Algorithmic optimization excels for e-commerce and product-driven campaigns where clear conversion signals exist. When a platform has enough conversion data, enough volume, and a clear commercial outcome to optimize toward, automation can do a very good job.
The problems start with softer campaign objectives.
When AI Targeting Goes Wrong
A traffic campaign can drive cheap clicks without driving useful visitors. A lead campaign can produce a low CPA while bringing in weak or irrelevant leads. The platform optimizes for what it can measure — not for what actually matters to your business.
For awareness, traffic, and lead generation campaigns, this gap between measured metric and actual business value is where budgets quietly drain away.
The Placement Problem
Broader automated targeting can inadvertently direct budgets toward bot traffic, click farms, and made-for-advertising sites. The metrics look fine. CTR is up, CPA is down. But the underlying placements are garbage.
Platform-reported metrics don't reveal what websites your ads ran on, or whether those sites had any real users reading real content. You need to check the placement report yourself.
What to Do About It
For product sales with strong conversion tracking, embrace automation. The signal is clean and the platform has enough data to work with.
For awareness and traffic campaigns, add controls:
- Pull your placement report regularly
- Audit for MFA sites, bot-heavy domains, and brand-unsafe environments
- Build exclusion lists and apply them account-wide
Google's January 2026 account-level exclusion rollout makes this more practical than it used to be. One exclusion list now applies across all campaigns automatically.
The point isn't to fight AI targeting. The point is to give it better inputs. Clean placement lists are one of the highest-leverage things you can do to improve automated campaign performance.