Intelligent CLM vs. Traditional Contract Management: What’s the Difference?

Contract management plays a pivotal role in business operations across industries, ensuring smooth transactions and compliance. Today, enterprises are increasingly leveraging AI-powered contracting tools to stay competitive in the market. Traditionally, the contracting process has been labor-intensive following legacy AI-model set up. However, with the advent of NextGen AI and other advancements in technology like Agentic AI, intelligent CLM is emerging as a game-changer.

^{Traditional Contract Management: Legacy Siloed Approach}

Traditional contract management relies heavily on siloed processes for contract drafting, reviewing, negotiating, storing contracts. Each step in contracting processes requires significant human intervention, which can be time-consuming and greatly prone to errors. Traditional mode of contracting has the following attributes:

File-Based Documentation: Today, many traditional contracting systems still use file and folder-based documentation, storing in email folders or local drives that remain dormant for years, and on requirement, cannot be retrieved owing to lack of data insights. In short, traditional contracting does not have centralized repositories and siloed data systems that cause inefficiencies leading to challenges in storage, retrieval, traceability and sharing of contracts. This can result in inefficiencies and increased risk of document misplacement, sensitive information leakages and other inevitable losses.

Human-Driven Negotiations: Contract negotiations in traditional contract management are typically conducted by humans, which can be a lengthy and complex process. The outcome of negotiations can vary greatly depending on the skills and experience of the legal teams involved. Moreover, lack of data insights and analytics leads to inaccurate data representation and inefficiency in the ecosystem hugely impacting turnaround times.  

Scattered Storage: Traditional AI-model with decentralized locations has limitations as contract data get stored in scattered manner such as on emails, hard disks, local drives. This leads to data loss and theft resulting in revenue loss.  

Limited Automation: Automation in traditional contract management is often limited to basic tasks, and extracting actionable insights from contracts is challenging due to data silos and a lack of centralized, accessible reporting tools. This lack of visibility can lead to missed savings, compliance risks, and inefficiencies.

Compliance and Risk Management: Ensuring compliance with legal and regulatory requirements is a critical aspect of traditional contract management. However, manual processes can make it challenging to consistently adhere to these requirements, increasing the risk of non-compliance.

^{Intelligent CLM: AI Assistants for Seamless Process}

AI-Powered Automation: Intelligent CLM leverages AI-assistants' capabilities to automate various aspects of the contract lifecycle. This includes drafting, reviewing, and negotiating contracts. AI assistants such as Data Extractor and Risk Analyzer can analyze large volumes of data to identify patterns, risks and make informed decisions, significantly reducing the need for human intervention.

Digital Documentation: With an intelligent contracting system, all documents are digital, making storage, retrieval, and sharing more efficient. Centralized repositories allow smooth contract management, digital contracts are easier to manage and can be accessed from anywhere, enhancing collaboration and reducing the risk of document loss.

Advanced Analytics: AI-powered systems can provide advanced analytics and insights, helping enterprises make better decisions. These systems can analyze past contracts to identify   potential contractual risks, enabling proactive management of contract portfolios.  AI-assistant risk analyzer provides scorecard of risk levels ranging from low, medium to high categories. Based on risk level, risk analyzer gives personalized recommendations and suggestions driving goals. Thus, the assistant   proactively assesses the risks of clauses and terms and monitor deviations in third-party contracts in real-time.

Automated Negotiations: Intelligent contracting systems can conduct negotiations using predefined rules and algorithms. This can speed up the negotiation process and ensure consistency in outcomes. While human oversight is still important, AI–assistants can handle many routine negotiation tasks. For instance, AI-assistant Data Explorer talks to your contracts in simple, natural language about prevailing terms, legal precedents, and more.  

Enhanced Compliance and Risk Management: AI contracting assistants like Risk Analyzer  can continuously monitor contracts for compliance with legal and regulatory requirements. It can also identify potential risks and suggest mitigation strategies, helping organizations stay compliant and reduce risk.

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_{Wrapping Up}

While traditional contract management has served businesses well for many years, the rise of intelligent contracting offers significant advantages. In traditional contracting, the lack of advanced automation means that many tasks must be handled manually, which can slow down the process. On the other hand, by leveraging AI and automation, organizations can streamline their contract processes, reduce errors, and enhance compliance. As technology continues to evolve, intelligent CLM is going to become the new standard in contract management, offering a more efficient and effective way to manage business agreements.

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Discover how Intelligent CLM can help your legal teams streamline and secure contracts. Reach us for a demo.

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