What Does the Future Hold for AI-based Contract Lifecycle Management?
By Viraj Chaudhary, Chief Operations Officer, ContractPodAi
We live in a world where business relationships often extend across international borders, workplaces are broadly virtual, and many contracts govern the use and ownership of intangible products. So, it only seems fitting that artificial intelligence (AI) plays a key role in enhancing contract lifecycle management (CLM).
Increasingly, contracts are becoming complex, as legal departments endeavor to cover every potential eventuality, and keep pace with the evolving risk and compliance environment. And as businesses grow organically — or through mergers and acquisitions — they accumulate large repositories of buy-side, sell-side, and operational agreements.
Business executives, corporate legal professionals, and contract managers often find it challenging to understand all of their commitments to customers, partners, and employees. Not to mention all of the covenants their suppliers and other parties have been made to them.
To better understand the future of AI in CLM, it is best to take a 20,000-ft view of its current state.
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Taking AI-Infused Contract Management from Creation to Approval and Beyond
Select leading CLM applications have automations or enhancements throughout the contract lifecycle. Among their many functions, they:
*Author contracts with assembly of pre-approved templates, clauses, and terms
*Review contract language for intolerable risk, compliance, errors, or liability exposure
*Analyze in-flight contracts for revisions, terminations, or upcoming renewals
*Deeply understand obligations and potential penalties for missing milestones or service level commitments
*Allow for advanced cognitive searches and natural language queries
However, even the most intelligent CLM suites on the market are only as effective as they are implemented and configured to be. That is relative to a company’s contract management workflows and practices. Nevertheless, AI functions like machine learning, robotic process automation, and natural language processing (NLP) all play key roles in delivering real value to organizations across industries.
Looking at the Future of CLM
Peering into the swirling mists of the crystal ball, one has to wonder what user experience will be like when it comes to AI-powered contract management. Speculating on what is to come in the realm of contract management is interesting to say the least. But the future depends on demand in the CLM marketplace, and the imagination and understanding of technical and business process engineers.
Facilitating Document Migrations and Profiling
Companies with large backfiles of contract and associated documents often find it challenging to export documents from their existing environment and preparing them for their new, AI-infused home. That is especially true if they have thousands — or even hundreds of thousands — of agreements in their archive.
So, will AI take over the process of making contracts discoverable by key criteria, like client names, authoring dates, contract managers, or other critical information? Well, for now at least, large migration processes are best handled by migration teams of attorneys, business process experts, and technology engineers.
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Helping Negotiation Partners on Both Sides of the Table
There are certainly improvements to be made in the negotiation process, and fortunately, AI and automation can help with that also.
Today, the security and privacy of online collaborative negotiations has quickly advanced, version control has rapidly evolved, and digital signatures are widely accepted. AI-powered CLM applications offer time-based triggers that accelerate negotiation partners’ reviews or alternatives to terms when negotiations are stalled. That is based on acceptable concessions from previous negotiations, of course.
Enhancing Risk and Audit Exposure Identification and Mitigation
Without question, getting a true audit of your contract library can be difficult and even expensive. However, a simulated audit based on the latest privacy, financial regulatory, industry, and legal standards can help surface and remediate any problems lurking in your contract drafts and active contract libraries.
Expanding the Scope of AI Access Across Data Repositories
Within many legal departments, contract management is an ideal use for AI. So, there are sure to be opportunities to expand the technology into all legal practice management platforms. After all, there are many other use cases for AI-based data processing across the legal, sales, finance, and operations departments. It stands to reason, then, that a centralized, highly scalable AI engine can be given broader access to data repositories — those that serve these other parts of the business.
Given that CLM platforms are integrated with partner applications, too, there are other possibilities for cognitive analytics, business process automation, machine learning algorithms, and NLP. Such broader access to relevant data — in disparate repositories — can positively affect the contract assembly, review, or negotiation phases within contract lifecycle management.
Determining the Next Steps
Based on the achievements already made in this space, do you have any insights on — or ideas about — how AI should further advance contract lifecycle management? Perhaps you have already sent a feature request to a CLM platform vendor. Perhaps you have penciled or inked them into a product roadmap. Either way, ideas are the fuel of successful human innovation; they cannot be kept under the proverbial hat.
Viraj Chaudhary is the Chief Operations Officer at ContractPodAi. He provides legal technology domain expertise for all new initiatives and supports overall project delivery to end customers.
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