Why This Founder Built an AI Agent to Replace Google's Own Ad Recommendations

Most founders default to Meta for paid acquisition and treat Google Ads as an afterthought. Mariah Brunner argues that is a mistake. Google captures some of the highest-intent buyers in your funnel, and many accounts are quietly bleeding money without anyone noticing. Her solution: an AI agent that acts as a full-time Google media buyer, built specifically to work against the platform's own incentives.

The Problem with Google's Default Recommendations

Google's in-platform suggestions push advertisers to spend more, because Google profits when you do. Brunner makes the incentive misalignment explicit: Google wants you to increase budget, while you want to increase profit. These are not the same goal, and the default optimization targets reflect that gap.

Her agent is designed to be skeptical of those recommendations from the start. Rather than accepting Google's suggested bid adjustments or budget increases at face value, the agent evaluates them against actual performance data and profitability targets.

What the Agent Actually Does

Speaking from her living room with the Google Ads logo overlaid on screen, Brunner walks through the agent's core responsibilities. On-screen text at one point summarizes two key functions: performing comprehensive audits and analyzing product-level performance. The full scope she describes covers several layers:

• Full account audits across campaign type, monthly spend, ROAS, CPA, and impression share.
• Shopping campaign analysis broken down product by product, so underperformers do not hide inside aggregate numbers.
• Brand search monitoring to make sure branded traffic is not being neglected or overpaid for.
• Non-brand search term review, where the agent pulls every search term, identifies wasted spend, and sets up negative keywords automatically.

The last point is where most manual account management falls behind. Negative keyword hygiene is tedious, repetitive, and easy to skip. Automating it with an agent that runs regularly keeps wasted clicks from compounding.

Budget Allocation as a Core Function

Beyond auditing, the agent recommends budget allocations. This is distinct from Google's automated bidding strategies, which optimize within a campaign but do not tell you how to distribute spend across campaigns or campaign types. Brunner's agent sits above that layer, deciding where each dollar should go based on where it generates the most profit.

Key Takeaways

• Google Ads captures high-intent buyers that Meta does not reach, and ignoring it leaves money on the table.
• Google's in-platform recommendations are optimized for Google's revenue, not your profit margins.
• An AI agent can run continuous account audits across spend, ROAS, CPA, impression share, and search terms at a level of detail that manual management cannot sustain.
• Product-level shopping analysis and automated negative keyword management are two of the highest-leverage automation targets in a Google Ads account.
• Budget allocation decisions should be driven by profitability data, not by platform defaults.