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Stop Reading Contracts, Part 1: Drive Efficiency with Advanced CLM AI

April 24, 2024

As artificial intelligence (AI) rapidly reshapes the landscape of organizational management, contract AI is becoming a prime mover in streamlining operations and enhancing efficiency. 

And the better the AI being deployed, the more impressive the gains.

The utilization of AI in contract lifecycle management (CLM) does more than simplify the administration of agreements. It also provides powerful tools for analytics, compliance tracking, and risk management, and can even contribute to the profitability, growth, and resilience of an organization – if it’s advanced enough.

Why adopt advanced contract AI?

It boils down to cost, efficiency, and control, as recent research explains:

  • An EY study found an average basic contract costs nearly $7,000 to create, while complex contracts averaged $50,000.
  • According to World Commerce & Consulting, a Fortune 2000 company has 20,000 to 40,000 contracts under management at any one time; manually reviewing them for any purpose can be intensely time-consuming and costly.
  • Cottrill Research points out that the contract process devours 18% of the selling cycle, on average.
  • The Association of Corporate Counsel reported that 80.8% of in-house lawyers had to participate in contract management by reviewing and drafting documents.
  • As recently as 2023, most legal departments were having to rely on disparate non-contracting tech solutions for contract lifecycle management; SharePoint was far and away the most-used “contract management” tool.

Fundamentals of AI in contract management

AI improves contract management processes by introducing automation and data analytics. They can facilitate the reading and understanding of contract language, allowing for more streamlined and efficient contract reviews, and deliver these core capabilities:

  • Data extraction: AI can automatically extract key information such as parties involved, contract values, dates, and renewal terms. This reduces the need for manual data entry and minimizes human error.
  • Risk assessment: By analyzing contract terms, AI identifies potential risks and suggests mitigations. AI tools can compare new contracts against a database of existing contracts to flag unusual or potentially harmful clauses.
  • Workflow optimization: AI streamlines contract approval workflows through automation, routing contracts to the right individuals for review and signature based on predefined rules and learned patterns.
  • Compliance monitoring: Continuously monitoring for compliance, AI systems can alert when contracts meaningfully deviate from regulatory standards or internal policies, facilitating real-time compliance management.
  • Contract analysis: AI engines utilize natural language processing (NLP) and large language models (LLMs) to parse complex legal jargon and provide insights such as contract term summarization or negotiation points.

The integration of AI into contract management reduces the time and resources spent on contract-related tasks, allowing legal and procurement teams to devote time to work more deserving of their professional skills. Plus, a good contract AI solution’s ability to continually deliver deep insights into a customer’s contract corpus means they can continuously enhance their business practices. 

What are key benefits of contract AI?

Let’s run through the list of fundamental benefits that an AI-powered contract lifecycle management solution should be able to deliver:

  • Resource optimization: By automating routine tasks, it allows your organization to redirect resources from contract administration to strategic initiatives, optimizing the utilization of legal and legal operations staffers and reducing operational costs.
  • Task automation: Contract AI brings to the table advanced granular capabilities such as the extraction of key contract terms, alerting relevant parties about milestones or renewals, and providing insights about your obligations you can use in monitoring obligation performance.  
  • Error reduction: Automation can reduce the chance of human error and ensure greater consistency in operations while enhancing decision-making processes. 
  • Scalability and flexibility: Organizations that use AI-powered contract management can efficiently handle large volumes of contracts, scale their operations effectively, and remain adaptable in a rapidly changing business environment.
  • Automatic compliance upkeep: Users can stay ahead of legal developments and remain compliant with changing regulations without investing large manual resources. 
  • Customization: A customizable AI solution can be trained on an organization’s specific and relevant contract data so it understands what to search for within those contracts.
  • Strategic collaboration: A proper implementation of advanced contract AI can set up legal operations (or other contract professionals, such as Procurement) to leverage the contract corpus as a strategic asset that supports growth and business success.

How have Microsoft, Workday, and other leading companies leveraged customizable contract AI to realize savings and contain risk?

Enhancing operational efficiency with contract AI

Contract AI can be a pivotal tool in optimizing operational efficiency. By enhancing contract management, automating and streamlining operations, and improving data analysis, it can help drive significant time and cost savings.

Streamlining contract processes

AI can revolutionize contract management by automating and accelerating contract management processes. What key capabilities does it deliver to accomplish this?

  • Critical data extraction: Key dates, clauses, and obligations are quickly and automatically identified, reducing errors.
  • Contract workflow standardization: Systematizing processes results in consistency, predictability and reductions in costs and mistakes.
  • Risk assessment: AI tools can predict potential risks by analyzing historical contract data.

Data management and analysis

Organizations may be dealing with huge amounts of contract data that can be efficiently managed and analyzed using a contract AI solution by:

  • Organizing data: An AI can collate data from all ingested contracts into a structured format in a centralized contract repository.
  • Insight generation: Contract AI algorithms detect patterns and trends, facilitating informed decision-making.

Automating routine tasks

Contract AI software excels at taking over time-consuming and repetitive tasks. This ensures tasks get completed quickly and accurately, while employees can spend their time on more strategic activities. Some 

  • Document processing: AI systems ingest, process and categorize documents much  faster than human counterparts, with far fewer errors.
  • Self-service review of customer/client contracts: Contract AI systems can make this quick and simple, especially if they leverage conversational AI allowing users to make queries about their contracts using simple, natural language to receive clear, insightful answers.

See how: Contract AI took mere seconds to process a healthcare provider’s “least decipherable documents.” Read more →

Find out how

Evisort

can help your team

Test Evisort on your own contracts to see how you can save time, reduce risk, and accelerate deals.

Strategic advantages of AI for the organization

Adopting contract AI can bring transformative benefits, particularly when it comes to efficiency improvements, enhancing decision-making processes, reducing risk, and gaining a superior competitive stance. By employing contract AI, organizations can decisively boost both their internal operations and their business standing and potential for success.

Informed decision-making

  • Data analysis: AI systems excel at processing vast amounts of data swiftly, which enables organizations to surface patterns and insights in their contracts that humans may overlook.
  • Precision: AI contributes to more accurate forecasts and trend analyses.
  • Speed and agility: Organizations can react in real-time to changing market or business conditions.

Risk assessment and management

  • Contract visibility for regulatory compliance: Visibility allows organizations to ensure that contracts and agreements are in accord with regulations and standards.
  • Isolate and mitigate risk: The ability to identify risk within the contract corpus means it can be remediated.

Competitive edge

  • Greater innovation: AI fosters innovation by automating routine contracting tasks, allowing employees to focus on strategic activities that drive growth – and that are more professionally gratifying.
  • Process optimization: Streamlining and automating routine or time-consuming tasks cuts operational costs and errors.
  • Revenue optimization: A better understanding of contracts creates upsell and renewal management opportunities.  
  • Operational excellence: This results from using AI to support a culture of continuous improvement.
  • Customer experience: By optimizing contract processes, reducing errors and disputes and more. 

Measuring the impact of CLM AI on organizational efficiency

The adoption of AI within organizations has tangible effects on efficiency, sometimes quite rapid. These can be quantified through specific metrics and financial assessments.

Key performance indicators

Organizations usually deploy key performance indicators (KPIs) to assess AI's effectiveness. They’re indicators that provide objective measures to monitor and evaluate the success of AI implementations. In evaluating contract AI, these KPIs can include:

  • Execution speed: Time taken to complete processes; in this case, contract turnaround time, meaning the average time it takes to draft, review and finish a contract, including revisions, approvals, and signatures
  • Speed of contract ingestion and processing: The time it takes to input/scan contracts into a system and process them into digital format.
  • Accuracy: Error rate reductions in tasks performed by AI systems will contribute to expediting the drafting, review, analysis and approval of contracts.
  • Employee productivity: Staff output can be elevated as their skills are put to better use as contract AI assumes previously manual tasks. 
  • Stakeholder/customer satisfaction: Improvement in the contracting process results in faster and more positive experiences for internal clients, company leaders and business customers.

Cost-benefit analysis

A cost-benefit analysis (CBA) is critical for weighing the financial investment in a contract AI solution against the economic advantages acquired by the organization. This analysis includes:

  • Initial and ongoing costs: Capital expenditure on AI technology and continuous operational expenses.
  • Return on Investment (ROI): Increased revenue or decreased costs directly attributed to AI over time. This includes any operational savings realized by improving processes, and other savings or revenue gains created through contract optimization.

Not all contact AI solutions are equal in improving efficiency

As of this post, the software review site G2 lists 99 different CLM products. As in any tech segment, it’s likely more providers will jump into the fray before the inevitable shakeout. Some will inevitably be better than others.

As we said at the start, the more advanced and purpose-built a contract AI is, the better it will perform. That’s because the complexities of contract management and compliance are best addressed with AI-native platforms designed from the ground up to optimize contract lifecycle management and analysis. That’s unlike some other offerings that  “white-label” GPT or other third-party AI platforms for limited, discrete functions.

What are some of the key features that enable AI-native CLM AIs to drive bigger efficiency gains and ROI?

A proprietary large language model (LLM)

Other solutions might use generic, third-party AI, while an AI-native solution boasts its own LLM specifically designed for contracts, resulting in:

  • Improved accuracy and efficiency: An LLM trained on a massive dataset of legal documents can understand contract language nuances more effectively than generic LLMs, producing higher accuracy in contract analysis, clause identification, and risk assessment, leading to faster review times.
  • Greater control over your contract data: When you use a provider with its own proprietary LLM, you will have clear visibility into how your contract data is used. 
  • A direct feedback channel: As the customer of a “GPT-wrapper” solution that merely incorporates a third-party solution, you do not have a direct line of communication with the people who build and maintain the LLM. Providers with a proprietary LLM, on the other hand, are able to take your feedback and use it to make the product better for you.

Focus on automation

An advanced contract AI solution prioritizes automating repetitive tasks within the contract lifecycle by using:

  • Automated contract ingestion, extraction, and key term capture: It can quickly and automatically extract contract data that your organization has specifically deemed relevant for precise search and analytics, eliminating manual data entry and freeing legal teams for higher-value tasks.
  • Accelerated workflows: It will automate contract drafting and negotiation by automating clause creation and redlining, streamlining workflows and limiting legal bottlenecks.

Enhanced search and analytics

How do better search and analytics improve efficiency?

  • Advanced search functionality: With this, legal teams can search for specific contract terms or clauses across the entire contract repository using natural language queries. This eliminates the need for manual searches through large volumes of documents.
  • Surface risks and opportunities faster: Potential contract risks or negotiation opportunities can be proactively identified so they can be addressed before they become issues, saving time and resources.

Integration and user experience

A good AI-native CLM solution can provide a seamless user experience that integrates with existing workflows. This includes:

  • Intuitive interface: A user-friendly interface and the use of natural language “conversational” AI can minimize the learning curve for legal teams.
  • Pre-built and custom integrations: Leverage pre-built and custom integrations to efficiently pass critical contract data surfaced by AI to the tools your teams work with every day, such as ERP, CRM, procure-to-pay, and productivity solutions, saving time and effort throughout your organization.

Conclusion: A new tool for enterprise efficiency

Improving operational efficiency is a goal that’s almost universally desired, especially among organizations of any real size and success. 

Advanced CLM AI can contribute to elevating that efficiency. A well-built AI-native solution not only improves legal or contracting processes, but can deliver powerful analytics and insights that can benefit other stakeholders and business units across the enterprise.

How? In the next post in this series, we’ll explore why it’s critically important for an organization to understand everything about its contracts – and how that pays off on multiple fronts.

Related Resources

On-demand Webinar

FinServe Compliance using Responsible AI

Guide

Customizable Contract AI

On-demand Webinar

Contract with Care: How Healthcare Organizations Are Using Contract AI for Compliance, Finance, and Procurement

Find out how

Evisort

can help your team

Test Evisort on your own contracts to see how you can save time, reduce risk, and accelerate deals.