Understanding Agentic Workflows & AI Agents
Introduction: Legal tech revolution
The legal industry is undergoing a transformation, driven by the rise of artificial intelligence. At the heart of this shift are two powerful concepts: AI agents and agentic workflows. They are already reshaping how legal teams operate, making processes faster, more accurate, and more scalable.
In this post, I will break down what these terms mean, how they differ, and most importantly—how they’re being used in real-world legal tech applications.
AI Agents: Autonomous legal assistants
An AI agent is a software entity that can perceive its environment, make decisions, and take actions to achieve specific goals. In legal tech, this means agents can perform tasks like reviewing contracts, tracking legal spend, or analyzing case law—all without constant human oversight.
Example:
An AI agent monitors your or your firm’s expense by automatically reviewing invoices, cross-referencing billed hours, and flagging discrepancies. It operates independently, learning from past interactions to improve accuracy over time. This frees up your time to focus on strategic decisions and servicing clients.
Agentic Workflows: Orchestrating legal automation
While AI agents excel at individual tasks, agentic workflows take things to the next level. These are multi-step processes where multiple AI agents collaborate under a coordinated system. Think of it as an assembly line: each agent handles a specific task, but the workflow manages the overall process, ensuring consistency, efficiency, and accountability.
Agentic workflows are especially valuable for complex, data-intensive legal processes. Here are three practical examples:
Contract Lifecycle Management Workflow
From intake to execution, every step is automated and optimized:
Intake Agent: Receives contract requests and extracts key requirements.
Template Agent: Selects the appropriate contract template based on deal type.
Drafting Agent: Generates an initial contract with custom terms.
Review Agent: Identifies potential risks and compliance issues.
Negotiation Agent: Suggests redlines and alternative language.
Approval Agent: Routes the contract to the right stakeholders based on risk assessment.
Execution Agent: Manages the signature process and final filing.
This workflow ensures contracts are handled efficiently, with minimal manual intervention and maximum consistency.
Litigation Discovery Workflow
Litigation discovery is notoriously time-consuming, but agentic workflows make it manageable:
Collection Agent: Identifies and preserves relevant documents across multiple systems.
Processing Agent: Handles data extraction, deduplication, and formatting.
Analysis Agent: Categorizes documents by relevance, privilege, and responsiveness.
Review Agent: Flags key documents for attorney review and provides explanations.
Production Agent: Formats and redacts documents according to court requirements.
Quality Control Agent: Validates the output before submission.
This approach allows lawyers to process massive document sets with greater accuracy and less risk of missing critical evidence.
Due Diligence Workflow
Due diligence often involves sifting through mountains of information. Agentic workflows make this process scalable and consistent:
Scoping Agent: Analyzes the transaction type to determine review requirements.
Data Room Agent: Organizes and indexes incoming documents.
Specialized Review Agents: Multiple agents focus on different areas (IP, employment, environmental, financial).
Risk Assessment Agent: Consolidates findings and scores risk levels.
Report Generation Agent: Creates executive summaries and detailed findings.
Tracking Agent: Monitors outstanding items and manages follow-up requests.
This ensures that every aspect of due diligence is covered, with no stone left unturned.
Why This Matters for Legal Teams
The power of agentic workflows in legal tech lies in their ability to handle the inherent complexity of legal processes while maintaining consistency, reducing errors, and scaling expertise across large volumes of work. Each agent contributes specialized knowledge, while the workflow ensures nothing falls through the cracks.
By offloading routine tasks to AI agents and agentic workflows, legal professionals can focus on higher-value work and problem-solving. This hybrid model—combining human judgment with AI efficiency—is the future of legal practice.
Conclusion
AI isn’t replacing lawyers—it’s making them more effective. The best legal teams will combine the efficiency of agentic workflows and AI agents with the judgment and creativity of human professionals. This collaborative approach will be faster, more accurate, and more client-focused than ever before.
Agentic workflows and AI agents are transforming legal tech. Understanding and adopting these tools will help you stay ahead in an increasingly competitive and innovation-driven industry. The future is here—and it’s powered by intelligent collaboration.
Well articulated, Renu. A lot of admin and clerical jobs would be replaced. And Evan of agents until they are proven will be a huge area where jobs will pick up. What other job opportunities does this entail?