Google’s pitch for AI-powered bidding is seductive. Feed the algorithm your conversion data, set a target, and let it optimize your campaigns while you focus on strategy. Machine learning will handle the rest. What Google doesn’t emphasize is that its algorithms optimize for Google’s goals, not necessarily yours. In 2026, as Smart Bidding becomes more opaque and Performance Max absorbs more campaign types, knowing when to guide the algorithm – and when to override it – has become a defining skill that separates average PPC managers from exceptional ones. AI bidding can deliver spectacular results, but it can also quietly destroy profitable campaigns by chasing volume at the expense of efficiency. The difference is not the technology. It is knowing when the algorithm needs direction, tighter constraints, or a full override. This article explains: How AI bidding actually works. The warning signs that it is failing. The strategic intervention points where human judgment still outperforms machine learning. How AI bidding actually works – and what Google doesn’t tell you Smart Bidding comes in several strategies, including: Target CPA. Target ROAS. Maximize Conversions. Maximize Conversion Value. Each uses machine learning to predict the likelihood of a conversion and adjust bids in real time based on contextual signals. The algorithm analyzes hundreds of signals at auction time, such as: Device type. Location. Time of day. Browser. Operating system. Audience membership. Remarketing lists. Past site interactions. Search query. It compares these signals with historical conversion data to calculate an optimal bid for each…