Contract AI is No Slam Dunk

As pressure on obligation tracking and renewal management increases, getting a handle on contract management after the signature is crucial.

In high school, I played offensive line in football. I also played basketball. When you combine the two, it shouldn’t take you long to realize that I couldn’t jump–but I really, really wanted to. One day, I was watching TV when a commercial came on advertising “plyometric shoes.” They promised a better vertical immediately.

I was sold and somehow finagled a pair. I put them on expecting to leap small benches in a single bound, but nothing happened. Nothing. I wore them every day for weeks. Still nothing. Then, a cousin let me in on the catch. To get the benefits, I needed to commit to a whole set of special exercises. I was crushed. My dream of magically becoming the next poster boy for Air Jordans went out the window. Instead, I was left with an (at the time) expensive investment and a long road ahead if I wanted to see any reward. 

In recent conversations with people in the contract management industry, I’ve had flashbacks to my brief (and imagined) slam dunk dream. Artificial intelligence (AI) continues to generate buzz among the contract management community as an answer to obscured visibility into contractual documents and mounds of data. Unfortunately, a large percentage of the people I talk to underestimate or fully discount the work they need to put in to realize the returns they are looking for and soon realize there is no “magic AI button”.

Don’t underestimate the difficulty (and importance) of clean data

Just like I underestimated how hard it was to jump higher, most people underestimate how hard it is to extract accurate, actionable and useful data from unstructured contracts. Companies also overestimate the “cleanliness” of their current documents and data. At Pramata, we’ve seen customers deploy a typical contract AI tool and still see error rates of up to 59%.

For all its promises of contract management transformation, AI is only as good as the data you’re using to tune it. And what we’re finding is that most companies don’t have good data to start. Plus, most contract AI tools leverage a limited set of contracts to develop their built-in algorithms, making it even harder to create meaningful intelligence across a diverse set of documents.

Just like me and my magic shoes, most people are looking for a “silver bullet” that just doesn’t exist. Because of this, there is a significant, often understated effort that must be put into:

  1. Building a representative data set
  2. Tuning the system against that data set
  3. Closing the many practical gaps that technology alone cannot deliver

Human-assisted Contract AI is the secret to success

To effectively apply AI to its broadest business value, it takes work. That work comes in the form of humans—skilled ones—providing accurate data normalization and superior data quality. This is because extracting and normalizing accurate, actionable, and relevant data from unstructured contracts is hard, for many reasons including:

  • Highly negotiated and amended language that materially affects downstream document families
  • Multiple document forms and naming conventions by department or acquired business units
  • Multiple ways to interpret the same thing (subjectivity)
  • Multiple clauses combining to produce one data point
  • Lack of data entry standardization
  • Missing documents
  • Poor OCR quality

Without those people and an integrated process, most Contract AI tools essentially become glorified text search or data scraping tools with limited insight into important contractual relationships.

The rewards are worth the investment

My point isn’t to dismiss the impact of AI—I mean my company is centered around AI technology. It’s also not to diminish the value of the contractual data sought by companies. I’ve been working with companies to solve this problem for my entire career. I’ve seen the cross-functional, organizational impact that having a handle on contracts and their data can have on productivity, growth opportunities, obligation and risk management.    

I firmly believe that managing signed contracts should be a top priority for companies; and advances in AI have made that more achievable than ever. As pressure on obligation tracking, renewal management and operating efficiency increases, getting a handle on contract management after the signature is crucial.  That being said, it’s essential for everyone to be realistic about what it takes to realize this significant opportunity.

At Pramata, we are on a mission to make managing your contracts effortless. We  take an integrated, human-assisted AI approach to contract management, unlocking critical data about a company’s contractual relationships. Repository as a Service (RaaS) is the first solution to combine the power of Contract AI technology with AI-Assist, a team of experts (humans!) to ensure ongoing accuracy and efficiency.

We’re straightforward and practical about the underlying challenges of contract complexity and data inconsistency, and we help our customers with the slam dunk they’re looking for.

Subscribe to Our Legal Impact Newsletter

Get exclusive event invites, peer best practices and the latest industry news right in your inbox!

More To Explore


How Pramata Speeds Up and Simplifies Mergers and Acquisitions

Contracts play a major role in the M&A process, starting with the buying company’s due diligence all the way through identifying overlapping customers and vendors, standardizing master agreements across the old and new companies and much more.