Zycus recognized as a ‘Strong Performer’ in The Forrester Wave™: Contract Lifecycle Management, Q2 2023  Read More

Artificial Intelligence powered Contract Management: Five business advantages

Businesses today possess a burgeoning matrix of contracts. As per a Pricewaterhouse Coopers (PwC) report, modern day organizations rely on an average of 20,000 to 40,000 contracts. This translates to mammoth amount of business intelligence stacked away in these contracting clauses. The sheer volume makes it cumbersome to manage and extract insights from these contracts.

Even as artificial intelligence (AI)-enabled contract lifecycle management (CLM) drives automation, it structures the entire contract lifecycle for buy-side and sell-side agreements. As a result, it delivers better risk management, profitability enhancements, and efficient timelines. Here is how AI-powered contract management can change the game.

1. Gain from smart authoring

Traditional CLM approaches offer a repository of contracting clauses, wordings and definitions. Machine learning-enabled CLM solutions go an extra mile as they sift through similar contracts from the past, identify patterns, as well as proactively recommend suitable clauses and standard definitions based on past experience.

To use an example, Al-based CLM systems prompt for the definition of “non-disclosure” to be standard across all contracts. In case of contracts across borders, AI-powered systems scan the repository for past contracts with parties in the given country,and recommend critical regulatory clauses.

2. Strengthen risk mitigation

AI is relevant to risk profiling and review as well. AI-enabled solutions can parse through documents, classify clauses, and highlight differences between the document versions.

Lawyers can now focus on risk assessment and advice rather than cumbersome reviews. Most AI-based CLM solutions use natural language processing (NLP). This enables the system to read and interpret unstructured data—akin to human comprehension capabilities. These CLM solutions can read agreements and highlight sub-optimal terms, or clauses that may not work in the firm’s interest.

3. Optimize contract review timelines

A Forrester Research study estimates average contract approval cycles to be around 3.4 weeks. Large global organizations face similar extended timelines for closure of contracts—reduction of such bottlenecks become imperative, given their scale. Use of contract management enables these firms to compress turnaround cycles considerably.

Due to the cross-functional nature of contract signing and negotiation, significant time is lost in multiple document reviews which are an added setback of e-mail-based processes, especially while dealing with various stakeholders from contracting parties. AI integrates all involved functions on to a single platform, making the e-mail process redundant. Such unified interfaces highlight changes in clauses, even as they facilitate versioning comparisons to speed up review and turnaround times.

AI technology seamlessly assimilates even third-party contracts into the system. This enables a universal view where all contracts can be reviewed in a single platform and helps in implementing policies and compliance across the contractual database.

4. Ensure better service

Verticals such as pharmaceutical and service industries face management challenges due to large volumes of partner and client contracts. Contracts vary in terms of renewal dates, key performance indicators (KPI) and engagement terms.

AI uses in-built algorithms to identify patterns in contract drafting across different languages, as well as mine important data points like dates, service level agreements (SLA) and incentives. These are then flagged for user action. Such visibility enables better compliance to terms, minimizes risk of exceeding deadlines, and ensures adherence to regulatory frameworks.

5. Get actionable data at your fingertips

As per a Harvard Business Review report, businesses lose between 5 percent to 40 percent in a single contract, owing to ineffective administration of clauses. AI-powered contract management enables organizations to derive full value out of contractual relations. Customizable alerts, reminders and user-defined dashboards ensure higher visibility of contract terms as well as better implementation of negotiated terms.

Integrating CLM solutions with existing organizational tools like ERP and CRM enables tracking of contract performance. Monitoring of vital milestones like payments, delivery schedules and license or certification renewals is yet another direct benefit. This translates into cost benefits by avoiding penalties due to incorrect or delayed payments and deadline breaches, as well as avoidance of penalties for regulatory non-compliance.

AI-powered contract management: The game changer

Aberdeen Research’s studies indicate an average of 82 percent drop in contract approval time, and optimal contract renewal rates, as high as 90 percent, by organizations using a CLM solution. Combine these with the improved productivity, contract quality and process agility, and AI-driven contract management is worth the business investment.

CLM is estimated to triple in value within the next six years, growing from $1086 million to $3167 million, as per ‘Global Enterprise Contract Management Market – Trends Analysis Product Usability Profiles & Forecasts to 2023’ report. AI will be the key impetus for this surge. AI-powered systems are changing the way businesses function, building leaner and more responsive legal teams that focus on value creation. AI harnesses the latent potential in written contracts to make it a strategic tool which identifies business opportunities and risks. Machine learning’s next evolutionary phase will enable these systems to apply contract rules as well as make informed decisions on the apt clauses and terms for every agreement.


Mr. Panchal is the Vice President at Zycus. An ardent promoter and practitioner of Theory of Constraints and CCPM, Digesh brings with him deep domain expertise from his long and rich personal experience in manufacturing. In his prior stint at Verdantis, he has led highly complex implementations of Master Data Management solutions for multiple master domains, across various industries and varied deployment models. As a forward-thinking leader with extensive experience in the design, development, testing, and rollout of cutting-edge B2B SaaS solutions, Digesh excels at driving the day-to-day operations of complex enterprises to produce turnarounds. At Zycus, Digesh is responsible for building a best-in-class AI-driven Enterprise CLM software and drive market traction.
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