Creating Value From Unstructured Legal Data

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Published: 17 October 2019
Author: Anu Chowdhry

The legal ecosystem is witnessing a fundamental shift with service delivery models being transformed at a pace never seen before. If investment activity is a strong indicator of the scale and urgency of unmet customer requirements, legaltech joined the $1 billion club in 2018 – a fourfold rise from 2017.

Law firms – traditionally known to set aside a minuscule percentage of their budgets towards technology – now have innovation and legaltech teams joining their ranks. This tremendous spurt of activity is part of a larger trend of businesses migrating legacy infrastructure to the cloud and increasing their emphasis on data-driven decision-making.

What makes legal services so ripe for disruption? Legal data is essentially unstructured in nature. In a typical litigation, valuable information floats in transcripts, emails and thousands of documents. On the transactional front, AI can sweep through clause libraries and suggest best-suited clauses. In fact, voluminous legal data is ideal training ground for any AI solution. The more case law or contracts that an AI solution is fed, the better it learns to detect errors and inconsistencies.

An AI solution is singularly best suited to handle large-scale legal reviews necessitated by change of law. Clients benefit from significant cost savings and faster turnaround time. Law firms can take on more high-value work with existing teams, whilst lawyers eliminate the drudgery and focus on strategic skills. These actions lead to businesses being able to close deals faster.

Furthermore, there’s also the undeniable aspect of traditional legal billing being heavily reliant on hourly-billing and lump-sum models. Law firms face constant pressure to cut legal spend and legal pricing, as clients demand pricing innovation and alternative fee arrangements. With legaltech driving the shift from passive curiosity to active implementation, the future of tech-enabled legal services is exciting.

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