In case you haven’t noticed, artificial intelligence (AI) is becoming a very big deal in business. And there is perhaps no area where the impact of AI systems (i.e., systems that exhibit intelligent behavior) will be felt more than in legal departments and, more broadly, in the area of contract management. Consider the enormity of collective knowledge that makes up commercial law and amount of money spent translating the semi-structured “legalese” that enshrouds what should be logical business constructs that sit at the core.
Every commercial contract is like a little knowledge base that contains critical data on organizational commitments (usually legal obligations), rights, remedies and rules that reflect business decisions made in the past that will affect performance in the future. Unfortunately, the amassed collection of thousands of these artifacts does not provide a “collective intelligence” that can be used efficiently to reduce commercial risks and increase economic value for the firm.
The trick therefore becomes not just how to digitize legal contracts, but also how to transform these documents into a structured commercial knowledge base that works in concert with AI based techniques and tools (of which the frequently mentioned term machine learning is only one of many) to create this collective intelligence.
But how? Does this require next-generation AI tools?
The answer is no (at least for now). But, if you want to build such commercial intelligence into your contract management, whether on the buy-side for supplier contracts or more broadly for all enterprise contracts, you should take three basic steps:
– Build a high-level knowledge base about all your contracts in the form of a contract repository to gain high-level self awareness of your commercial health vis-à-vis your contract documents.
– Derive key intelligence from within your contract data to identify critical risks and latent opportunities (e.g., unclaimed money due to you). This is where the heavy lifting of AI starts by training the “machine” to decipher the legalese down to a granular contract clause level (including metadata)