In previous posts, we’ve explained what contract lifecycle management is and why it matters for business. Legacy systems provide contract management software that automates some or all of the process of contract creation and management, from the generation of templates, through the negotiation and drafting of new or revised clauses, to the execution and ongoing management of a portfolio of agreements.
Moving Forward into the Future
At Evisort, we’re focused on the advent of artificial intelligence in contracts, and exploring what machine learning and natural language processing mean for the world of law. Businesses need to understand what’s in their contracts fast. COVID-19 and the sudden need to locate force majeure clauses presented a tipping point. Companies wanted to know right away how to manage their vendor, supplier, and rental agreements. Review processes that typically take weeks or months, whether your business has hundreds or tens of thousands of contracts, no longer would suffice.
The only way to understand quickly what’s in all of your contracts is with contract intelligence: artificial intelligence built into the contract management platform. With the ever-changing regulatory environment and privacy laws, understanding what’s in your contracts quickly is now an everyday need, not a one-time, freak occurrence.
Already, we can see the effects that AI is exerting on multiple aspects of legal practice, ranging from faster, cheaper, more accurate document review to a shift in budget allocation by in-house legal departments away from law firms that bill by the hour, and toward legal tech that promises to do mundane legal work in a fraction of the time that a team of humans would require.
For example, Walmart estimated that their adoption of AI-powered legal technology reduced the time required for routine tasks related to litigation by 60 to 80%. AI-backed automation reduced the time required to create documents such as answers to litigation and discovery requests to only two minutes, giving their lawyers more time to focus on strategy instead of completing menial, repetitive tasks.
In addition to dramatically enhanced speed, AI’s natural language processing capabilities provide augmented accuracy. Our own internal studies show that Evisort can read a 30-page document in just 15 seconds with 95% accuracy. Compare that to the human lawyers who failed to correctly identify up to 75% of relevant documents in this study that pitted an AI algorithm against humans performing manual document review.
In a nutshell: AI is faster and more accurate, and can be less expensive as a result of the drastic decrease in hours billed by human lawyers.
We know that in-house legal teams are turning to AI to help reduce the cost of mundane legal tasks. In 2018, the Thomson Reuters State of Corporate Law Departments Report showed that more than three quarters of in-house legal departments actively sought to reduce their spend on external counsel, and nearly half indicated in a Gartner study that they would increase their spend on legal technology by 2021.
AI-powered legal tech platforms are becoming more accepted, less feared, and better understood. So what does this emerging technology mean for transactional legal practices and procurement teams that churn out thousands of contracts every year?
It means that we’re shifting from the concept of contract lifecycle management to a new, smarter way of engaging with a business’s contracts: contract intelligence.
Improving Contract Analysis
Machine learning algorithms are empowering businesses to move far beyond simply staying on top of deadlines and collecting signatures. By extracting genuine insights from the language contained across hundreds or thousands of contracts, a contract intelligence platform can increase a team’s contract business intelligence capabilities while giving them more time to develop strategies based on that enhanced understanding of their business.
Logistically speaking the contract review process is quite demanding and is often prone to human error resulting in undesirable outcomes later down the road. Automating the process eliminates potentially costly hiccups and frees up team members to focus on high priority tasks.
Thanks to the current sophistication of natural language processing algorithms, an AI platform can also produce writing indistinguishable from that of a human writer. Instead of having a human lawyer or contract manager spend hours drafting legal clauses, businesses can now rely on AI to do the same job in minutes—and the higher the volume of contracts your business manages, the smarter the algorithm becomes at speedily producing new agreements with all of the terms you need.
Evisort is contract intelligence. It’s the only end-to-end platform with AI built into the core architecture.
Evisort’s leading-edge, proprietary AI can process 122,400 pages in just one day (how fast can your lawyers read?), extracting valuable insights from contract data as it goes.
It comes pre-trained on millions of examples and variations of clause language so that it can detect 60+ standard fields and provisions with 95% accuracy, out of the box, at minimum. That’s not all: Evisort can create custom algorithms with 95% accuracy starting with only 10 training examples.* On top of that, Evisort’s Optical Character Recognition (OCR), which detects objects such as text, company logos, signatures, and tables in scanned or digital contracts, is 97% accurate*. Compare that to the much lower 80% accuracy that most CLM platforms’ OCR is capable of offering.
A typical lawyer will take hours to review an 85-page contract. Evisort does it in just one minute. What could your legal and procurement teams accomplish with that much more time on their hands?
Contrary to what some fear, AI will not put every attorney out of a job. Instead, automating the creation of rote commercial agreements frees lawyers and procurement managers to concentrate on more complex deals and compliance issues, maximizing the value that they provide to their businesses and enabling teams to evolve into true intelligence organizations.
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*based on internal testing and customer testimonials