As I previously posted, I spent last week at the ILTA conference in Orlando. Like just about every legal tech discussion and conference these days, talk about generative AI and its uses in the substantive end of law practice dominated. Lost in all this hype, though, a quiet revolution is going on with the use of AI and automation in the business end of the practice of law. Lots of developments to ease the burden of back office stuff like billing, collections, intake, and the like. All the administrative tasks that can’t be billed for but significantly impact the firm’s profitability.
While at ILTACon, I had the chance to talk to Doug Matthews, the Chief Product Officer of Aderant, a legal business management provider. Matthews was enthusiastic about some of these new administration use cases. As an example of the new, more sophisticated back office tools, Aderant launched an electronic automated billing platform called Onyx earlier this year. This platform takes such things as billing guidelines and automates their application into the pre-bill process.
The result is fewer write-offs for failure to comply with billing guidelines. That’s important because, in large firms, there can be numerous billing guidelines across the client mix. These guidelines are not consistent, and manual compliance takes time. This time is often exaggeerated since compliance with guidelines by timekeepers, especially in the heat of battle, can be spotty.
As Matthews also pointed out, the guidelines are often negotiated by different lawyers than the timekeepers on a given matter. Sometimes, the guidelines can vary by individual matter. So, keeping up with these can be time sink for lawyers who would much rather be working on billable matters than fussing with obscure guidelines. But failure to heed guidelines can result in reductions in bills and reduced revenue for the firms. Over time, these reductions can add up.
Aderant also offers electronic and paperless billing solutions that make getting bills out easier and reduce the time lawyers need to spend on them in general. I can tell from experience that for most lawyers, reviewing bills is the bane of their existence. Getting bills out sooner and with less lawyer time means increased revenue.
Aderant also offers programs to capture and manage expenses and ensure proper collection, among other things. These programs are all designed, as Matthews puts it, to “make the CFO’s job easier.
Back office tasks, if not done or done poorly, can doom a firm.
These programs are emblematic of what AI and data can do for what lawyers often see as mundane administrative tasks. But these tasks, if not done or done poorly, can doom a firm. For example, there may be ways to better determine the cost of taking certain types of work and matters in the first place. Similar programs could also be used to determine the experience and skill set of lawyers in a firm by looking at what they have billed for and how much time they spend on specific tasks. From there, firm management could make better decisions on how to staff matters.
Profitability is the third rail in lots of law firms
AI could also automate financial reviews to better forecast and determine the profitability of individual partners. Profitability is the third rail in lots of law firms. How do you measure individual profitability? Is a lawyer billing $3 million or more a year at $300 an hour more profitable than one who bills less overall per year but at a substantially higher rate?
How the question is answered often requires getting into the firm’s overall financial picture and needs. It also gets personal with the lawyers involved and leads to bickering and bad feelings. And that’s not to mention the compensation angle. How does and should a comp committee evaluate these differences? Lots of time and energy could be saved if there was a way to analyze financial needs and data and determine who is more or less valuable to a firm. AI and data analytics could do just that.
The more these tasks can be automated and augmented with AI, the more profit for the law firm
Another pain point for firms: most have DEI- programs but don’t measure the success (or lack thereof) of these programs. AI and data analytics could supply hard answers and reports showing whether the programs have the desired impact and, if not, how to change them. Moreover, clients increasingly demand that firms show them data evidencing DEI—improvement. Automating that task could save a lot of time and energy.
Back office tasks require staffing and resources. Law firms face the choice of hiring people to do this Work, outsourcing it, or trying to do it themselves. The latter is the worst solution since it takes time away from billable activities from which all revenue in most firms comes. But the more these tasks can be automated and augmented with AI, the more profit for the law firm. Back office work may not be as sexy as talking about generative AI, but the blocking and tackling work, the behind-the-scenes work, must be done.
And that work is crucial to a firm’s success.