A comprehensive, disciplined approach to contract lifecycle management (CLM) is critical to navigating the volume and complexities of business agreements today. According to the 2025 CLOC State of the Industry Report, 62% of organizations are using CLM technology to achieve this.
While CLM solutions can streamline and add structure to some or all aspects of the contract lifecycle, the game and opportunity to improve processes has changed significantly in this age of generative AI.
Just over half (54%) of the CLOC report respondents plan to implement AI and 33% plan to adopt workflow tools within the next one to two years. It’s with good reason – generative AI promises unprecedented efficiency, accuracy, and scalability. But achieving those benefits requires a strong understanding of the CLM solution landscape and the use cases and approach for applying this technology.
5 Ways Generative AI is Advancing Innovation in CLM
Generative AI is just beginning to fully integrate across the contracting lifecycle, from pre- to post-execution. Many of today’s providers specialize in niche processes only. Here are five examples of where generative AI is boosting the capabilities of CLM tools.
- Metadata abstraction
Instead of manually entering key information (like payment terms, deadlines, or parties involved), generative AI automatically extracts these data points from uploaded contracts and populates them within the system. Benefit: Streamlined data entry.
- Review and redlining
Traditional CLM platforms rely on pre-configured clause libraries for drafting and reviewing. Generative AI eliminates this dependency by analyzing legacy contracts, creating a repository of fallback clauses, and suggesting replacements or edits during the review process. Benefit: Faster negotiations.
- Clause libraries
Generative AI can build a clause library dynamically in real time. When drafting or reviewing contracts, users can pick clauses and fallback options directly informed by historical patterns. Benefit: Compliance and consistency.
- Language support
Generative AI solutions now support processing contracts in up to six or seven languages. This helps global organizations efficiently manage multilingual agreements without the burden of translation efforts. Benefit: Global capabilities.
- Search and query
Some advanced CLM platforms are embedding AI-powered search capabilities through integration with platforms like ChatGPT. Users can query systems for specific contract-related information, and the AI pulls relevant clauses, obligations, or details instantly. Benefit: Time savings.
Legal Liability: Negligence and Legal Malpractice
Attorneys have a duty of care to safeguard client funds and confidential information. If attorneys fail to implement cybersecurity safeguards, it can result in disciplinary action, malpractice claims, and reputational damage.
- Negligence: Clients can claim that an attorney failed to implement reasonable cybersecurity measures, such as verifying wire instructions by phone, using multi-factor authentication, or securing email communications.
- Legal Malpractice: If an attorney's failure to implement adequate cybersecurity measures results in financial harm to the client, they may face malpractice claims. The ABA Model Rules of Professional Conduct, particularly Rule 1.1 (Competence) and Rule 1.6 (Confidentiality), require attorneys to take reasonable steps to protect sensitive client information.
Even if an attorney did not knowingly facilitate a fraudulent transaction, failing to take preventive measures can expose them to liability. To mitigate these risks, attorneys must adopt proactive cybersecurity governance, including client data protection strategies and thorough verification protocols.
The Biggest Misconception of Generative AI and CLM
It’s important to note that the use of generative AI and CLM tools doesn’t have to be mutually exclusive.
Some CLM platforms have started embedding generative AI features into their workflows. If you already have a CLM system, oftentimes a generative AI module can be seamlessly added.
Taking Advantage of Service Providers in the CLM Space
There are two main ways to partner with a service provider to optimize the use of generative AI-enabled CLM technology.
Organizations can take a tech-as-a-service approach. This strategy allows businesses to partner with service providers who already have an AI tech stack – like Integreon – to pilot AI solutions before committing to licenses or infrastructure. Benefits: Lower costs, reduced risk, and access to expert guidance.
For those who do take on the investment and implementation of CLM tools, service providers can help in several ways:
- Expert configuration of generative AI modules
- Playbook development and iterative updates
- Modular AI deployment that aligns with specific use cases
- End-to-end support for contract abstraction, redlining, and review
The result of this level of support: faster return on tech investment. And a greater certainty of long-term success.
Whether you’re working with an existing CLM or exploring a standalone AI solution, understanding your organization’s needs and future goals is key to success. The innovation of generative AI within the CLM space is far from over, and organizations will need to continually evolve their strategies to drive ongoing ROI from their CLM tools.
