AI is proving to be the ultimate value-add for law firms
Jennifer Roberts, Data Scientist at Intapp, discusses how the opportunity for artificial intelligence in legal is ripe, especially in the area of client service from intake to business development and delivery of services.
By Jennifer Roberts, Intapp
The capabilities of AI have opened the doors for new opportunities across industries, playing on value propositions around efficiency and profitability to the point that not even law firms can ignore it anymore. The potential within a law firm certainly impacts the way lawyers practice legal work.
Legal research has changed dramatically over the years with the digitization of case law, statutes, and regulations (Harvard’s entire collection of case law is now available to the public!). ROSS Intelligence (IBM) is using Watson to perform legal research, training Watson to interpret law terminology. AI is also being leveraged to review contracts, and even offer intelligent contracts (based on a variable set). Products like Lex Machina provide lawyers with new insight in case work, offering a better understanding of outcomes against judges/jurisdictions/opposing counsel. Lastly, there is an efficiency play with things like e-filing, which allows for the prep and filing of court docs electronically.
The practice of law has been a focus of much of the AI available to firms today—at least the AI that has made its way to popular use. They’ve gone through the motions of the tech hype cycle and achieved the “slope of enlightenment” or, perhaps for some, the “plateau of productivity.” Arguably, some of it still has a way to go and it’s debatable where it stands, but AI for the practice of law is making its mark.
On the other side of the business of law, the journey on the hype cycle has just begun. All in all, the opportunity of AI in this space encourages the idea of raising the profile of the legal professional to do higher value work. The opportunity is ripe, especially in the area of client service from intake to business development and delivery of services.
Unique Areas of Focus
Looking outside of legal, AI has stepped in to help companies win more profitable business and foster deeper client relationships, as well as retain and cross-sell to clients. When considering that 80% of a firm’s revenue comes from 20% of the firm’s current clients, clearly this is an area worth investigating for ways in which AI can help. Firms are beginning to explore these areas, leveraging predictive analytics, automation and clustering models to drive relationships.
In areas like white space analysis, using data from financial management systems on the revenue generated within each practice for a client, as well as client’s demographic data, firms can begin to understand buying patterns for specific segments of clients (perhaps even developed through clustering). From there, predictive modeling allows firms the ability to understand a client’s propensity to engage a certain practice area that they are not otherwise engaged with at that firm (likely bringing that work elsewhere).
This same data also allows firms to predict a client’s likelihood of attrition and/or relative health with the firm. There is also the ability to forecast financial viability with the firm to help it understand the total addressable market (TAM). Any one of these alone has the ability to help a firm’s marketing and business development professionals transform from reactive to proactive, raising the profile of marketing and business development to now play a more strategic role in understanding the client, deepening (and even mending) relationships with clients and identifying where the largest opportunities are hidden for the firm. In our studies, while we’ve found that some of the knowledge around opportunities is known anecdotally, having the data to show the potential of what happens when you are able to identify two or more practices that are correlated —and then quantify the impact for the firm—brings a new level of meaning and action to the data.
Thinking about other areas of the client life cycle, intake and risk provide a clear opportunity for AI to make an impact. Based on our studies, the average large firm does about 1,500 searches per month and, on average, each search takes 62 minutes (between risk and the fee earning lawyer), equating to 1,550 hours per month. For the impact of scale, that is 7,750 miles walked (at a 12 minute pace)! The ability to predict if a new matter or client is a risk to the firm via AI has the potential to save serious time, considering our studies on the application of AI capabilities show that at its current state, 80% of decisions can be made by an AI model. This model can predict if the results from a search are a risk or not, equating to a time savings of 1,240 hours per month that can now be returned to the firm. The value model is based on the systematization of the process and highlights new efficiencies as humans and machines augment one another’s strengths. Using the model to assist with decision-making tasks helps prevent mental lapses and user inconsistencies. Moreover, that time savings now empowers risk analyst to add value elsewhere throughout the intake process.
Using AI Strategically
The shift of work allows for scarce resources to now be utilized in far more strategic, value-added ways. Not only can firms intake clients faster, but analysts can now spend time being deliberate about the clients and work they onboard. What does this mean for the firm? Ensuring that the type of work aligns with the firm’s strategy (is the work in a practice or industry that the firm is looking to expand their expertise, or in an area where the firm just made a large lateral investment), understanding if the work is profitable (yes, some client engagements are more about winning the work to begin the relationship but this is the exception not the rule) or if the client is a financial risk (like already carrying bad debt with the firm). These are just a few examples of where time can now be spent as opposed to sifting through searches.
The process shift also opens the door for more proactivity and collaboration around the client, which requires different departments to begin to work together. Collaboration is frequently cited as a barrier to most initiatives at firms: In a recent Intapp and Law Vision whitepaper, lack of collaboration among functions, as well as data, stood in the way.
We cannot ignore the culture at firms that make collaboration difficult, nor can we ignore the benefits of strategic alignment and the natural fit between intake and business development when it comes to serving the client in a differentiated way to win more work. Envisioning this, with the power of the AI mentioned prior, marketing and BD can engage on cross-selling efforts on a much larger magnitude with far more confidence than they once had with just a spreadsheet and Post-it notes. To bolster that confidence, they can work with the intake and conflicts teams to not just assess the potential conflict of a client or matter, but also assess if a client or matter is viable from a financial standpoint in terms of profit, and that the client doesn’t have a risk of carrying bad debt.
This also provides an opportunity to ensure that the work aligns to the firm’s strategy. If the work doesn’t make sense for the firm, isn’t profitable, or is with a client carrying debt the firm now has the added intelligence to know not to pursue the work. In another example around RFPs, think about the benefit from an ROI standpoint of knowing if a client or matter is even worth pursuing; the time savings alone for not going after an engagement that doesn’t make sense for the firm is worth it. Add in additional functions to this, like pricing, a firm now has a better understanding of what is being delivered (predicted and scoped through AI) and can monitor it, track the progress and help the lawyer and client to ensure delivery of value and satisfaction. This all comes from the benefit of additional time for higher-value work and collaboration, thus allowing the firm to up the game in how the client is being served, therefore deepening the relationship and expanding wallet share.
Yet, when asked about involvement between business acceptance/intake and pricing, marketing and business development during a flash survey at the recent LMA P3 event, only 62% said they have a slight amount (aka are process influencers) and 14% have no involvement, leaving only 24% remaining who claim to be moderate process stakeholders. No one had tangible collaborative involvement aka process ownership.
In order to fully realize the value-add in the shift of scarce resources that AI offers, process ownership is required in a collaborative manner. During conversations in focus groups, we have heard about the power of these groups collaborating around the client, but more often we hear the disbelief in how to make this work. The end game is realizing a better market position to not just compete, but also retain and grow clients through strong client relationships, all made possible by value-add of legal professionals provided by the efficiency and analytical power of AI.
Jennifer Roberts is manager of strategic research at Intapp. She has spent the last six years studying the application of data science in the professional services market. At Intapp, she is responsible for the analytics and research component that supports thought leadership as well as market and product strategy.