AI is reshaping paid media faster than most advertisers can keep up—but the teams seeing the best results aren’t the ones handing over control to the algorithm. In this video, Casey Anderson, Paid Media Director at Two Octobers, breaks down how to work with AI in Google Ads and Meta Ads to drive better performance while keeping humans in the driver’s seat.
What’s in this Video
Learn how machine learning and AI have evolved across both platforms—and what that means for how you structure and manage campaigns today. Casey walks through four key levers for AI-driven ad performance: audience and signal inputs, creative inputs, bidding and goal settings, and campaign structure. She also covers the most common mistakes advertisers make when working with AI, from over-segmenting campaigns to skipping the learning period, and how to avoid them.
Key Takeaways
- The evolution of AI in Google Ads and Meta Ads, from manual bidding to the AI-first era
- How to use first-party data and audience signals to help platforms find the right customers
- Creative inputs you can control—and when to let AI generate assets
- Why consolidated campaign structures outperform fragmented ones
- Common mistakes that undermine AI performance and how to fix them
- How to audit your campaigns regularly to stay in control of what AI is doing
Whether you’re running Performance Max, Meta Advantage+, or smart bidding strategies, this video gives you a practical framework for feeding the machine well—and getting better results because of it.
