Written by Matt Shearer, CPO, Data Language
In recent years, the legal sector has taken its first meaningful steps beyond basic digitisation towards true digital transformation. The industry is making a concerted effort to manage business processes by moving away from a manual, document-centric approach, and toward a data-driven approach and using machine learning for the heavier administrative tasks.
For example, 2019 saw the launch of General-purpose Legal Mark-up Language, which enables accurate and automated extraction of data from legal documentation for sharing with relevant intermediaries. There are also government-funded programmes like the Tech Nation LawTech Sandbox, which opened in December 2020 and aims to fast track transformative ideas, products and services in the legal sector, including AI.
Today there are interesting developments in areas, including risk mitigation (Deep Tech Resolution Lab detects early signs of customer/supplier legal disputes), and machine learning-powered guidance for small businesses (Legal Utopia provides rapid and low friction guidance for common legal issues).
Looking into the future, the immediate opportunity is in knowledge management. To unlock new value from data and organisational knowledge using AI, organisations need to pivot from document-led to data-led and re-think their knowledge backbone.
This step is required for organisations to be able to ask more useful questions of their organisational information, and crucially in this discussion, to train their predictive machine learning capabilities to enable automation.
For true machine learning-based AI in legal, there are numerous examples of legal text classification systems. This is not surprising, as one of the few areas where AI training data is available in law is the categorisation of documents for retrieval. The volume of training data needed and the scaling of training cycles, though, are two areas that could be improved.
Legal firms that build their core expertise and differentiation into the design of their information management systems, at a granular and interconnected level, will create an advantage for themselves – both in their ability to adapt rapidly and their readiness to harness AI for new business models.