This article outlines the stages of CLM maturity and how Artificial Intelligence (AI) can be strategically integrated at each level to drive efficiency, reduce risk, and maximise business value.

Organisations of all sizes are embracing AI to layer into current or improved business processes for the purpose of efficiency, self-service, business intelligence, and more.  This is an important time for injecting AI into contracting processes as part of a Contract Lifecycle Management system.  

The Epiq CLM Maturity Model outlines the progressive stages towards enhancing contracts management:

1. Initial (Manual Process): Characterised by scattered contracts locations, limited visibility, high risk, and reactive issue management. AI can enhance this stage by providing basic AI search capabilities to improve contract location.

2. Defined: Involves basic contract and playbook templates, standardised processes, a centralised repository, basic automation, and reporting. AI can assist with automated redlining and basic clause extraction to enhance negotiation and risk assessment.

3. Managed: Features well-defined processes, automated workflows, KPIs, regular reviews, and improved collaboration. AI solutions like predictive analytics and automated contracts routing can streamline operations and proactively mitigate risks.

4. Measured: Focuses on data-driven decisions, continuous improvement, system integration, advanced reporting, and proactive risk management. AI can provide advanced analytics and reporting, along with contracts performance prediction, to offer deeper insights and improve outcomes.

5. Optimised: CLM is fully integrated into business strategy, with predictive analytics driving decision-making, continuous innovation, and significant business value. AI-powered contracts negotiation and predictive maintenance further automate and refine contracts lifecycles.

Key Benefits of AI-Powered CLM:

• Reduced Risk: Proactive identification and mitigation of potential contract risks.

• Increased Efficiency: Automation of key processes, including redlining, routing, and approvals.

• Improved Visibility: Centralised repository and advanced analytics provide a comprehensive view of contract obligations and performance.

• Cost Savings: Streamlined processes and reduced risk of non-compliance lead to significant cost reductions.

• Enhanced Collaboration: Improved communication and collaboration among stakeholders.

• Data-Driven Insights: Advanced analytics provide valuable insights for strategic decision-making.

Creating greater efficiencies, visibility, and insight with your organisation’s contracts, CLMs can work hand-in-hand with AI capabilities to take contracts generation and management to the next level. When doing so, organisations will consider the maturity of their CLM, AI, and the intersection of the two. A maturity model framework that measures and roadmaps the organisation’s awareness, readiness, and transformation with increasing sophistication and improvement will define the capability benchmarks for CLM and AI.  
By strategically integrating AI into each stage of the CLM maturity model, organisations can transform their contracts processes, unlocking significant value and achieving a competitive advantage. Moving from manual, reactive processes to data-driven, streamlined contracts management is essential for success in today's dynamic business environment.


Karthik Radhakrishnan is the Director of CLM R&D and Chief Architect at Epiq. He is an experienced Technology Leader with over 35 years of IT experience, specialising in the conception, development, and management of software applications. With over 20 years of expertise in Contract Lifecycle Management (CLM) and Configure, Price, Quote (CPQ) domains, he consistently delivers high-quality solutions to clients.