It is a truism that nothing ever stays the same, but business leaders today must feel as if the ground beneath them is continually shifting as they adapt and adjust to an endless stream of regulation and new compliance responsibilities.
The sheer volume and complexity of regulation, ranging from financial and data legislation to ESG reporting and economic sanctions, now poses one of the biggest challenges to legal professionals and, indeed, businesses today.
The scale of this challenge is made larger both by the unprecedented volume of legal documents that need to be reviewed during regulatory compliance exercises and complex corporate operating structures that often see relevant data siloed across different storage environments, with key information most commonly sat fragmented on each employee’s computer rather than contributed to a common, shared knowledge bank. What’s more, the economic, reputational and, now, moral implications of non-compliance have never been higher.
Against this backdrop, the need for AI has never been greater. At present, many law firms and organisations still rely on rudimentary tools and traditional ‘manual’ review techniques to locate relevant information. Not only do these methods result in countless inefficiencies, but they also place legal professionals at significant risk of missing key information.
By contrast, AI can understand vast numbers of legal documents in a matter of seconds, understanding and processing them and flagging key information and recommendations for lawyers to analyse and potentially act upon.
One need only refer to the sanctions recently imposed on Russia, which have required legal teams to take immediate action to assess their level of exposure to sanctioned entities, to appreciate the value of AI. With its ability to instantly understand legal documentation, AI can provide a holistic overview of an organisation’s business activities, identifying all geographies present within contracts and displaying any contractual ties to Russian entities.
AI would not only surface documents in the Russian language, but also any reference to Russian places or legal structures within English or other language documents. Much of this insight is achieved through AI’s conceptual understanding of language. So, if a lawyer searched for mentions of ‘Russia’ within their documents, AI could, for example, recognise that words such as ‘Russian Federation’ or ‘Moscow’ would likely also be relevant to the search, and thus should be included. Most importantly, an organisation could proactively define its own geographical risk parameters to include documents relating to other nations that may be jeopardised by conflict.
This all-encompassing view of an organisation’s entire legal documents, irrespective of the volume, complexity or language they are written in, makes AI invaluable to lawyers amid an ever-changing regulatory landscape.
We have seen AI work to this effect for a relatively new yet critical compliance responsibility: ESG reporting. AI can provide an instant understanding of a company’s existing ESG position by, for instance, highlighting out-of-the-box all regulatory requirements across contracts and allowing lawyers to easily gauge operations and exposure to any volatile regions or countries that have not, for example, signed up to the pledges made at COP26.
Perhaps of most value to lawyers is AI’s ability to not only deliver this critical insight from existing documents, but also anticipate future changes in standards or regulation by adapting as social mores or laws shift. State-of-the-art AI is so sophisticated that it can be updated simply by being shown an example of how a concept should look.
For example, should financial levies be imposed on non-renewable energy sources or, perhaps, other nations deemed to be assisting Russia, AI just needs to be shown one instance of compliant (or non-compliant) clause drafting. Following exposure to this one example, it will then be able to flag every other document containing this clause and any instances of non-compliance across all incoming documents.
Indeed, the inherent agility of AI allows it to stay on top of the even the most changeable of regulatory sectors, such as the financial sector. AI has even helped organisations such as major UK infrastructure investment and management group, Semperian, and consultancy firm, Ernst & Young (EY) Law, to identify concepts even as deeply embedded as LIBOR, away from which the financial sector has now shifted.
Indeed, by using AI, lawyers can quickly identify LIBOR-related provisions (for example, provisions pertaining to LIBOR definition; Interest Rate definition; Change in Law and LIBOR fallback) highlighting which provisions need to be amended. AI thus allows legal teams to review the entirety of their contracts and understand their risk exposure helping to mitigate the impact of enhanced regulation.
We have seen enormous upheaval over the past few years in terms of regulation and policy shifts, from increased financial regulation increasing in the wake of recessions and trading scandals, to data privacy becoming one of the most important issues of our time and new laws emerging in the wake of Brexit, the Covid-19 pandemic, and sanctions. In such an unpredictable world, legal departments everywhere face vast challenges.
AI can help law firms and in-house legal teams alike to cope with the sheer volume of regulation, providing enhanced contractual understanding and freeing teams up to deal with the other implications that these changes carry.
Eleanor Weaver is CEO of Luminance