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AI-Powered CLM: Redefining Efficiency & Accuracy in Legal Operations – An Interview with Industry Expert Daniela De La Vega Smith

The integration of AI into CLM is redefining how legal and compliance teams operate, providing unprecedented efficiency and accuracy in today’s rapidly evolving landscape of digital transformation. We’re thrilled to sit down with Daniela De La Vega Smith, a legal and compliance professional with over 18 years of experience in the oil and gas industry, who has become a prominent voice in exploring AI’s impact on CLM.

With her expertise spanning high-stakes contract negotiations, tender design, and regulatory compliance across North and Latin America, Daniela has a unique perspective on how AI technologies are reshaping contract processes. 

In this exclusive interview for TechBullion, Daniela offers a deep dive into how companies are leveraging AI-powered CLM to streamline workflows and enhance cross-departmental collaboration. Additionally, she shares her vision for future AI advancements that promise to revolutionize contract management, making it an essential tool for forward-thinking companies navigating today’s complex legal landscape.

AI-Powered CLM - Interview with Industry Expert Daniela De La Vega Smith

Daniela De La Vega Smith

How is AI changing the landscape of contract lifecycle management, and what are its biggest benefits to the process?

AI in conjunction with Life Cycle Systems (“LCS”) is becoming increasingly necessary and beneficial within the legal, procurement, and contracts departments due to its capacity to automate routine tasks that are time-consuming, and take valuable resources focus from more strategic tasks that require expertise, knowledge and critical thinking. 

The most relevant tasks are centered on contract reviews, answering questions related to the scope of the agreements, comparing agreements, and procuring compliance with standard practices related to the industry and corporation. With AI tools properly managed, the amount of data that can be reviewed and analyzed brings a new level of efficiency, particularly helpful for teams with limited resources. 

AI should be focused on reducing costs and margin of error due to the workloads within the legal or contract management group. Extremely repetitive and routine processes and tasks, which tend to be manual, are likely to incur errors that may impact the business. 

In what ways does AI help reduce human error in contract management, and how does this impact overall business efficiency?

The main factors that contribute to human error in contract management are work overload, repetitive and routine tasks, and involuntary oversight of details. An error made during the life cycle of a contract can significantly impact the business and most of the human errors could have been easily detected. AI can compare, summarize, and analyze the data contained in the contracts, based on the parameters provided related to the company’s policies and standards, applicable laws, previous agreements, between others, that can pick up and alert of any deviation (unintentional or intentional) from any of these standards. 

The main benefits, although simple, are extraordinary, It takes simple routine tasks from team members, especially senior professionals, and focuses on more critical and strategic matters that increase efficiency and response time to internal and external stakeholders. 

Could you explain how AI technologies enhance contract review and negotiation accuracy and speed?

Based on the solutions currently offered by AI that can be applied to contract review, they enhance, lower the possibility of human error, and make it more efficient.

AI can  summarize contracts and other relevant documents.,reports, suggest alternative clauses, and complete legal research, it may even draft simple contracts based on previous templates or companies and industries standards., this all saves time on professionals to focus on the more strategic matters and where value is added to the contract review and negotiation. 

AI also, by tracking changes made to the document and proposing alternative wording, or raising red flags based on previous contracts or disputes, it ensures a more thorough review and critical thinking to those analyzing the information and suggestions.  

Therefore, it provides the team with enough information to help set forward an actual strategy to address the negotiation in a timely matter by IA taking these tasks and helping the team have the compound information needed instantly, which makes the process more efficient.

How can AI ensure compliance with complex and evolving international regulations in contract management, particularly for global companies?

AI can help monitor regulatory content and alert of any significant regulatory changes, and new requirements on a global level, based on relevant regulatory databases. Can recommend changes to contract articles based on local jurisdictions, and generally facilitate the contract review process by notifying of any existing deviations from internal policies, regulations, and general legal obligations. This facilitates the complex controls process that companies have in place, and helps identify the evolving regulations in a more timely manner. 

What role does machine learning play in helping organizations predict risks within contracts, and how does this benefit legal and compliance teams?

The main role it plays is to help the legal, procurement, or contract management teams address and mitigate risks in the contracts by analyzing the contract data and flagging potential compliance issues that are constantly present. 

It is a challenge once a problematic clause has been identified within a contract to determine if it is contained in any other previous agreement, this learning tools can enable the companies to complete a full analysis of their contracts database and alert of its presence in any other existing agreement. This helps advertise any future issues, take corrective actions, and it can even flag the risk levels of each contract for future reference. 

Machine learning also helps to mitigate human error and oversights, by identifying risk areas that can be commonly missed due to high volume of work, and manual labor.  And every useful function is to help identify patterns that in the past have generated disputes, due to the language carried in the agreements. 

How are companies leveraging AI-powered contract management to streamline workflows and enhance collaboration across departments?

Automating repetitive tasks, such as contract reviews, summaries, data analysis, and risk management, has boosted collaboration and efficiency across teams within the company. This automation improves workflow by accelerating processing times and fostering stronger synergy. A shared database allows collaborating teams to receive alerts and updates on critical contract lifecycle stages, ensuring all stakeholders stay informed. The contracts database, with accessible functionalities, enhances communication as support requests and inquiries are now based on real-time data accessible to each team member. Additionally, the ability to analyze and predict risks is improved by feeding the database with cross-functional data from departments like supply chain, legal, and sales. This integration enables comprehensive contract performance analysis, taking external factors into account.

Looking ahead, what advancements in AI do you anticipate will further revolutionize contract management in the next few years?

I expect more enhancements in the life contract management systems and the synergy it brings between the companies’ departments, with predictive AI that will further help identify patterns to better make predictions.

Source: AI-Powered CLM: Redefining Efficiency & Accuracy in Legal Operations – An Interview with Industry Expert Daniela De La Vega Smith

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