As artificial intelligence (AI) becomes the norm in legal operations, more and more legal teams are using it to handle contracts efficiently.
As the technology continues to evolve, there is a growing emphasis on the role of AI in addressing complexities in contract management, adapting to regulatory changes, and enhancing collaboration among stakeholders.
The 2024 ACC Chief Legal Officers report shows that 45% of chief legal officers (CLOs) will invest in new technology solutions to boost operational efficiency in 2024 — the highest since 2021. This sudden increase underscores a rising recognition within organizations of the powerful impact that efficient contract management processes can have.
In this article, we’ll explore best practices for implementing AI in contract management and the fundamental concept of AI in this context.
AI in contract management refers to the simulation of human intelligence processes by computer systems to streamline and enhance various aspects of the contract lifecycle.
The application extends from the creation and negotiation stages to contract analysis, compliance monitoring, and even contract optimization. AI increases efficiency and accuracy by minimizing human errors and reducing the time and resources required for contract-related processes.
Capabilities of AI have expanded from early rule-based systems to sophisticated machine learning models. The current state reflects a landscape where organizations increasingly adopt AI-powered contract management solutions to stay competitive and mitigate operational challenges.
This involves using machine learning algorithms, natural language processing (NLP), and automation to improve the efficiency, accuracy, and overall effectiveness of managing contracts. These solutions contribute to better decision-making by providing valuable data-driven insights.
Generative AI or GenAI, a term coined to represent the next generation of AI, is profoundly influencing the field of contract management.
GenAI’s advanced capabilities in understanding context, recognizing patterns, and continuous learning help comprehend complex legal language, identify subtle nuances in negotiations, and adapt to evolving business needs. Organizations using this technology in contract management experience improved decision-making, faster contract cycles, and enhanced risk mitigation.
As GenAI continues to evolve, its impact on contract management is expected to deepen, bringing in increased efficiency, transparency, and strategic value in handling contractual relationships.
Traditional contract management for in-house legal teams often grapples with challenges such as time-consuming manual processes, potential errors, and difficulties in ensuring compliance.
CLOs are actively looking for solutions in AI technology. According to the report, “67% of CLOs believe that AI will have a 'mostly positive' or “'somewhat positive' impact on the in-house legal profession, with 35% saying that the applications with the most potential will be in document analysis and 28% saying drafting documents.”
According to a 2023 survey report, just 4% of legal teams using manual processes for contract management claim they have a deep understanding of key contractual risks to their organizations, while 87% of businesses using an automated CLM claim better visibility of contract risks.
AI systems excel in ensuring accuracy and compliance, mitigating legal risks, and enhancing the overall quality of contract management processes. Additional benefits of AI in CLM are as follows:
AI-powered contract management systems excel at automating routine and time-consuming tasks, such as data extraction, contract creation, and analysis.
With machine learning algorithms, these systems can quickly and accurately process large volumes of contractual data, allowing legal teams to allocate their time and expertise to more strategic and nuanced aspects of contract management.
Historically, legal professionals spent considerable time manually reviewing and drafting contracts, which not only consumed valuable resources but also left room for human errors. Nowadays, these labor-intensive tasks can be streamlined, thanks to AI.
It’s no wonder regulations and enforcement are keeping CLOs up at night, with 53% of them identifying these as the top concern among their three main worries for 2024. One of the significant advantages of implementing AI in CLM is improved adherence to regulations.
With AI, CLM platforms can swiftly analyze vast volumes of contracts, identifying potential regulatory risks and discrepancies. This not only saves valuable time but also mitigates the chances of human error.
Moreover, AI algorithms can continuously learn and adapt to changing regulations, ensuring that organizations remain up-to-date and compliant. When combined with human expertise, AI augments decision-making processes, providing nuanced insights that lead to more precise, legally sound contracts. This collaborative approach not only fortifies regulatory adherence but also amplifies the overall accuracy and effectiveness of CLM operations.
AI embedded within CLM systems revolutionizes business insights by extracting rich data and generating valuable insights from contracts. Through advanced NLP and machine learning, AI can quickly sift through contract clauses, terms, and conditions, extracting information on pricing, obligations, and risks. This data is then transformed into actionable insights, revealing trends, patterns, and potential opportunities.
AI-driven contract management systems come equipped with a range of features essential for optimal performance.
Essential Features for Contract Lifecycle Management (CLM) Software
Source: ContractPodAi
Organizations across all sectors are struggling with questions around AI — where to start, how to start, what use cases, and what solutions. The landscape is diverse and becoming more complex as new solutions emerge, with innovations happening at lightning speed.
As organizations increasingly adopt AI technologies, it becomes crucial to follow best practices to ensure successful integration and maximize the benefits of AI in contract management. Here are eight key areas to focus on:
Before diving into AI implementation, clearly define the objectives and scope of the project. Identify specific pain points in your contract management process that AI can address. Whether it's reducing manual errors, improving document searchability, or enhancing risk analysis, having a well-defined scope ensures focused efforts and measurable outcomes.
Selecting the appropriate AI technology is critical for successful implementation. Depending on your needs, you may consider NLP for understanding and extracting information from contracts, machine learning for predictive analysis, or optical character recognition (OCR) for document scanning. Evaluate different solutions and choose the one that aligns best with your organization's goals.
Ensure seamless integration with existing contract management systems and other enterprise applications. This integration not only facilitates a smooth transition but also enhances the overall efficiency of your business processes. Compatibility with existing tools promotes user adoption and minimizes disruptions.
AI-driven contract management involves handling sensitive and confidential information. Prioritize data security and compliance with industry regulations. Implement encryption, access controls, and regular security audits to safeguard sensitive contract data. Complying with privacy regulations such as GDPR and HIPAA is crucial for maintaining trust and avoiding legal issues.
Invest in comprehensive training programs to familiarize users with the new AI-driven contract management system. Ensure that employees understand how to leverage the technology effectively and address any concerns or resistance to change. Continuous education and feedback loops contribute to a smoother transition and optimize the use of AI tools.
AI is only as effective as the data it processes. Implement robust document management processes to ensure high-quality input for AI algorithms. Standardize document formats, clean up data inconsistencies, and establish a centralized repository for easy access and retrieval. Well-organized data improves the accuracy of AI-driven analyses.
Regularly monitor the performance of your AI-driven contract management system and assess its impact on key performance indicators (KPIs). Use feedback from users and analytics to identify areas for improvement and optimization. AI systems can learn and adapt over time, so ongoing evaluation is crucial for maximizing their effectiveness.
Consider the scalability of your AI-driven contract management solution. As your organization grows and the volume of contracts increases, the system should be able to handle the added load. Plan for scalability from the outset and choose technologies that can grow with your business.
In assessing your organization's contract management needs, it's important to evaluate key aspects to shed light on current strengths and areas for improvement, guiding efforts to enhance efficiency and optimize processes.
When you’re ready to choose a CLM solution, you need to evaluate the various options available in the market. But prior to selecting a shortlist of providers, to narrow down your choices, you’ll assess the providers based on the following five initial criteria:
The effectiveness of a company's CLM product is crucial in making a decision.
It's important to look at the range of functionalities available, not just for immediate needs but also for potential future needs like digital transformation and increased value generation. This strategic approach can prevent the need for another CLM search in one to two years.
Product functionality assessment should also consider scalability and precision. Scalability involves the automation and AI capabilities of the tool, allowing for seamless growth as your business expands. Cognitive precision refers to the tool's ability to manage complex contracts and data with its automation and AI alongside standard or template contracts.
Implementation support is vital in a CLM offering. CLM implementation is not a simple 'plug and play' process, and might lead to common errors if not implemented properly. A successful deployment involves software setup, migration of existing contracts, configuring AI features tailored to your business's contract and compliance needs, and integrating with other enterprise software for maximum efficiency.
Pricing is a top priority of any CLM search, closely tied to ROI (return on investment). Additional functionality typically leads to increased value for clients. However, more important than ROI is the tactical plan your CLM provider offers to help you attain that return and their dedication to your success. We’ll discuss ROI in more detail below.
Evaluating providers based on their customer retention, supported by direct customer feedback, is crucial. Failed implementations often lead to customer churn, followed closely by a lack of functionality for ongoing process improvement.
Given that the contract management industry is still relatively new, there are many new providers. Assessing business history (at least 5 years old), current customer base (at least 50 similar enterprise clients), and funding levels (minimum $40 million) can help gauge business viability and reduce customer risk.
Gauging and measuring the impact of CLM software provides a tangible means to demonstrate the success of the software to stakeholders and executives, showcasing its value in terms of efficiency, cost savings, and risk mitigation.
Secondly, these metrics highlight areas within the CLM process that might need improvement, allowing for targeted enhancements to optimize workflows and outcomes. Establishing benchmarks through measurement creates a foundation for future evaluations, enabling organizations to track progress over time and make informed decisions about the software's ongoing utilization and potential upgrades.
KPIs collectively form a robust framework for organizations to assess and optimize the impact of AI in contract management.
Tracking KPIs might consist of:
In the short term, ROI in CLM software manifests through streamlined processes. Automation of contract creation, negotiation, and approval drastically reduces the time and effort required for these tasks, boosting operational efficiency.
Teams can quickly locate contracts, track key dates, and ensure compliance, minimizing errors and delays. This leads to immediate cost savings by reducing manual labor hours and mitigating risks associated with missed deadlines or non-compliant contracts.
Looking to the long term, the benefits of CLM software investment become even more profound.
of companies lose their bottom line through poor contract management.
Source: World Commerce & Contracting
On a more conservative note, research from Ernst & Young found that the average company loses anywhere from 1% to 5% of EBITA from its bottom line due to ineffective contract management. The value within your company will depend on the challenges your operation faces.
Implementing AI in contract management can yield various long-term advantages, enhancing efficiency, accuracy, and overall effectiveness in handling contracts. Here are some key long-term benefits of ROI from AI implementation in contract management:
AI can automate repetitive tasks, such as data entry, document review, and contract drafting. This reduces the time and effort required for manual work, allowing teams to focus on more strategic and value-added activities.
AI streamlines the contract lifecycle, from creation to negotiation, approval, and renewal, leading to faster turnaround times. This, in turn, accelerates business processes and reduces delays, contributing to cost savings.
AI-powered systems can significantly reduce human errors in contract creation and review, leading to more accurate contracts and minimizing the risk of legal issues.
It helps organizations stay compliant with changing regulations by automatically flagging potential compliance issues, reducing the risk of legal penalties and fines.
AI can analyze large volumes of contract data to identify patterns, risks, and opportunities. This allows organizations to proactively manage and mitigate risks associated with contracts, ensuring better decision-making and protecting against potential liabilities.
AI-powered contract management systems provide real-time insights into the status and performance of contracts. This transparency enhances visibility for stakeholders, allowing them to make informed decisions and respond quickly to changing circumstances.
AI can create comprehensive audit trails, tracking all changes and activities related to contracts. This ensures accountability and facilitates compliance with internal policies and external regulations.
AI analyzes historical contract data, providing valuable insights for strategic decision-making. Organizations can identify trends, optimize contract terms, and negotiate more favorable agreements based on data-driven intelligence.
With AI automating routine tasks, organizations can allocate human resources to more strategic and high-value activities, contributing to overall business growth and innovation.
AI-powered contract management systems are scalable, allowing organizations to adapt to changes in contract volume and complexity without a proportional increase in workforce. This scalability is particularly beneficial for growing businesses.
AI enables better collaboration among teams involved in contract management. Teams can work simultaneously on contracts, access real-time updates, and collaborate seamlessly, leading to improved communication and efficiency.
The long-term advantages of ROI from AI implementation in contract management extend beyond immediate gains, providing a foundation for sustainable growth, improved risk management, and strategic decision-making within organizations.
The pursuit of continuous improvement is imperative by the need to stay current with AI advancements. Regular updates play a pivotal role not only in enhancing AI system performance and efficiency but also in addressing security vulnerabilities and ensuring compliance with standards.
Organizations can follow a set of valuable tips for continuous improvement. These include:
The integration of AI in contract management is not merely a trend but a strategic move toward efficiency and compliance.
As AI continues to evolve, in-house legal teams that embrace these technologies are poised to navigate the complexities of contract management with greater agility and effectiveness. The future promises exciting developments, making AI an indispensable tool in the arsenal of modern legal operations.
Unlock the power of efficient contract management with the right software—discover how today!
Edited by Sinchana Mistry
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