Agentic Artificial Intelligence (AI) for Legal Practice: Designing and Implementing AI Agents
About This Course
Learn how to understand, evaluate and implement Artificial Intelligence (AI) agents in modern legal workflows. As AI capabilities evolve beyond simple prompting and rules-based automation, legal teams must identify when to apply deterministic automation, Generative AI (GenAI) tools, or more advanced agentic AI systems to improve efficiency and decision-making.
This module focuses on how agentic AI can be applied across legal practice, legal operations, in-house legal teams and public sector legal environments. Participants will learn how to identify suitable legal processes for agentic AI by assessing process complexity, variability and decision requirements. This includes how to break down legal workflows into structured agent tasks, decision points, tool interactions, and human review checkpoints.
Through a practice-oriented and implementation-focused approach, this course also introduces the orchestration logic required for agent-enabled legal work. Participants will compare manual processes, rule-based automation, GenAI-assisted workflows, and agentic systems based on business value and implementation feasibility. Participants will also develop a practical AI agent use case tailored to a legal function.
Designed for working adult learners, the module emphasises real-world relevance, structured thinking and practical decision-making, without requiring technical coding. It equips participants to make informed judgments about where agentic AI fits within legal work, how it should be designed responsibly and how legal teams can move from experimentation to useful implementation.
By the end of the course, participants will be able to articulate credible legal use cases of AI agents, design controlled-agent workflow, and evaluate deployment readiness in a way that aligns with business outcomes and the realities of legal work operations.
What You'll Learn
• Differentiate agentic Artificial Intelligence (AI) workflows from deterministic automation, basic Generative AI (GenAI) prompting, and traditional Robotic Process Automation (RPA) in a legal work context
• Identify legal work processes where agentic AI can create value, based on process variability, decision complexity and process requirements
• Break down legal operations workflow into structured AI agent tasks, decision points, tool interactions and human review checkpoints
• Understand orchestration logic for an agent-enabled legal work process, using task sequencing, approval gates and fallback rules
• Compare alternative solution approaches for example, manual, deterministic automation, Gen AI-assisted and agentic, using business value and implementation feasibility criteria
• Build out a practical agentic AI use-case for a legal function
Entry Requirements
Participant should have at least a Bachelor's Degree or a Diploma with at least 3 years working experience. They should also bring their own personal laptops where they can install their own applications without administrator restriction.