AI for Contract Management: Understanding Potential and Limits

If you follow tech and innovation news, there’s a good chance you’ve heard a lot about AI. AI, or artificial intelligence, is the use of machines to perform functions that typically require human intelligence.

If you’ve ever bought something after it showed up in Amazon’s recommendation engine or you’ve asked Siri or Alexa to play you a song or what the weather is outside, then you’ve already experienced AI in action. But with so much buzz about the capabilities of AI to transform so many of our daily and business functions, you may be wondering about its potential to make contract management workflow more effective and efficient.

While AI is a broad term to describe any technology that allows a device to act intelligently, the greatest opportunity for contract managers likely lies within the subset of AI known as “machine learning.” Machine learning is a concept which refers to mathematical modeling and algorithms which utilize data to improve decision-making. As such, the potential for contracts should be somewhat obvious: if machine learning runs on data, then contract managers – with their portfolios of thousands of documents, if not more – have ample fuel to drive machine-generated insights.

What are the potential benefits of AI in contract management?

So what can enterprises do with this data fuel? When it comes to contract management, the potential is vast. If your company is already approaching contracts proactively, then there’s a good chance that you’re already using the data within your contracts to refine and improve the contract management process. This may include things like keeping track of how variations in specific wording and contract terms affect contract performance and then using those learnings to strengthen the language of future agreements. But while conducting contract post-mortems can indeed be helpful, if you’re doing your reviews manually, you’re limited by the amount of information you can research and digest.

Machine learning can make these efforts far easier because instead of having to track and analyze agreements one by one, algorithms can process the data from vast volumes of agreements in order to reveal more accurate and actionable insights and trends. Even better, predictive technologies could allow AI to model out the potential results of a contract based on past performance of other agreements under varying scenarios. This could enable organizations to introduce terms during the drafting phase that could help boost contract performance under certain conditions or assist in earlier and more effective identification of contracts that could be at risk of underperformance or failure.

The challenges of AI in contract management 

While the promise of AI for contract management seems tremendous, there is a fundamental limitation that applies strongly to the field of contract management. It’s the requirement that machines be able to read and process the data that’s required to power AI insights.

Why does this limitation apply to contract management in particular? Because machines are only able to process data they can access. When you consider how many organizations still lock up hard copies of their contracts in filing cabinets (and that’s if they can find their contracts at all. One study published in the Journal of Contract Management found that more than 70 percent of companies can’t find 10 percent or more of their written agreements), it’s easy to understand how far many organizations are from realizing the powerful benefits of AI.

Even if you’re using tools such as Excel and shared drives to store your contracts, you’re still far from ready to leverage the powers of AI technology. That’s because in order for machines to glean insights from your contracts, they must first be able to uniformly digest their contents. This requires more than merely scanning your documents, as this typically creates a picture file from which computers cannot extract meaning.

If you’re looking to make your contract portfolio AI-ready, a good first step would be to start digitizing your documents using optical character recognition (OCR). OCR converts the words that are on your pages into computer-based text, which can then be searched or subjected to machine learning formulas. While it may be too onerous to scan all historical contracts, the sooner you adopt contract lifecycle management software that is capable of converting your documents, the sooner you will begin growing your data pool – and the more data AI has to work with, the more significant the insights it can glean.

It’s also useful to have a plan for what sorts of insights you are looking to derive from your data so that you can set up custom reports to track the right metrics. These reports can then be exported as Excel files for easy data processing.

With some AI technologies still in their relative infancy, we’ve only just begun to determine the many benefits intelligent automation may yield within contract management. But if organizations want to be well-positioned to take advantage of these innovations, it’s important to take steps now to ensure their contract portfolios are ready for the transformation.