WELLBEING / ACCOUNTABILITY / LEADERSHIP / PERFORMANCE

How do you maintain control, accountability, and governance as AI becomes more autonomous?

This 90-minute webinar introduces the Model Context Protocol (MCP) as a practical framework for structuring and governing legal AI systems. Rather than focusing on hype or theoretical AI governance, this session explores how MCP-style architectures help firms control how AI agents interact with data, tools, workflows, and people—and why this matters for risk, compliance, and operational trust.

Drawing on real-world experimentation and emerging best practices, Morgan Llewellyn will break down how firms and legal teams are beginning to operationalize agent frameworks, what’s working, what’s failing, and how to apply these concepts pragmatically within existing legal environments.

Participants will leave with a clearer mental model for agent-based AI, a shared language to engage internal stakeholders, and concrete ideas for piloting AI safely and responsibly inside their organizations.

By the end of this session, attendees will:

• Understand how agent-based AI is changing the legal tech landscape
• Gain a practical framework for controlling AI systems using MCP concepts
• Be able to ask better questions of vendors, technologists, and internal teams
• Identify realistic next steps for piloting and governing legal AI responsibly

Key Themes & Discussions

From Tools to Agents: The Next Phase of Legal AI

Why agent-based systems represent a step change, How agents differ from traditional AI tools and copilots, and where firms are already encountering agents.

Understanding MCP (Model Context Protocol)

What MCP is, and what it is not, how it structures AI access to data, tools, and actions, and why context control is foundational to trust, safety, and reliability.

Designing Control, Not Just Capability

Guardrails vs. governance: where most firms go wrong. Controlling inputs, permissions, and outputs across AI workflows. Preventing hallucination, data leakage, and unintended autonomy.

Practical Architectures for Law Firms

Examples of MCP-style architectures in legal settings. Integrating agents with document systems, KM, matter data, and workflows. Aligning AI design with legal risk, ethics, and compliance requirements.

What’s Working (and What Isn’t)

Lessons from early adopters experimenting with agent frameworks. Common failure points and unrealistic assumptions. How to avoid over-engineering while maintaining control.

From Experiment to Operation

Where to pilot agent-based AI safely. How to involve IT, KM, risk, and practice leadership. Building internal confidence and shared understanding

Who Should Attend

This webinar is designed for legal professionals responsible for AI strategy, governance, and implementation, including:

• CIOs, CTOs, and Heads of IT
• Innovation, AI, and Legal Tech leaders
• Knowledge Management and Information Governance professionals
• Risk, Compliance, and Data Protection leaders
• Practice leaders and partners overseeing AI adoption
• In-house legal operations teams exploring advanced AI use cases

Our Speaker