AI tools can speed up and scale Meta ad campaigns, but over-reliance can create costly problems. The two most common issues are inaccurate targeting and automated ad disapprovals. Knowing these risks and how to manage them ensures better results.

Targeting Risks

Meta's AI systems like Advantage+ Audience and Lookalike targeting analyze huge datasets to find potential customers. However, if you leave targeting entirely to AI, it may favor volume over quality. This can result in high impressions and clicks but very few conversions or sales.

To reduce this risk, always combine AI with your own targeting filters.

• Start with interests, past actions, or warm audiences (like website visitors);
• Track conversion rate and ROAS to measure lead quality;
• If reach is high but conversions are low, narrow targeting or build custom audiences based on your best customers.

Automated Disapprovals

Meta's AI scans ads for policy violations in text, visuals, and landing pages. While necessary, it often misinterprets messages — especially in sensitive niches like health, finance, or self-help. For example, a harmless line such as "feel confident again" could be flagged as making personal assumptions.

Ways to reduce disapprovals:

• Review Meta's ad policies and follow Creative Guidelines;
• Avoid implying personal traits or emotional states (e.g., "tired of being broke?");
• Test new ads with small budgets first to minimize risk;
• If wrongly flagged, request a manual review — human reviewers often overturn errors.

Too many disapprovals hurt your account quality score, which limits campaign reach and effectiveness. The best approach is to use AI for automation but stay actively involved in strategy, creative review, and audience analysis.