Every formal business and legal dealing starts with a contract. Contracts are a source of valuable information in the event of disputes, renewals, or certain strategic decisions. They need to be maintained and tracked to ensure obligations are met by all parties involved. Despite their importance, it is no secret that contract lifecycle management (CLM) is something that most companies don’t do very effectively. It’s understandable why this was the case in the past – it needed to be done manually, which is cumbersome, time-consuming, and prone to error.
But with the advent of legal software and tools powered by artificial intelligence (AI), the task of dealing with contracts has becoming significantly easier. AI, in particular, is helping to automate certain functions and increase speed and accuracy at just a fraction of the manual cost. This frees up experts from mundane, repetitive tasks to focus on those that add greater value to the business or clients. The global legaltech AI market was worth US$3.2 billion in 2018 and is projected to grow to US$37.9 billion by 2026 – that’s over ten times.
AI in contract lifecycle management
Processes within CLM where AI tools are being currently deployed include drafting, negotiation, review, and post-execution management.
Drafting: AI tools can be used during drafting for standardized contract templates that contain the appropriate language so it need not be done from scratch each time. They can also help evaluate the language of non-standard contracts in some cases.
Contract Review and Negotiation: Reviewing, negotiating, and finalizing a contract can be a long-drawn process, with all parties tweaking terms of the draft contract to best suit their needs. Lawyers can be required to read through thousands of pages and redline changes they want over multiple iterations. Doing this manually can be fraught with errors or missed clauses due to the minute details and edits. It can also delay business goals, which can be costly for companies.
There is a lot of scope to automate parts of the contract review process, including reading, identifying predetermined concepts, extracting relevant information, and presenting the data in easy-to-read formats. While lawyers are still needed to go through the specifics, using an AI tool shows them where exactly they need to focus their attention.
This ultimately allows for negotiations to be faster and more accurate, which in turn can help close a deal quickly.
End-to-End CLM: The work doesn’t end with a contract being signed. Keeping on top of obligations and terms (such as payments, deliverables, and due dates) can be a nightmare since companies have thousands (millions in the case of large companies) of contracts to track. Doing this manually is near impossible and relying on tools like email and Excel is bound to lead to mistakes. Often, different divisions within one company have no idea about terms in the contract.
The growth of LegalTech now offers CLM software that serves as a central repository for contracts, and AI tools can be incorporated within the system to tag and extract contracts based on required fields. AI can also be used to set track workflows and deadlines so that obligations can be met in time.
The human angle to contract AI tools
There is legitimate concern that AI-powered tools will render certain types of jobs redundant, putting thousands of people out of work. While automation can certainly do this, there is still need for human intervention – and this is not just to interpret results given out by the AI system.
AI is still in its infancy in the legal space, but there are numerous tools being introduced to help automate multiple aspects of the legal processes. These tools need quite a bit of calibrating and “training” to eventually learn what to do, which requires people with the relevant experience – specifically contract management specialists.
Companies that build AI tools do exactly this – they use experienced lawyers, paralegals or contract management experts to teach their tools what to do. This is called the “human-in-the-loop” model. People are able to make subjective decisions regarding certain clauses or contracts and train the tool to do the same. This not only customizes the tool for the specific needs of a company but also improves the overall accuracy of the tool.