Google Ads and Meta have spent years building AI into their bidding and optimization algorithms, to the point that much of the tactical work a media buyer used to do manually is now done by the platform alone, generally better.
What’s already better left to the algorithm
Automated bidding (Target CPA, Target ROAS, Maximize Conversions) consistently beats manual bidding once there’s enough conversion data volume. Fighting the algorithm by manually adjusting bids every day tends to produce worse results than trusting the automation and focusing human effort elsewhere.
What still needs human judgment
- Audience strategy and account structure: what to segment, how to organize campaigns, what signals to feed the algorithm.
- Creative: the message, the angle, the value proposition. No AI yet knows what real problem matters most to your ideal customer without being told.
- Business judgment: understanding whether a campaign that “performs” according to the platform is actually bringing profitable customers, or just generating cheap, low-quality leads.
The risk of automating without good input data
An ad platform’s AI is only as good as the conversion data it receives. If tracking is misconfigured or measures low-quality events (leads that never buy, for example), the automation aggressively optimizes toward the wrong target.
Where generative AI adds value today
Generating copy and creative variants to test faster, summarizing insights from long reports, and detecting anomalies in campaign performance are concrete uses where generative AI already adds real value, without replacing the final decision of what to test and why.
The practical conclusion
The highest-value work in paid media today isn’t manually adjusting bids, it’s making sure the data feeding the algorithm is correct, and spending human time on strategy and creative.
If you want to review which parts of your ad account are worth automating and which aren’t, message me on WhatsApp.