AI has impacted most areas of Marketing – including Google Ads.
Automated bidding, Performance Max campaigns, and machine-learning driven targeting can save advertisers time and uncover opportunities humans might miss. But despite the hype, AI still isn’t a replacement for human strategy, especially when it comes to campaign structure and intent. However, a skilled Google Ads specialist understands why certain search terms belong in specific campaigns.
A perfect example is with search term allocation.
Inside many Google Ads accounts, AI systems will often allocate search queries to the “wrong” campaigns. A branded search term might trigger a generic campaign instead of a brand campaign. High-intent commercial queries can end up directed into broad, automated campaign types like Performance Max, where reporting and control are limited.
From Google’s perspective, the system is optimising for its chosen objective - often conversions or conversion value. But from a business perspective, that can create major problems:
- Budget gets pulled away from priority campaigns
- Reporting becomes unreliable
- Brand traffic inflates the performance of broader campaigns
- CPCs increase unnecessarily
- Strategic testing becomes harder
This is where human expertise comes into its own.
A skilled Google Ads specialist understands why certain search terms belong in specific campaigns. Humans can apply business context, margin considerations, customer intent, and commercial priorities in ways AI simply can’t. AI sees patterns. Humans understand strategy.
For example, if a user searches for a company name, a human Marketer knows that traffic should likely be isolated in a branded campaign to protect budget efficiency and measure true incremental growth. AI may instead funnel that traffic into whichever campaign it predicts will hit conversion targets fastest.
The result is that the account may appear to perform better on paper, but actually it’s becoming less efficient and less transparent.
AI is an incredibly powerful tool for optimisation, automation, and scale. But tools still need operators. They work best when they're tested in a structured way and measured against clear objectives. Automated campaign types or AI-driven targets needs to be introduced with strong negative keyword controls, clean conversion data, and a stringent A/B testing approach.
Google Ads success doesn’t just come from letting algorithms run freely, it comes from knowing what levers to pull and when. Algorithms need guiding with human insight, oversight, and strategic direction.
