AI Bid Management: What's Actually Changed in 2025

• •Enhanced CPC is gone. As of March 2025, Google retired ECPC for Search and Display campaigns. Campaigns not migrated to another strategy now default to Manual CPC with no AI enhancement.
• •Microsoft followed suit. In 2024, Microsoft Advertising barred new native campaigns from using Manual CPC, auto-upgrading existing ones to eCPC.
• •New features accelerate the shift. Google Marketing Live 2025 introduced AI Max for Search and Smart Bidding Exploration. As of July 2025, you can set optional Target CPA or ROAS within Maximize Conversions campaigns.

• •Insufficient data problems. Smart Bidding needs minimum 15 conversions per week to optimize effectively.
• •Learning phase instability. New campaigns need 7-14 days for Google to learn. Performance can be erratic.
• •Goal misalignment. If your conversion tracking is wrong, AI will efficiently achieve the wrong outcome.
• •Black box frustration. You can't see exactly why the algorithm made specific decisions.
• •Over-optimization for indicated metrics. AI will find the cheapest conversions—which may not be the highest-quality leads.

• •Maximize Conversions: Use when you want volume at any cost within budget. Spends your entire budget.
• •Target CPA: Use when you have a specific cost-per-acquisition threshold. May reduce volume to hit target.
• •Maximize Conversion Value: Use when conversion values vary significantly. Requires value tracking.
• •Target ROAS: Use when you need specific return thresholds. May restrict volume significantly.
• •Maximize Clicks: Use for awareness campaigns or when you lack conversion data.
• •Target Impression Share: Use for brand defense or competitive positioning.

• •Brand defense campaigns where you want exact control over visibility
• •Very low volume accounts without sufficient conversion data
• •New campaign testing when gathering initial data
• •Highly seasonal businesses where historical patterns may mislead AI
• •Accounts with complex offline conversion cycles

1. Verify data quality. Ensure conversion tracking is accurate.
2. Set appropriate targets. Set realistic targets based on historical performance.
3. Respect the learning phase. Allow 7-14 days without significant changes.
4. Establish guardrails. Use bid limits, audience exclusions, and performance thresholds.
5. Budget for learning. Allocate 40-60% to top-performing campaigns, 20-30% to experiments.
6. Monitor systematically. Check performance weekly during stable periods, daily during learning phases.

• •Verify conversion volume. Minimum 15 conversions/week; ideally 30-50/month.
• •Check learning phase status. Don't change anything during this period.
• •Review conversion tracking. Are you measuring the right events?
• •Assess target realism. Are CPA/ROAS targets achievable based on historical data?
• •Look for external factors. Seasonality, competition, market changes.
• •Identify algorithm confusion. Erratic bidding patterns indicate problems.

• •Third-party bid management tools (Optmyzr, Acquisio, Adalysis) add layers on top of platform AI: cross-platform optimization, custom rules, enhanced reporting.
• •Fully autonomous solutions (Albert AI, PPC Samurai) handle keyword selection, bid adjustments, and creative optimization with minimal human input.
• •Agency automation platforms (Fluency, Adzooma) combine bid management with workflow automation for multi-client management.

The advertisers succeeding aren't fighting this transition—they're adapting:

• •Trusting algorithms with tactical bid decisions
• •Focusing human effort on strategy, creative, and data quality
• •Setting appropriate guardrails rather than overriding AI decisions
• •Investing in measurement infrastructure that feeds AI accurate signals
• •Monitoring for problems without micromanaging every bid