How Law Firms Should Embrace Agentic AI for Multi-Step Legal Task Automation
AI agents are changing how legal tasks get done by handling multiple steps autonomously. In early 2025, major AI companies introduced new agentic workflows, highlighting this shift. For example, Harvey launched agentic workflows in March, and Thomson Reuters updated CoCounsel in June with agentic AI capabilities for tax and accounting workflows.
But what exactly is an AI agent, and how could it affect legal work? Think of AI development like building with LEGO blocks. Basic components combine to create more complex tools. At its core, an AI agent is software layered on top of a large language model (LLM) that processes input and generates output. Chatbots like ChatGPT, MS Copilot, Harvey, and CoCounsel are examples of such agents.
From Basic AI Agents to Agentic Workflows and Autonomous Agents
A simple AI agent might answer a single question or complete a single task. Agentic workflows go further—they execute a chain of tasks after one trigger. The goal is to create autonomous agents that operate independently and continuously produce results. ChatGPT and Claude have started offering tools that claim to do this, but real-world testing shows they still need improvement before being reliable for legal work.
Consider translating a contract from English to French to understand these differences:
- Basic AI agent: You input the text and request a translation (like ChatGPT).
- Agentic workflow: The system guides you through steps—uploading the contract, detecting the language, translating, formatting the document, and preparing it for download.
- Autonomous agent: A continuous translation assistant running in real time, possibly on your mobile device, translating spoken language as you interact in another country.
Truly autonomous agents for legal work come with risks. They must maintain confidentiality and allow for lawyer review, which is critical in legal practice.
Why Legal Firms Should Invest in AI Agents Now
Legal AI solutions are becoming essential investments. Data from DeepJudge, a company that builds AI agents for law firms, shows their platform can deliver four times the return on investment within a year. Users save over 65 hours annually previously spent on information search alone.
Two Approaches to Building AI Agents in Legal Practice
Legal AI tools for agents fall into two categories:
- Pre-built AI workflows inside existing chatbots: These use proprietary software, legal databases, and integrations. Firms starting with AI agents should explore this first. For example, Harvey offers 30+ workflows covering tasks like drafting documents, extracting event timelines, and summarizing changes.
- Custom workflow platforms: These let firms design their own AI workflows using internal data and documents, selecting preferred LLMs and defining specific tasks. DeepJudge and Aria are major players here. Some firms connect these platforms to case management tools (like Clio) to create dynamic dashboards that track case status.
Platforms that allow quick building and iteration of customized AI tools provide a practical way for law firms to optimize their operations.
The Current Market: Early Adopters and Those Just Starting
Law firms today fall into two groups: those just beginning with AI and those actively using multi-step agentic workflows. Building these workflows can free lawyers from routine tasks and open new ways to approach legal practice.
For legal professionals interested in exploring AI tools and automation further, courses and resources are available to gain practical skills and stay updated on AI developments. Check out Complete AI Training’s legal-focused AI courses for hands-on learning.
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