The AI Operating Model: How to Run Marketing When Agents Do the Execution

Looking forward to this session? Share it!

As AI agents take on more marketing execution, teams need to rethink how they organize and oversee the work. Who defines the objective? How does a brief become an actionable workflow? Which decisions can an agent make, and when does a person need to review, approve, or intervene?

This case study explores an operating model for marketing with AI agents, following work from initial direction through execution and review. It examines how responsibilities, team routines, and accountability change as agents become part of everyday workflows. Attendees will learn how to keep human judgment connected to execution and establish clear ownership as they move from individual experiments to repeatable operations.

Key takeaways

• Translate marketing objectives into clear briefs and boundaries for AI agents.
• Define responsibilities across business owners, agents, and human reviewers.
• Identify where approval, escalation, and intervention belong in a workflow.
• Adapt team routines to review agent activity and maintain accountability.
• Build a repeatable operating model that connects AI execution to business outcomes.