Scaling Facebook Ads profitably requires more than increasing budgets. As campaigns grow, advertisers must monitor performance signals, compare creative and audience segments, make timely decisions, and avoid wasting spend when data is incomplete or conditions change. AI agents can support this process by turning campaign data into structured analysis and repeatable actions, while keeping strategic control in human hands. In this practical course, you will learn how to combine Facebook Ads operations with AI agent workflows. You will map a scalable campaign system, define reliable measurement using tools such as the Meta Pixel and Conversions API, and design agents that can review performance, identify meaningful changes, and recommend next steps. You will also explore how agents can connect with reporting tools, spreadsheets, APIs, and notification channels without giving them uncontrolled access to your advertising account. The course covers decision rules for budget scaling, creative and audience evaluation, anomaly detection, testing workflows, approval checkpoints, and safeguards that reduce the risk of automated mistakes. By the final lesson, you will have a structured blueprint for an AI-assisted scaling system that supports daily operations while preserving human oversight. This course is designed for performance marketers, media buyers, growth practitioners, founders, and developers who understand the basics of Facebook Ads and want to improve efficiency through AI agent integration. No advanced machine learning background is required. Ready to move beyond manual campaign monitoring and build a smarter, more controlled approach to scaling? Start designing your AI-assisted Facebook Ads system today.