What is the Role of AI in Contract Management?

Artificial Intelligence is taking contract management to the next level. Gone are the days of manual inputs and sifting through lengthy email threads. Through the use of AI, CLM technology has the potential to improve contract document management in any industry, no matter how extensive or complex a contract portfolio may be.

Combining machine learning (ML), natural language processing (NLP), and other AI technologies, AI-powered contracting software such as Sirion utilize a neural network-based system to identify, learn from, and offer prescriptive insights based on retrospective contracting data to help create smarter agreements, faster than ever before. 

Below, we’ll discuss the various application points and the benefits AI contracts provide: 

Harnessing Contract Intelligence with AI

Legacy contracts are often spread across multiple data silos, limiting visibility and accessibility. As a result, contract managers—and by extension, other key stakeholders—are unable to access contract information on demand due to lack of centralization and data structuring.

This lack of visibility also prevents organizations from effectively enforcing contractual terms, leading to suboptimal business outcomes.

However, through the use of AI-powered auto-extraction and analytics, CLM software drastically reduces the time required for data extraction. Here are some ways in which AI helps you make the most of contractual data:

• Information discovery and visibility: AI-led CLM platforms such as Sirion can connect with industry-standard software such as ERP, P2P, and CRM to pull in and digitize documents, which are then stored in a centralized, cloud-based repository. 

Once uploaded, users can utilize the “fuzzy search” or any other advanced search function to quickly and easily locate contracts according to the title, clauses, counterparty name, and so on. In effect, this functions like ‘Google search’ for contracts.

• Data extraction and accessibility: The AI engine also extracts metadata, clauses, obligations, SLAs, rate cards, and other relevant data points from contracts. This makes all granular contractual data immediately accessible.
• Performance management: The extracted data can then be visualized through role-based dashboards to enable supplier performance and obligation fulfillment tracking. 

This information can also be used to support re-negotiation strategies, identify cross-sell and upsell opportunities, and facilitate smarter, data-backed decision-making. 

AI Contract Authoring & Negotiation

Standardized contract management processes are key to ensuring due diligence during the contract authoring and negotiation phase. However, given the sheer volume of contracts organizations must manage, reliance on traditional, inefficient contracting processes becomes increasingly problematic.

When done manually, the contract drafting and legal review process can be arduous, error-prone, and simply impractical. Miscommunications and unfavorable agreements are more likely to occur. This, in turn, may prolong the contract negotiation phase, adding to the workload of contract professionals. 

Fortunately, with one-click drafts enabled by AI-guided contract assembly tools, templates, and automated workflows, companies can streamline the drafting phase and expedite the negotiation cycle by up to 50%.

To ensure compliance with company-preferred positions at every touchpoint, contract management systems provide AI-assisted redlining and clause selection. These tools accelerate the legal review process by automatically scanning drafts and third-party papers to discover risk elements. 

Everything from missing clauses, clause deviations, insertions, deletions, and modifications are highlighted by the AI. The AI can then offer prescriptive suggestions for preferred clause language. Not only does this significantly shorten the legal review phase but also enables companies to draft contracts up to 90% faster using standardized contracting language. 

Risk Management

When businesses have thousands of procurement contracts, customer contracts, non-disclosure agreements, other contract types, and legal documents to manage, manual risk mitigation is ineffective. Simply put, organizations will continue to unknowingly increase their risk exposure. 

Companies that adopt AI contracting software can go on to improve risk discovery in third-party papers and legacy portfolios. 

As a self-learning system, a CLM’s AI engine can compute and generate risk scores against contract drafts by comparing its clauses against the enterprise contracting playbook. Contract managers can then course-correct based on the AI-suggested modifications.

With regards to legacy contracts, risk identification is made possible thanks to digitization.  Following digitization, information from both printed and handwritten agreements can be extracted and subsequently compared against company standards.

The CLM system alerts all stakeholders of potential issues and areas of risk—leading to fewer compliance issues and better alignment with desired business outcomes.