The path to transformation

Last month I wrote about the rationale for law firms facilitating innovation and change. My impression was that the transformation of legal services is more about redesign than reinvention. The emerging technologies which are changing the law firm business model are about redesigning the user experience for legal services providers and their customers.

Examples include using artificial intelligence (AI) applications to handle tasks that involve repetitive, though not identical processes. Chatbots are a good example. When they are applied within the firm, they streamline interactions between users and data by allowing them to interrogate multiple systems from a single interface. When they are customer facing, they facilitate communication and efficiency/efficacy through intelligent automation of routine customer interactions. This makes it easy for customers to get in touch with the firm, and frees up lawyers from routine processes to deliver more interesting, value-added and profitable work.

This article considers the path to transformation: from design thinking to implementing innovative technologies that make a difference. The first challenge is deciding which ideas to implement; the second is identifying and deploying the best technology to deliver them; and the third is synchronising strategic planning with the evolving legal services market, either as a first mover, or a fast follower.  

Stuart Whittle, business services director at Weightmans, leads a cross-departmental innovation group which includes partners and subject matter experts. ‘We start by identifying the business problems that we are trying to solve either for us or our clients, and what can we do differently, and then we look at what’s out there that can potentially address them,’ he says.

‘We are addressing our main competitive challenges by focusing on three core elements. The first is developing and leveraging client relationships, to maximise revenue growth and cross-selling. That is mostly the partners’ job – talking to clients about their needs and how we can help.

‘The second priority, which involves the entire business, is service delivery – delivering client value while maintaining profitability. The third element is around business services. Innovation means trying new things, so our first step is to gather ideas from team meetings and decide whether any of them are worth taking forward.’

The implementation dilemma is particularly apt when it comes to AI tools. Legal AI is a hot topic but an immature market. The start-up dynamic has transformed legal IT, but it has also confused procurement patterns. Although a growing number of law firms have established tech incubators, most legal services providers are considering AI technology from two perspectives: boosting productivity while maintaining profit margins; and providing the ‘innovation’ focus that has become part of client and partner expectations as they read about robot lawyers in the mainstream press. This makes IT investment business critical.

Furthermore, legal AI tools are narrow and specific, requiring a portfolio of applications. This is relatively straightforward when the business case is clear. For example, magic circle firms might apply a combination of legal AI engines Kira, RAVN or Luminance to M&A due diligence, analysing large volumes of deal documents, comparing specific clauses and identifying anomalies. The time saving is so significant that it will represent a cost saving to the client while maintaining the firm’s profit margin, because notwithstanding whether their lawyers charge hourly rates or work to a fixed or capped fee, most firms still use time as a measurement of productivity and value. At the volume end of the legal services spectrum, the scalability and consistency of AI-powered processes boosts the efficiency and quality of commoditised work which lends itself easily to intelligent automation.

We constantly look at what’s out there and have created a list of vendors that address specific challenges.

Karen Jacks

Choosing technology partners to deliver AI requires a different approach from the conventional legal IT procurement model, because AI is an immature market with a strong start-up dynamic. The point was made in a panel debate at the AI Summit in London: working with AI technology is not about developing monogamous long-term relationships with vendors. As well as developing a portfolio of products that meet your firm’s specific requirements, it is important to avoid vendor lock-in because technology is advancing rapidly, the market is constantly changing, and start-ups cannot always scale up quickly. Josh Sutton, global head of data and AI at Publicis.Sapient, explains: ‘You need to plug in and out of different technologies as the market matures.’

As Rob McCargow, AI programme leader at PwC UK observes, this casts a different light on strategic decision-making: ‘AI delivers value – but only when you have a problem to solve. You can start with the strategy and look for the pain point, but when it comes to emerging tech you cannot be deterministic – otherwise, what happens when something new (and better) turns up? Emerging tech, including AI, requires a directional tech strategy, rather than a deterministic one.’

Whereas Whittle uses business requirements and competitive challenges as a strategic starting point, Karen Jacks, chief technology officer of Bird & Bird, has taken an iterative approach to emerging technology, starting from the technology and looking to see where it can meet the business needs of the firm and its clients. ‘We constantly look at what’s out there and we have created a list of vendors that address specific challenges,’ she explains. ‘In terms of legal AI there is no one-size-fits-all partner, so we have been looking at two types of vendor. First, we are interested in vendors that have developed a specific solution that can be deployed rapidly for a quick win. Second, we are considering generic products to identify anomalies and issues.’

Jacks is talking to Kira and Luminance about due diligence as well as non-legal-specific provider Rainbird for AI integration. The firm is working with RAVN on a proof of concept around analysing data and identifying expertise across the firm’s global offices.

For AI to become mainstream in legal, it needs take-up beyond the magic circle and international, tech-savvy firms like Bird & Bird which have the bandwidth to test multiple products simultaneously. What about small to mid-size firms for whom AI’s scalability offers the potential to take on bigger deals without increasing their resources, thereby enhancing productivity and market positioning? Andrew Joint, a partner at technology boutique Kemp Little, which handles more specialist, less repetitive tasks, focuses on the business case for investing in training and using AI tools: ‘We are interested in applying AI tools to deals that involve multiple contracts, or GDPR reviews, where we are looking at lots of different policies, processes and agreements, to find data protection-related issues. Contract analysis and review is especially interesting as it aligns with our focus on technology contracting.’

It is important to consider the need to invest sufficient time and effort in training the system so that it produces quality output that we are happy to put in front of our clients.

Andrew Joint

However, AI does not suit every activity. ‘We have been working with Kira, which is particularly strong on generic and specific issue spotting,’ Joint says. ‘However, it is important to consider the need to invest sufficient time and effort in training the system so that it produces quality output that we are happy to put in front of our clients. Clients have an expectation that, as technology specialists, we will use the latest tools, but they still require a certain level of service, and this underpins the business case for investing in the technology.’

Another consideration is that you cannot treat all law firms or legal specialisms in a generic way, and the impact of technology is different across different business and practice areas. ‘As a firm that specialises in technology contracting, we need to be credible in how we apply the latest tools, and consider how best to augment our practice in a way that maximises our skills and resources,’ he says.

At the AI Summit, Marc Lien, director of digital development and applied sciences at Lloyds Banking Group, used the red pill/blue pill analogy from The Matrix to describe the strategic dilemma around the take-up of AI and other emerging technology in banking. His message applies equally to the legal sector. While the red pill takes you down the rabbit hole of transformation – and recognition as an innovator – there is also an element of risk involved in working with immature products.

In legal technology, as in banking and financial services, the blue pill is not the end of the story (as it was in The Matrix). Rather, it represents a continuous improvement, fast-follower strategy, setting up an innovation function to keep a finger on the pulse of disruptive technology while maintaining the existing profitable business model – that is, the rest of the firm carries on as normal – and then evolving as the industry changes. The best option depends on the strategic direction of your firm, as well as its size, profile and culture.

Lien set out three steps to implementing AI – or any emerging technology:

1. Do not prove concepts, prove value (this means running a successful pilot);
2. Run AI-powered champion challenge models alongside business as usual (to demonstrate their benefits); and
3. Stand back and let the business owner take the credit (as BLP did with the first contract robot – the project was owned by the real estate practice not the IT or innovation department).

As Morpheus told Neo in The Matrix: ‘There’s a difference between knowing the path and walking the path.’ Now the AI/innovation hype is subsiding, it is time for firms to decide which route to take. The impression so far is that, with a few exceptions, law firms are hooked on the blue pills, but the fact that 2017 has so far seen more fast-followers than innovators is evidence that AI is genuinely hitting the mainstream.