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From request to retirement, contracts have a complicated path through your organization's systems. If your contracts are still sitting around in spreadsheets and file cabinets, you know how hard it is to lay your hands on the contract you need, when you need it, wherever you are.

As you look to update your contract lifecycle management (CLM) system, artificial intelligence (AI)-powered solutions promise to simplify how you manage your contracts without digging through filing cabinets and manual systems. It's an exciting time to explore CLM solutions but finding one that uses AI effectively can be a challenge.

Contractually Speaking

Legal professionals often experience frustration around CLM systems. They want a better solution, but they're wary of current technology and their ability to reliably manage compliance and mitigate risk. There are three issues that consistently arise when discussing CLM.

1. Difficulty collaborating: Legal professionals involved with contracts run the gamut from in-house legal department lawyers to IT managers to procurement officers. They all want a CLM system that allows for ease of collaboration between departments, all without sacrificing compliance and risk management. When departments can't collaborate effectively, the chances are high that they simply will not collaborate at all, further siloing how each department manages and tracks contracts.

2. No single source of truth: Organizations run into trouble when they have contracts scattered in spreadsheets or file rooms. There's simply no way to tell if they're looking at the most updated version of a contract. However, considering the risk involved in having multiple versions of binding legal documents, consolidation is the only viable solution. It's important to remember that, since every department handles contracts differently, they should all be consulted for successful consolidation.

3. AI skepticism: AI is, according to seemingly every pundit, the next big thing. That means almost every tech company is bound to talk up their "AI technology," but how do you know who's really on the cutting edge, and who's not?

AI: The Cure for CLM Blues?

CLM presents a special challenge. Paper contracts, multiple clauses per contract, and complex versioning are all factors, but AI is up to the challenge. So, what does an AI-enabled CLM solution need to truly alleviate the problems surrounding contract management?

First, to find any contract, clause, or keyword in an instant, the solution needs optical character recognition (OCR). OCR capabilities allow legal professionals to search for contracts instantly by recognizing metadata from scanned documents, such as contract amount and renewal date. With AI-based OCR functions, the CLM system reads contracts and converts them into data that organizations can easily access and at the point of greatest need.

The second capability of an AI-driven CLM system is a conversational interface using natural language processing (NLP) with tools such as Alexa. Conversational interfaces utilize voice commands to boost productivity and allow hands-free connectivity. A voice-based AI integration lets users' interface with the CLM system directly, including search, reading, or editing fields and records as well as counting. For example, users can simply ask, "Alexa, how many contracts are due this month?"

The third way AI assists legal CLM is with risk scoring. AI risk-scoring can help organizations manage risk and maintain compliance. Once companies configure the desired risk-level formula, an AI risk-scoring tool can quickly review documents and flag risky clauses and contracts for further review based on the company's preferences. In addition, AI can collect data and recommend actions on types of clauses or contracts.

Finally, we can't forget about machine learning. Machine learning allows organizations to "train" AI-powered solutions to perform custom functions using popular machine learning models from Amazon, Google, and Microsoft. If this sounds complicated, it doesn't have to be. Ideally, training a new algorithm for machine learning can be accomplished with a few mouse clicks at most. With machine learning in a CLM system, organizations can, for the first time, make predictions and use them to automate workflows.

 

Colin Earl is the founder and CEO of Agiloft, a Silicon Valley pioneer in no-code development platforms for business applications and contract and commerce lifecycle management (CCLM).