What to Leave ON vs OFF in Google Ads AI Automation

If you’re running Google Ads, one of the most important decisions you’ll make is what to automate and what to control.
Google is pushing AI and automation more aggressively than ever. From bidding and targeting to ad copy and campaign structure, there are now dozens of features designed to “optimise” performance automatically.
When used correctly, automation can be incredibly powerful. It allows accounts to scale faster, test more efficiently, and uncover opportunities that would be difficult to identify manually.
However, automation is only as effective as the data and strategy behind it.
Without accurate tracking, meaningful conversion actions, and clearly defined values, Google’s AI cannot distinguish between activity and actual business outcomes. In these cases, it will still optimise but not necessarily in a way that drives profit, quality leads, or long-term growth.
That’s why knowing what to leave on, what to switch off, and what to test is critical.

What Is Google Ads AI Automation?
Google Ads AI automation refers to the machine learning systems that optimise campaigns in real time.
These systems analyse signals such as:

• User behaviour

• Search intent

• Device and location data

• Historical performance

Based on this data, Google can automatically adjust:

• Bids

• Targeting

• Ad creatives

• Budget allocation

The goal is to improve performance but without strategic input, these systems can prioritise volume over quality.

Why Automation Needs Strategy
Automation works best when it has clear direction.
If your account is feeding Google:

• Weak or incomplete conversion data

• No value differentiation between actions

• Broad or unclear targeting

Then the AI will optimise towards the wrong signals.
This can result in:

• Higher spend with lower return

• Irrelevant traffic

• Reduced lead quality

• Less control over campaign performance

Automation should enhance your strategy not replace it.

Common Google Ads AI Features (What to Review)
There are several AI-driven features within Google Ads that should be reviewed regularly.
These include:

• Auto-applied recommendations

• Broad match keyword expansion

• Optimised targeting (especially on Display campaigns)

• Automated bidding strategies

• Conversion actions included in optimisation

• AI-generated ad copy

• AI-created sitelinks, callouts, and structured snippets

Each of these can either improve performance or dilute it - depending on how they’re used.

What to Leave ON (Recommended)
Some automation features are highly effective when supported by strong data and structure.
Best to keep ON (in most cases):

• Smart bidding with proper conversion tracking and values

• Audience signals to guide targeting

• Performance Max campaigns (when structured correctly)

• Responsive Search Ads (with controlled inputs)

These features allow Google to optimise efficiently while still working within your strategic framework.

What to Switch OFF (or Use Carefully)
Other features should be approached with caution, especially if your account is still developing or lacks strong data signals.
Consider switching OFF or testing carefully:

• Select auto-applied recommendations (to maintain control)

• Broad match keyword expansion without strict monitoring

• Optimised targeting on Display (can expand too broadly)

• Automated bidding without conversion value signals

• Conversion actions that don’t reflect real outcomes

• AI-generated ad copy without review

• Automatically generated sitelinks and assets

These features often prioritise scale and reach which doesn’t always align with performance or ROI.

Best Practice: How to Manage AI in Google Ads
Instead of turning everything on or off, take a structured approach:
1. Control your inputs
Ensure:

• Conversion tracking is accurate

• Conversion values reflect business priorities

• Campaign structure is clear

2. Test before scaling
Introduce automation in controlled environments before rolling it out across the account.
3. Monitor performance closely
Review:

• Lead quality

• Cost per acquisition

• Search term relevance

4. Maintain strategic oversight
Automation should assist - not replace decision-making.

Pro Tip: AI Optimises for What You Tell It
Google’s AI is not inherently “smart” - it’s responsive.
It will optimise towards:

• The data you provide

• The signals you prioritise

• The actions you include

If those inputs are misaligned, performance will be too.

Our Approach at Air Digital
At Air Digital, we use AI as a tool - not a strategy.
Our approach is:

• Keep control over core account structure

• Test AI features in isolation before scaling

• Protect high-performing campaigns

• Use conversion values to guide optimisation

This allows us to leverage automation while still prioritising performance, profitability, and long-term growth.

Monthly Google Ads Checklist
Use this as a quick monthly review:

• Review AI features currently enabled

• Check auto-applied recommendations settings

• Audit conversion actions and values

• Monitor keyword expansion and search terms

• Review ad assets for accuracy and messaging

• Assess performance before applying automation changes

Final Thoughts
Google Ads automation is evolving rapidly, and AI is now embedded into almost every part of the platform.
Used correctly, it can significantly improve efficiency and scale.
Used without strategy, it can quickly lead to wasted spend and poor-quality traffic.
The key is not choosing between manual or automated - it’s knowing how to balance both.

Need help reviewing your Google Ads automation setup or improving performance?
Get in touch with Air Digital