2019 will be "the year of the switch to artificial intelligence"! This is what the Cercle Montesquieu announced in a study published last February(¹) . The legal departments are more than aware of the evolution of their business influenced by automation and many of them anticipate an in-depth transformation in the next 3 to 5 years. But what do we really mean by terms like "AI" or "Machine Learning"? To better understand, we propose today a concrete insight on how AI works within your contracts.
What is artificial intelligence?
Artificial intelligence seems to be the buzzword of the moment and yet it is not a recent concept. The term was defined in 1956 at a conference in Dartmouth in the United States by a group of scientists (economists, computer scientists, etc.) who formalized the discipline in research. At a time when computer science was making great strides and was heavily financed by defense budgets in the context of the Cold War, the dream of these pioneers in the field was intertwined with the one carried since antiquity by philosophers and mathematicians: to reproduce human thought and, more broadly, to create machines capable of relieving man of his most thankless tasks.
Several technological revolutions later (internet, cloud computing, computing capacities...), artificial intelligence accelerates its development and is integrated into our daily software to assist the professional in the most difficult and complex tasks for humans. If only in the legal field, the benefits of AI are multiple.
👉 Read our article on the subject: Why automate contract management?
One AI or many?
If we usually talk about artificial intelligence (singular), it is in fact a multitude of specialized AIs that work together to solve our problems.
There are two types of artificial intelligence:
- Symbolic AI: machines execute actions according to rules dictated by humans, in deduction of input data (requires business expertise to build these rules and make them evolve over time). The system does not learn by itself and it is necessary to describe its reasoning precisely.
AI by learning: this involves making sense of input data in order to be able to transpose a reasoning onto new data. This is learning by example, which requires business expertise to identify these examples and name them. The system writes the best rules by itself.
In the example above, we show pictures of cats and dogs to the machine to train it to recognize the images of "dog" or "cat" when it is confronted with new pictures of animals later on.
It is the set of techniques and algorithms that allow the machine to discover and extract from a set of data a set of hidden similarities: we speak of " patterns ". This is how the machine learns and develops. These patterns can be used to make groupings and predictions on new data sets. Machine learning is particularly useful for analyzing large volumes of diverse and evolving data... such as contracts, which have a life cycle, and regulations!
Artificial intelligence in contract management
How does AI process contracts?
In addition to character recognition (OCR), which allows an image to be "translated" into an editable text file, artificial intelligence allows important information to be recognized according to the context: types of contract, clauses, key elements (dates, amounts, duration, counterparties, etc.).
Automation at all stages of the contract life cycle
Enterprise Contract Lifecycle Management (ECLM) is the set of best practices that apply to all stages of the contract lifecycle: drafting, negotiation and review, approval and signature, monitoring, reporting and auditing. Automating your contract management means making your contracts an organized, searchable and up-to-date database, useful at all stages of the process...
- When drafting: you can create your contracts from the templates or clauses most relevant to internal contract policy and regulations.
- During negotiation and review: AI automatically recognizes key clauses and data within the contract. You can find this information in summary sheets at a glance.
- During validation and signature: automated approval circuits make collaboration fluid until signature, without going through the traditional paper signature pad or email exchanges, which are easy to lose track of...
- When monitoring: you can instantly identify the types of contracts, the important fields and the priority clauses within your entire database of contracts. For example, you can easily find all the contracts containing such and such a clause, taking effect between such and such a date, on such and such a type of contract and involving such and such a counterparty... all at once!
- During reporting and auditing: you can easily analyze your entire contract database and quantify your company's contractual activity, risks and opportunities thanks to the statistics extracted from your data (status of your contracts, dates, signatures, types of documents, etc.) but also thanks to the automatically filled-in audit forms that can be exported directly to Excel or by API.
In short, if AI frees the lawyer from tedious tasks such as typing, proofreading and researching large volumes of data, it also provides more visibility to help him better control his commitments: what are my obligations in case of data breach? am I in compliance with the RGPD? Are all my contracts signed? Are there any non-standard clauses? Can I find the latest versions of my contracts and all amendments?
Due diligence, compliance maintenance, financial monitoring, lease review, knowledge management, history recovery... the applications of AI in the legal industry are as numerous as there are use cases. What's yours?
👉 To learn more about AI and contract management, download our white paper on the topic.
(¹) Study "Digitization of legal departments", conducted by Day One, CMS Francis Lefebvre Avocats and the association of legal directors Cercle Montesquieu , February 2019
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