This article was written by Mayank Tripathi
Two major threats that the legal sector is facing at the moment are the growing number of alternative legal services providers (ALSPs) and the entry of the Big 4 accountancy firms – KPMG, Deloitte, EY and PwC. The result is an increasingly competitive market where clients want services that are cost efficient. In response, law firms have started to adopt technology-based solutions such as artificial intelligence (AI) in an attempt to lower costs.
The most common way AI is being deployed is Technology Assisted Review (TAR). This means that barring documents that are specific to an agreement, most documents in a transaction tend to be boilerplate. Examples include employment contracts, licenses etc. However, while these documents may be similar, they differ from one transaction to another and still need to be identified each time. Having lawyers engage in determining and locating documents that are relevant can be time consuming and therefore costly; this is where TAR comes in. TAR AI programs can quickly review a large number of documents and produce those documents that are relevant to a transaction. The automation of these tasks makes the whole process more efficient and cost effective. Moreover, the program engages in machine learning – over time it becomes more efficient as it “learns” to spot trends in the type of transaction being engaged in and what documents are required. Eversheds Sutherland has partnered with Luminance to provide AI-powered solutions to M&A due diligence.
By automating tasks that are generally time consuming and generic, law firms are becoming more efficient and competitive. Moreover, by not billing clients for such day-to-day work, clients get more value for their fees. This is a key factor in retaining clients that would otherwise be attracted to the new entrants in the market like the Big 4. However, it needs to be noted that problems may arise regarding documents specific or unique to a transaction. These are likely to be missed by the algorithm as it may not have processed enough data to accurately establish a link between locating the document, deciding whether it is relevant and as a result retrieving it. At this point, human intervention would be necessary and this goes to show that AI is but a tool facilitating a task and cannot yet be relied to carry out the entire task on its own. This could change in the future.
Moreover, law firms have realised the long term potential of the technology and are paying very close attention to the growing lawtech industry. Mischon de Reya, for example, has invested in multiple platforms – timekeeping program Ping and case management platform Everchron and Thirdfort, which are used to verify client identity and source of funds. Certain law firms such as Allen & Overy and Clifford Chance have gone so far as to starting their own incubators by giving lawtech start-ups a space to develop and test their platforms in order to stay ahead of the competition. Clifford Chance has also partnered with Fliplet – an app building platform in a bid to encourage trainees to come up with their own technological solutions to problems they face at work.
However, what’s stopping AI from being adopted by all law firms across the board?
One of the concerns is the reliability of the technology. The efficiency of any AI platform is reliant on the quality and quantity of data that is fed into it. Processing large volumes of high-quality data is the only way for any AI platform to provide consistent and reliable results. Given the relatively recent acceptance of AI technologies in contemporary legal circles, there is the question of whether or not AI has had a chance to process an appropriate amount of data. However, law firms possess large volumes of data in the form of old contracts, agreements etc. that if opened up to AI would help improve the efficiency of the technologies in the long run.
Secondly, a program that processes data that is covered by legal privilege also raises privacy concerns. Firms are likely to have to invest in robust data protection teams and the maintenance costs of having to procure additional software, hardware, servers etc. At the same time, as the technology becomes more reliable and efficient, demand will see an increase. Firms are likely to incorporate the use of AI in order to stay competitive and modern. As demand increases, there will be an increase in supply; this increase in suppliers will lead to lower and more efficient prices over time.
For students applying for vacation schemes and training contracts:
It would be a good idea to research your law firm’s approach to technology such as AI. Students could also go one step further and learn basic programming skills. Not only does this help one stand out amongst other applicants, basic programming literacy could help trainees understand the technology behind the software used by their law firms.
Moreover, with tasks such as doc-review being automated, trainees will now have more opportunities to engage with tasks that are more analytical and complex in nature. This would lead to a more well-rounded training contract experience and trainees will be better equipped with the skills needed post qualification.