, the award winning contract review automation software startup, and discussed how LawGeex is acing legal ops and why the future of the legal industry will be shaped by a metric-driven approach.
How is LawGeex improving legal operations?
There are multiple ways that I could argue how we're improving legal operations. The number one thing is that we are dramatically streamlining the incoming contract review process for day-to-day contracts, like NDAs and service agreements. These agreements tend to hold up the business because they can't get them signed without legal but legal has more impactful things to do. We streamline that entire process with AI and automation, and at the same time, we're giving lawyers back their valuable time to do strategic work. They don't want to be disturbed three or four times a day with “Hey, can you sign this? Hey, can you sign this?” We've built a platform which can automatically answer that question for you.
What has LawGeex aced in the last 12 months?
There are two things that come to mind. The first is that recently there was a study published by a collaboration between a couple of top US universities and professors that stated that our AI is more accurate and significantly faster than the average lawyer at reviewing every day standard legal contracts. The second thing is, which is probably more interesting, is when we released the story, we expected an industry shock. We expected people to go "Oh my God, I can't believe it. That's amazing." But what we actually saw time and time again was people responding saying, “Yeah, this doesn't surprise us. We've been using AI for the last three years. We knew these results. This isn't impressive to us.” For me, that was a huge eye-opener, as it showed that the industry is a lot more mature than most vendors realize. When most vendors talk about legal technologies and legal AI, they're saying things like: "legal tech is going to revolutionize the way we work and these technologies are going to change the way we practice law." What we've seen is that legal has revolutionized the way we practice law and legal AI and legal tech are now mainstream. It's no longer a question of the future is coming. All of these technologies are now here to stay. They're used as often as email and Microsoft Word. It's not a revolution that's coming, it's a revolution that's happened. And therefore our question to the market and our customers is, "what have you done so far?", as opposed to "what do you do next?"
As someone at a company that has really been at the frontier of pushing this game-changing technology, what innovation do you think will make the biggest impact on legal operations in the next five years?
I would answer that very clearly by saying it's not a technology. The biggest impact that I predict will is going to happen over the next three to five years within the legal operations space is the beginning of a metric-first legal approach, by which I mean benchmarks, KPIs and using numbers. The legal operations role in my opinion is going to be at its most successful when it's driven by metrics as opposed to qualitative data and workflows. This means customers knowing things like the cost of the contract or average billing rate or how many hours they bill or where can they optimize. That is not a technology, it's a mindset shift. The problem is not a technological one, the technology exists. Instead, the challenge is changing the mindset of practitioners of legal operations so that they know they need to optimize.
How would you define legal operations as an industry or as a discipline?
My background is not a legal one, it is in operations. I’ve spent a lot of time in the retail and travel and online spaces in the operations room. For me, operations is about the efficiency of the operation itself. Everything from workflows to cost management to time management to communication improvements. Operations practitioners are the people who make sure everything is running as it should and sometimes the delta between where things are and where they could be is a difference of 50% 60% 80%, and the legal operations role is to get them there. And sometimes the delta between how things are and how things could be is to 2 or 3% but those potential points are worth millions of dollars. So the legal operations role is the person that looks at legal where it is now, where it could be and what's the path to get there.
Both of the last two answers suggest that you don't think technology is the be all end all. Can you maybe point out for us what some pitfalls may be for a legal department adopting a technology like LawGeex?
I definitely can. The biggest pitfall, whether it's us or any other legal technology, is to adopt a technology and begin the onboarding process because you are interested in the technology or because you think it's cool or because you want to see it in action. I think the critical questions that businesses need to ask themselves before adopting any legal technology are: " What is the pain I'm trying to solve?” and “What is the best solution to that problem?" That solution could be technology. If the pain I'm trying to solve is I have customers all over the world and I want to be able to speak to them directly but at the same time I'm in a different country, then the solution might be email or phone system or Skype or Slack. Or it might be using a courier service. It might be flying across the world to sit next door to them for that important meeting. But if you take on a technology because you're curious to see what the technology is going to look like with no clear use case and with no clear success metrics in mind -- so you don't know what a successful pilot looks like before you start -- it can be very difficult to then have a successful pilot. Unless you are bringing in a technology to solve a specific pain or to improve a specific process, you have a much lower chance of success. On the flip side, if you do have a specific use case and you have benchmarks or metrics or a specific pain that you're trying to solve, then the onboarding process for any new technology or process or service can be much more effective. You can actually see a 10x return on your investment in the time you spend and the money that you spend if you know exactly what pain and what problem you're trying to solve. That would be the biggest possible advice I would give to somebody who's thinking of using any legal technology. As long as you know the problem you're trying to solve you're ready in a much better place.
You live and breathe AI. Can you help us separate the buzzy AI from the real robust AI?
“AI is magic until you know how it works, then it's just software.” That's a catch phrase that I've heard in the past that I like, but I would word it differently. The difference between traditional software and AI is that when you're building a traditional software system you define exactly what goes in and exactly what goes out. So the developer says when x happens, y is the result. With an AI system, the developers themselves don't tell the machine: when x happens, you do y. They let the machine work it out for itself. And more often than not if you turn around to somebody who built AI and ask "why did the computer make this decision?," they often won't be able to answer.
Are there cases where people are calling it AI, but it might not be truly?
It happens all the time. Before the AI boom, there was big data boom and every company was calling themselves big data. And it was irrelevant how big the data was. Before then, it was online. Everything was online. You were an online travel agent, an online this, an online that. Nowadays we just called them business. There will always be people that pick up on the latest buzz words and use it for promotional marketing. And to be honest, as annoying and frustrating as it is, it's not really a major issue in my book. The point is, does it solve my pain? If it does, then it's a solution. If it doesn't, then it's not. And the honest truth is the customer doesn't care either. They have a problem, they want a solution. They don't mind if it's humans or AI or traditional software as long as you're able to solve their problem accurately, efficiently, at the right cost, and in the right timely manner. In fact, I genuinely no longer care if somebody says they're AI or not. I want to know what the pain is they solve, the solution they bring to the table and the result at the end of the day.