Agentic Workflows: How Will It Change Contract Management?

What Are Agentic Workflows?

Agentic workflows are an evolution beyond traditional automation. Instead of simply following rigid, predefined steps, these AI-powered systems can understand goals, make decisions, and adapt their actions based on changing circumstances. Where standard automation excels at repetitive tasks with clear rules, agentic AI workflows can tackle complex scenarios requiring judgment and contextual understanding.

So, what are agentic workflows? Agentic AI workflows are designed to achieve specific business goals autonomously. They combine multiple technologies to understand, process, and act upon information in contracts without constant human direction.

This article will explore how these advanced systems are transforming contract management software, the technologies that power them, and the benefits they provide to organizations.

• What Are Agentic Workflows?
• Key Components of Agentic Workflows
• Common Use Cases for Agentic Workflows
• Benefits of Agentic Workflows for Contract Management
• Limitations of Agentic Workflows
• Best Practices for Using Agentic Workflows
• Example of Agentic Workflows in Contract Management
• Accelerate Contract Intelligence With Icertis

Key Components of Agentic Workflows

The power of agentic workflows comes from several technologies working together to enable truly autonomous contract management.

AI Agents

AI agents are intelligent programs that operate with specific goals and the authority to make certain decisions within defined parameters. Unlike passive tools that wait for instructions, agents actively monitor conditions, identify when action is needed, and execute those actions independently.

In contract management, these agents might monitor expiration dates, detect non-standard language, or flag potential compliance issues. The most sophisticated agents can even learn from previous contract negotiations to suggest optimal terms or anticipate potential bottlenecks in approval processes.

Natural Language Processing (NLP)

NLP enables AI agents to understand and generate human language, a crucial capability for effective contract management. Modern NLP can interpret complex legal terminology, recognize intent in contract clauses, and identify subtle differences between seemingly similar phrases that might have significant legal implications.

This technology allows agents to extract key information from contracts, compare language against approved templates, suggest alternative wording, and even draft entire sections based on business requirements. As NLP capabilities grow, these systems become increasingly skilled at understanding context and nuance in legal documents.

Robotic Process Automation (RPA)

RPA handles the structured, rule-based aspects of contract workflows. These digital workers excel at repetitive tasks, such as extracting data from contracts, populating templates, moving documents through approval chains, or updating records in multiple systems simultaneously.

While less sophisticated than AI agents, RPA components are essential for handling high-volume, standardized activities that would otherwise consume valuable human time. They are the workhorses of AI agentic frameworks, reliably executing routine operations while more advanced AI components handle complex decisions.

Workflow Orchestration

Orchestration systems coordinate activities of different agents and automated processes across the entire contract lifecycle. This component ensures that each task occurs in the proper sequence, with the correct information available at the appropriate time.

For example, orchestration might ensure that after an AI agent drafts a contract, it routes it to the correct approvers based on the contract value, then triggers an electronic signature process, and finally initiates obligation management after the contract is signed. This coordination ensures process integrity in complex contract workflows that span multiple departments and systems.

Interoperability

For agentic workflows to function effectively, they must interoperate seamlessly with other business systems. This means that AI agents must communicate and collaborate across various platforms and applications to achieve cohesive, enterprise-wide business process outcomes. This is made possible through protocols such as Agent2Agent and MCP. Interoperability with CRM, ERP, procurement, and financial systems allows agents to access critical business data and update records across the organization.

These connections enable agents to make informed decisions based on real-time business conditions. For instance, an agent might check current inventory levels before approving supply contract terms or verify budget availability before proceeding with a new service agreement. Contract AI systems can then utilize this information to make more informed recommendations.

Common Use Cases for Agentic Workflows

AI agentic workflows are already improving several aspects of contract management. Common use cases include:

• Self-service contracting: Employees can request simple agreements through conversational interfaces, with agents handling drafting, approvals, and execution without legal team involvement for standard contracts.
• Automated negotiation: AI agents can review counterparty redlines, accept standard changes, suggest alternatives for problematic terms, and only escalate truly exceptional issues to human negotiators.
• Proactive compliance monitoring: Agents continuously scan both active contracts and changing regulations to identify potential compliance gaps before they become problems.
• Intelligent obligation management: Beyond simple calendar reminders, agents can track complex interdependencies between contract obligations and proactively coordinate fulfillment activities across departments.
• Real-time risk assessment: As contracts move through drafting and negotiation, agents can evaluate evolving risk profiles and alert stakeholders when proposed changes might exceed risk tolerance thresholds.

Benefits of Agentic Workflows for Contract Management

Organizations using agentic AI workflows in contract management can expect several significant advantages:

Accelerated Contract Turnaround

Automating routine aspects of contract creation, review, and approval dramatically reduces cycle times. What once took weeks can often be completed in days or even hours. This acceleration is valuable for high-volume, time-sensitive agreements where delays directly impact business operations or revenue recognition.

Increased Accuracy and Consistency

Human error in contract management can have costly consequences. Agentic workflows maintain consistent application of approved templates, standard clauses, and business rules across all contracts. This standardization reduces risk while ensuring that agreements reflect current policies and legal requirements uniformly throughout the organization.

Improved Risk Management

Agentic workflows excel at identifying potential issues that humans might miss. AI agents can systematically check every clause against company policies, flag unusual terms, and assess risk factors across the entire contract portfolio. This comprehensive oversight helps organizations maintain compliance and avoid unfavorable commitments before they're finalized.

Smarter Workflow Routing

Traditional contract workflows often follow rigid paths regardless of a contract's specific characteristics. Agentic workflows, however, can dynamically determine optimal routing based on contract value, risk profile, urgency, or other factors. This intelligence eliminates unnecessary approvals for simple agreements while ensuring adequate scrutiny for complex or high-risk contracts.

Data-Driven Insights

As contracts move through agentic workflows, these systems capture valuable metadata about process efficiency, negotiation patterns, and contract performance. This information promotes continuous improvement of both the contracts themselves and the processes used to create them. Organizations gain visibility into bottlenecks, commonly contested terms, and other patterns that might otherwise remain hidden.

Contract Lifecycle Automation

Agentic workflows can manage the entire contract process from request to renewal or termination. After signing, agents continue monitoring for milestone dates, obligation fulfillment, and performance metrics. This end-to-end automation ensures nothing falls through the cracks across potentially years-long contract lifecycle management processes, helping organizations maximize value and minimize risk from their agreements.

Limitations of Agentic Workflows

Despite their potential, agentic workflows aren't without challenges. The technology is still evolving, particularly in highly complex legal scenarios that require nuanced judgment. Questions remain about liability when autonomous systems make decisions, and many organizations face challenges in managing change when implementing these advanced solutions.

The most successful implementations maintain appropriate human oversight at critical decision points. Agentic AI works best as a collaborative partner with human experts rather than a complete replacement. Organizations should establish clear governance policies defining where agents can act independently and where human review remains essential.

Best Practices for Using Agentic Workflows

Organizations can maximize success with agentic workflows by following these best practices:

• Start small and targeted: Begin with well-defined, lower-risk contract processes before expanding to more complex scenarios. Early wins build confidence and provide learning opportunities.
• Define clear success metrics: Establish quantifiable goals for improvements in contract cycle time, risk reduction, or resource efficiency to measure the effectiveness of implementation.
• Invest in quality data: Agentic workflows perform best when trained on clean, well-structured historical contract data that reflects desired outcomes.
• Maintain transparency: Ensure the system can explain its reasoning and decisions in terms that business users can understand, building trust in the technology.
• Balance autonomy and oversight: Carefully determine which decisions agents can make independently versus which require human approval, adjusting these thresholds as confidence grows.

Example of Agentic Workflows in Contract Management

To understand how agentic workflows can deliver tangible business impact, consider a hypothetical example from a global manufacturing company looking to improve its procurement process. 
  
Today, supplier agreements at this company typically take 32 days from request to execution. A major contributor to this delay is the manual back-and-forth with the legal team, even for standard contract terms and routine redlines. 
  
With agentic workflows embedded in a smart CLM platform, this process can be dramatically streamlined. The procurement manager initiates the workflow directly from their sourcing system or a conversational interface—staying within their day-to-day tools. Once triggered, AI-driven agents generate a fit-for-purpose draft agreement based on the supplier’s profile, jurisdiction, and transaction details. 
  
When working with third-party contracts and clauses, contract review agents automatically evaluate them, accepting standard changes and escalating only non-standard or high-risk deviations to legal, complete with recommendations and context. This ensures legal experts are pulled in where their judgment is needed, allowing them to focus on strategic risk instead of administrative review. 
  
In some cases, the entire agreement can be completed without human intervention. For complex deals, the workflow ensures legal receives only items that require meaningful input, minimizing delays and reducing the contract lifecycle. Agentic workflows can also be auto-triggered based on events in other systems, further integrating and automating the end-to-end process. 
  
By aligning contract tasks with the right personas through intelligent automation, the business operates more efficiently. The result: reduced contract cycle times, lower legal overhead, and a procurement team empowered to execute agreements faster and with greater confidence.     

Accelerate Contract Intelligence With Icertis

As organizations use newer forms of contract management, agentic workflows are the next step in efficiency, accuracy, and value creation. Icertis Contract Intelligence leads this improvement with purpose-built AI that allows for autonomous contract processes while maintaining the governance and visibility businesses need.

Generative AI combined with Icertis' deep contract intelligence expertise helps organizations move beyond basic automation to intelligent, adaptive contract management. Schedule a demo today.

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