Is there a role for artificial intelligence in the pricing of legal services?

Richard W Smith
GSJ Consulting Sydney
richard@gsjconsulting.com.au

‘Professional services’, whether that be accounting, engineering, architects or, in this case, legal services, are often referred to as being ‘credence services’. Which is to say, they rely heavily, if not entirely, on the ‘credibility’ of the person or organisation providing the service. The purchaser of your services, your customer, needs to be able to feel entirely confident (trust) that you have the skills and expertise necessary to be able to fix their problem.

Unlike the purchase of a product, say a pair of shoes, the complexities that lie behind the selection of a services provider primarily based on gut feeling, such as a lawyer, have historically made determining the pricing of that service a minefield of extremely difficult decision trees.

Consequently, for the past 100 or so years, deciding on how we will price our services has been more of an art form than a science.

Service providers are constantly battling issues such as:

• imposter syndrome;
• market demand;
• client budgets;
• the perceived versus actual value of the service being provided; and
• our competitors’ rates.

Add to this the fact that 99 times out of 100, the pricing of a service is determined by the service provider themselves (is there a conflict of interest here?) and not by any third-party overseer, thus it is not difficult to see that we are currently insecure about and unprofessional in the way we price a very professional and highly sought after skill.

Is there a role for artificial intelligence in the pricing of legal services?

Over the past three to five years, artificial intelligence (AI) has begun to transform how we go about much of our day-to-day business.

While not at the forefront of this transformation, legal service providers have not been excluded from this movement and this rapid transformation has included some of the larger law firms onboarding programs such as:

• CoCounsel from Thomson Reuters;
• Clio’s Clio Duo;
• Harvey AI;
• Microsoft’s CoPilot; and
• ChatGPT.

Just to name a few.

Many of these programs do not, however, include pricing as a core functionality.

Which raises the question: is there a role for AI in one of the core functionalities of our business, namely pricing?

The challenge AI faces in pricing legal services

As previously mentioned, a core challenge faced when pricing legal services is that it is fundamentally, and always will be, a credence service. We are a ‘people business’ and without the trust of our clients/customers, we won’t sell very much.

But trust is only one of the challenges in regard to pricing legal services. Others include self-doubt about our true worth. A more comprehensive problem also lies in how we reward ourselves for those services performed.

Currently, in both civil and common law jurisdictions, the practice of law relies on the utilisation of our lawyers. The core element of which relates to the ‘busyness’ of our lawyers against annual/monthly/daily targets. This busyness typically comes down to the number of hours a lawyer is able to work in a year.

Of itself, I have no issue with firms wishing to bill by the hour. At the end of the day, it’s your business. The service being provided is yours. Quod erat demonstrandum, how you wish to price that in the market is your decision to make. And if your clients are willing to pay that hourly rate, all credit to you.

But this business model creates a major challenge for anyone wanting to use AI to help them price their services. How you overcome this challenge will play a pivotal role in the successful implementation of AI in your firm’s pricing.

Seven ways AI will revolutionise your firm’s pricing culture

AI is a data-centric approach to pricing. It offers tools and techniques that should enhance your decision-making process. It offers third-party oversight to how you price your service.

Here are some practical examples of how this can be achieved:

1. the automation of routine pricing tasks: AI can streamline your pricing processes by automating routine tasks, for example, data collection, the number of files opened in a month, the average file value, etc. This automation reduces human error and allows you clearer oversight of the health of your practice. It should also reduce the cost of manually collecting this information for compliance-related reporting purposes, etc, which in turn will reduce the overall cost of doing business;
2. leverage segmentation: AI tools will help you track the fee, notably fixed and capped, you agreed with your client and ensure that proper matter leveraging occurs. Should utilisation of the matter fall outside of the assigned leveraging model, notification of a rectifying measure will be alerted to the partner. This information will then be collected and used in future pricing analysis modelling;
3. increase your firm’s win/loss ratio for bids, tenders and pitches: the use of AI-powered predictive analytics should help firms capture win/loss ratios on bids and tenders. This information can then be translated to help firms understand where price pressure in tender responses might be and to address these. In turn, this should help increase the firm’s win/loss ratio, increase revenue and, by default, hopefully profit;
4. helping to determine value: while value will always remain in the eye of the beholder, the use of AI tools can help your firm assess the perceived value of your services by analysing feedback from your clients, helping to project trial and transaction outcomes, and providing oversight of current trends. A lot of this information is already available, but it a labour-intensive process loved by very few! Utilising AI in this process will help provide your firm with real-time insight that allows you to set prices that align more closely with the value your clients associate with your services;
5. customer segmentation: the use of AI can help your firm’s marketing and business development team segment your clients based on historical data, purchase behaviour and preferences. This segmentation should help enable the business development team to advise partners on the best pricing strategies that cater to different client profiles, enhancing customer satisfaction and loyalty;
6. dynamic pricing: dynamic pricing is a bit of a nasty phrase at the moment, but there is little doubt it has a big part to play in the future pricing of the legal profession. Why should you not be allowed to alter your pricing depending on the urgency of a client’s needs? After all, if you want to jump the queue, should you not be required to pay a premium for this? AI algorithms will help your firm analyse real-time data to recommend appropriate dynamic pricing models that will ensure you remain competitive, while maximising revenue opportunities; and
7. horizon scanning/predictive analytics: AI-powered predictive analytics will help law firms forecast future trends, such as shifts in demand or changes in market conditions. By anticipating these trends, firms can proactively adjust their pricing strategies to stay ahead of their competitors.

The road ahead…

The road ahead for AI’s participation in the pricing of legal services is bumpy. To the best of my knowledge, less than a dozen software providers provide AI enhanced/empowered pricing dynamics tailored specifically to law firms.

That said, AI will play an increasingly important role. Because, in leveraging advanced algorithms and data analytics, AI will help your firm to optimise pricing strategies, enhance customer satisfaction and increase profitability.

And who wouldn’t want a part of that!