AI use cases in the legal realm are starting to snowball – and that wasn’t necessarily a foregone conclusion just a few short years ago. Today, AI is moving into a growing number of tasks, both large and small. Ultimately, that’s good news for end users, who will be the beneficiaries of this development as they work smarter and more efficiently.
The forsaken “to do” items
One area where AI can be particularly helpful is in tackling those administrative chores or tasks that are important, but often get pushed aside “to do later” whenever things get busy.
Exhibit A: email filing. Some legal professionals are very good at filing emails into the proper matter folder within the document management system the moment the emails arrive, or perhaps by end of day.
Then, there’s another set of people who save their email filing for the end of the week, or maybe the end of the month, or maybe even the end of the quarter. In some cases, the task gets pushed back indefinitely because other “higher priority” items keep popping up that require their attention.
AI can assist here by analyzing all the emails in an end user’s inbox that haven’t been filed and then intelligently suggesting different matter folders within the DMS where those emails should go. Suddenly, the “drudgery” of email filing becomes manageable with an assist from AI.
We can see a similar application for AI with another task that often gets relegated to the back burner: properly tagging all of the documents within a firm’s document estate.
Legal professionals are busy people, and they will often pick the broadest categorization for files that they are uploading to the DMS – for instance, choosing “document” under the metadata field for “type of content”. That’s fine, but it’d be better to specify what type of document it is, if you want to conduct meaningful searches on that content later down the road.
Again, AI can be very helpful in handling this sort of task. Running AI over the documents can help classify exactly what type of document it is – a real estate lease? a share purchase agreement? an employment contract? – and tag it accordingly, enabling firms to get better value out of the documents already in their possession. Given that firms often have thousands of legacy documents – or even millions, depending on the size of the firm – that were never properly tagged in the first place, this is no small thing to let AI chip away at this task rather than hoping that busy humans will make time for it.
Getting contracts into shape
Another AI use case that is quickly gaining traction is contract retrieval and remediation. In the face of new laws, regulations, or other changes in the business environment, legal professionals need to review their existing contracts to identify which ones are impacted by the change and require adjustments.
Historically, legal professionals search for these contracts using parameters such as jurisdiction, contract type, or other criteria. As described earlier, AI can go through an entire document estate to automatically classify, tag, and apply proper metadata. This makes finding the proper contracts easy because the search parameters are already present and ready to be searched on – for instance, find all documents that are real estate leases within the jurisdiction that is Singapore.
Retrieving the right contracts is the first step. From there, AI can step in again to lend a hand. For example, legal professionals can use a generative AI, chatbot-style interface to ask the AI to look for the presence of specific clauses in the pile of contracts that have been retrieved to see if they need to be adjusted or not. When each individual contract is hundreds of pages long, this is a huge timesaver.
Of course, AI can also assist with properly drafting contracts in the first place. Oftentimes, organizations will have a playbook that spells out what the contracts that they sign need to look like – for instance, any employment contract needs to contain provision X, or any vendor agreement needs to contain clause Y.
As a new contract is being created, a smart AI agent can continuously check that document against the playbook to make sure it contains everything it needs to and hasn’t taken any wrong steps. Even better, if the playbook is ever updated, AI can step in again to analyze the existing contract estate and see which contracts need to be adjusted to bring them into compliance with the latest best practices in the playbook.
Room to grow
It is early days yet with this technology, which means that the AI snowball has plenty of room to grow larger, roll its way into more and more use cases, and solve a greater number of problems for legal professionals. Ultimately, this is a welcome development, and a step towards an AI-enabled future where legal professionals are freed up to focus on the tasks that matter most to them, so that they can deliver their best work.
Jan Van Hoecke
VP of AI Services
iManage
Photo by U.Lucas Dubé-Cantin
