Home > Artificial Intelligence (AI) > Can Law Firms Gain a Sustainable Advantage with AI?
The article Investing in AI? Strategy Principles Say Go Lightly and Later by Hugh Simons in the American Lawyer (18 May 2018) argues that law firms cannot gain a sustainable competitive advantage by investing in artificial intelligence (AI). I question his thesis in this post.
You’ll see interesting apps built by law firms in the @fastcase AI Sandbox this year. Third-party AI apps will be the new floor (think eDiscovery) – but the applications firms build with their own (non-commodity) data & expertise will become differentiators – the new ceiling.
A couple of others chimed in, agreeing with Simons that one cannot gain competitive advantage from AI and firms should focus on offering clients the best service by whatever means necessary. Personally, I am on the side of Ed and Alex: I do see how building tools, especially with proprietary data or expertise, can create sustainable advantage.
I like this point and agree with Noah. I have argued in the past that large law firms have few apparent advantages from size. Recently, however, in the age of Big Data, I tuned that argument to acknowledge that access to vast amounts of data in bigger firms can be an advantage.
Don’t we see firms sustaining competitive advantage over the long term because of their better expertise and execution-skills? (Lots of examples of high end firms and their best practice groups.) would AI customization and ability to use be any different?
I would say totally opposite. @seal-software it’s about allowing secure shared models. To reduce over fitting of data. If law firms only ever use the data they have. The models will never be as good as if a shared global model is created. But with Data ownership retained.
First, on form, This is a great example of Twitter at it’s best, with multiple points of view and a robust conversation. Of course, following it all on Twitter can be hard as Tweet threads can split, as happened here. And not all Tweets may be fully formed or completely argued points (that certainly applies to mine). So forgive me if I have misconstrued (or omitted) any Tweets on this article spawned by my Tweet about it.
Second, on substance, I find the views of Ed, Alex, and Noah persuasive: either by building unique AI systems (or products) or by harnessing huge amounts of data and applying expertise in training, I do think that larger firms can gain a sustainable competitive advantage.
Kevin raises a good point though about aggregating data. I would need, however, to understand the ownership model of the training in more detail to comment further on that.
I see a future where it’s even possible that firm-built AI tools or big-data-powered + custom-trained commercial AI tools become a virtuous circle. What does that mean? Think about high-end practices today. Many firms can handle a deal or litigation but only a handful have the experience to handle the biggest and most complex deals and litigation. They tend to get that work and therefore maintain the experience advantage over time. Why won’t AI be the same and create the same advantages?
I think it’s terrific that the Twitter discussion focuses on differentiation. It’s great that all agree that this is the key issue. And I’ve no monopoly on truth, so I respect that others’ views differ. I read the counter argument to my point being that the customization of the 3rd party applications will create differentiation. This is entirely logical and reasonable. I confess I don’t foresee this happening though. Why? Because it didn’t happen when people made the same claim with other technologies I’ve seen over the last 25 years–it didn’t with ERP systems (SAP, Oracle, etc.) for industrial companies, on-line banking solutions for retail banks, or e-discovery solutions for law firms. Rather, AI will become table stakes–a must have for sure, but not a differentiator. Hence, the time to invest is when the ‘must have’ becomes a ‘must have’, which is later rather than sooner.