Opinion: CEO of Luminance explains how AI can not only understand, but anticipate, regulatory changes.
With a range of Russian entities now subject to severe sanctions, organizations around the globe are racing to ensure compliance with these new obligations, or in some cases withdraw from the Russian market altogether. But for many companies engaged in cross-border business, the challenge has been to efficiently assemble and analyze all contracts across their company and supply chains.
The scale of this challenge is obvious, as is the pressure from stakeholder groups on organizations to provide a comprehensive assessment of their liabilities. Furthermore, a one-time review of contractual obligations no longer appears to be sufficient in ensuring compliance, as the breadth of sanctions imposed on Russian individuals, banks and businesses continues to grow.
The economic and moral implications of sanction non-compliance are high, and artificial intelligence has a key role to play in helping businesses effectively manage their risk.
Against a backdrop of enhanced regulation including data privacy policies, ESG requirements and, now, global sanctions, the need for AI has never been greater.
At present, many organizations still rely on basic keyword search within rudimentary contract lifecycle management (CLM) systems – or, more often than not, actually not using technology to assist them at all when it comes to locating relevant information across their legal documents.
Not only does this result in inefficiencies, but also places businesses at significant risk of missing key information and, therefore, being non-compliant.
This issue is compounded both by the unprecedented volume of legal documentation that needs to be reviewed during regulatory compliance exercises and complex corporate operating structures that often see relevant legal documents siloed across different storage environments, with key information commonly fragmented among employee computers rather than contributed to a common, shared knowledge bank.
Whilst legacy technologies have attempted to address this issue, the inherent rigidity of these rules-based systems means that they can do little more than query legal data for keywords.
By contrast, AI can actually understand legal documents, processing vast numbers of documents in a matter of seconds. From this understanding, it can flag key information and make recommendations for legal teams to analyze and potentially act upon.
Assessing risk and liability with AI
So how can AI help businesses comply with the sanctions on Russia in the context of a regulatory compliance review?
With its ability to instantly understand legal documentation, AI can provide a holistic overview of an organization’s business activities, identifying all geographies present within contracts and displaying any contractual ties to Russian entities.
In this way, AI can display all business operations in Russia, not only surfacing documents in the Russian language, but also any reference to Russian places or legal structures across English or other language documents.
This unique language and jurisdiction agnosticism, achieved by AI reading patterns within language, would allow a company to easily gauge its operations and exposure to sanctioned entities.
Indeed, much of the insight delivered by AI is thanks to its conceptual understanding of language. AI can understand concepts within documents in much the same way that a human brain does, forming links between ideas.
So, if a company searched for mentions of ‘Russia’ within their documents, for example, AI could recognise that words such as ‘Russian Federation’ or ‘Moscow’ would likely also be relevant to the search, and thus should be included.
Importantly, this allows organisations to be proactive and define their own geographical risk parameters, possibly using this next-generation technology to identify documents and terms relating to other nations that may be jeopardized by conflict.
AI anticipates changes
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 a new concept. For example, should more sanctions be introduced in the future, perhaps on 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.
This all-encompassing view of an organization’s entire contractual landscape, irrespective of the volume, complexity or language that the documents are written in, makes AI invaluable to lawyers amid what is likely the fastest moving and most enduring sanctions imposed on a major economy that the modern world has ever seen.
The sanctions imposed upon Russian individuals and organizations are ultimately just one example of the enormous upheaval that we have witnessed in recent years in terms of regulation, policy shifts and landmark events.
Over the past few years alone, law firms and in-house legal teams alike have dealt with the ramifications of the Covid-19 pandemic and Brexit, watched financial regulation increase in the wake of recessions and trading scandals, and seen data privacy emerge as one of the most important issues of our time.
In such an unpredictable world, modern companies, particularly those operating across borders, face vast challenges. The implementation of AI will help them respond to even the most unexpected events and regulatory upheaval, helping with contractual understanding and commercial questions, and freeing legal teams up to deal with the other implications these changes may carry.