Google Ads Advisor Review: Can Google’s AI Really Optimise Your Campaigns?
Google has quietly introduced a new beta feature inside Google Ads called Ads Advisor — an AI-powered assistant built with Gemini that aims to help advertisers optimise campaigns, troubleshoot issues, and improve performance.
At first glance, it looks like Google is taking a major step towards an AI-driven future where advertisers can simply “talk” to Google Ads instead of relying on agencies or campaign managers.
But does it actually work?
After putting the system through a real-world test inside a live Google Ads account, the results were surprisingly mixed. Some suggestions were genuinely useful. Others felt more like Google trying to encourage advertisers to spend more money.
In this article, we’ll break down:
- What Google Ads Advisor is
- How it works
- The good and bad parts of the system
- Whether it can genuinely improve campaign performance
- Why advertisers still need to think critically before accepting its recommendations
What Is Google Ads Advisor?
Google describes Ads Advisor as:
“An agentic conversational experience built with Gemini in Google Ads.”
According to Google, the tool is designed to:
- Provide personalised answers to advertising questions
- Help diagnose performance problems
- Troubleshoot policy or tracking issues
- Suggest campaign optimisations
- Generate ad copy and creative suggestions
Essentially, Google wants Ads Advisor to function like an AI campaign consultant built directly into the Google Ads interface.
The long-term vision appears to go far beyond campaign suggestions.
At Google Marketing Live, Google demonstrated a future where AI agents could:
- Detect conversion tracking issues
- Install Google Tags automatically
- Access website builders like Wix
- Fix tracking implementation problems
- Optimise campaigns autonomously
In theory, this could reduce the need for traditional Google Ads managers altogether.
But the important question is:
Is the technology actually ready for that?
Testing Ads Advisor in a Real Account
The Ads Advisor was tested inside a small Google Ads account for an interior design business.
This was not a massive enterprise account. It was a modest business with:
- One employee
- Limited scalability requirements
- Existing lead flow
- A focus on efficiency rather than aggressive growth
The campaign had also recently shifted from:
- Target CPA bidding
to - Maximise Conversions
This change had been made due to market seasonality and reduced demand earlier in the year.
That context matters — because it quickly exposed one of the biggest weaknesses in Ads Advisor.
The First Problem: Google Wants You to Spend More
When the AI analysed the account, its first recommendations focused heavily on:
- Increasing impression share
- Improving visibility
- Relaxing bidding restrictions
- Increasing budget
- Improving ad rank
In other words:
Spend more money.
The system highlighted that the account was losing impressions due to ad rank and budget limitations.
Technically, this wasn’t incorrect.
But the issue was context.
This particular advertiser did not want to scale aggressively. The business already had enough leads and intentionally maintained a modest advertising budget.
Yet Ads Advisor interpreted lower impression share as a “problem” that needed solving.
This reflects a major concern with Google’s AI systems:
They often assume growth is always the objective.
For many businesses, that simply isn’t true.
Some advertisers want:
- Better lead quality
- Lower cost per conversion
- Stable performance
- Controlled spend
- Profitability over scale
An AI system that doesn’t understand business intent can easily push advertisers towards decisions that increase spend without improving outcomes.
The Ad Strength Issue
Another recommendation focused on improving “Ad Strength”.
Ads Advisor suggested that poor Ad Strength scores were harming ad rank and overall campaign performance.
This is where things become more questionable.
Ad Strength is not a direct bidding signal
Google heavily promotes Ad Strength, but many experienced advertisers know:
- A higher Ad Strength score does not guarantee better performance
- More ad variations do not automatically improve conversions
- Over-optimising for Ad Strength can sometimes hurt click-through rate and lead quality
In practice, advertisers often see:
- Excellent Ad Strength
- Worse real-world results
The AI appeared to treat Ad Strength as a major optimisation priority, which could mislead less experienced advertisers.
Where Ads Advisor Started to Improve
The real turning point came when a more specific question was asked:
“I am not looking for more traffic. I am looking for cheaper conversions. What should I do?”
This changed the quality of the recommendations significantly.
Instead of pushing for more spend, the AI began focusing on efficiency.
And some of the suggestions were genuinely good.
Good Suggestion #1: Eliminating Wasteful Search Terms
One recommendation identified broad search terms that had spent money without generating leads.
Examples included:
- “Interior designer”
- “Interior designer London”
Meanwhile, more specific searches were converting efficiently.
The AI suggested:
- Pausing wasteful broad terms
- Moving them into exact match
- Prioritising high-intent queries
This is a perfectly reasonable optimisation strategy.
In fact, it mirrors what many experienced PPC managers would do when trying to reduce wasted spend.
Good Suggestion #2: Reintroducing Target CPA
The AI also recognised that the campaign was running on:
- Maximise Conversions
without - A Target CPA limit
It suggested introducing a Target CPA again to reduce expensive leads.
This was actually a strong recommendation.
The account had previously moved away from Target CPA due to market conditions, but performance had stabilised enough that reintroducing a target could make sense again.
The AI identified this correctly.
That’s impressive.
Good Suggestion #3: Geographic Efficiency Analysis
Another useful insight involved location-based performance.
The system identified specific London boroughs producing lower CPAs than others and suggested focusing spend there.
Again, this is a legitimate optimisation tactic.
For local campaigns, geographic segmentation can dramatically improve efficiency when handled correctly.
The Biggest Weakness: Lack of Business Context
Despite some strong recommendations, the overall system still has a major flaw:
It lacks strategic understanding.
The AI doesn’t truly understand:
- Business goals
- Profit margins
- Lead quality
- Operational capacity
- Scaling limitations
- Commercial realities
Instead, it largely interprets account data through the lens of Google’s incentives.
And Google’s incentives are obvious:
- More spend
- More automation
- More adoption of Google features
That doesn’t necessarily align with the advertiser’s objectives.
Why Experienced Advertisers Still Have an Advantage
This is where human experience still matters enormously.
An experienced Google Ads manager can:
- Identify bad recommendations
- Understand nuance
- Apply commercial logic
- Balance efficiency with growth
- Ignore irrelevant automation suggestions
Most advertisers cannot.
And that creates risk.
Because many businesses may assume:
“The AI suggested it, so it must be correct.”
That assumption could become expensive very quickly.
Final Verdict: Is Google Ads Advisor Any Good?
Surprisingly, yes — to a degree.
The system performed much better than expected when given clear instructions around efficiency and cost reduction.
Some recommendations were genuinely useful and aligned with real PPC optimisation strategies.
However, the default behaviour still strongly favours:
- Increased spend
- Broader targeting
- Greater automation
- Higher visibility
That should not surprise anyone.
Google ultimately benefits when advertisers spend more money.
Overall Score: 6.5/10
Ads Advisor is not a failed product.
In fact, it’s a significant improvement over Google’s previous AI assistance systems.
But it is not yet sophisticated enough to replace experienced Google Ads management.
At its best, it can:
- Surface useful optimisation ideas
- Highlight inefficiencies
- Assist with troubleshooting
- Speed up analysis
At its worst, it can encourage advertisers to:
- Overspend
- Over-automate
- Relax efficiency controls unnecessarily
How Advertisers Should Use Ads Advisor
If you decide to use Google Ads Advisor, approach it carefully.
Best practices include:
1. Ignore Default “Spend More” Recommendations
Many initial suggestions will focus on growth and visibility.
That does not mean they are correct for your business.
2. Ask Specific Questions
The quality of responses improves significantly when you ask targeted questions such as:
- “How can I reduce CPA?”
- “Which keywords are wasting spend?”
- “Where am I losing efficiency?”
- “Which locations perform best?”
3. Validate Recommendations Manually
Never assume the AI is correct automatically.
Check:
- Search term reports
- Conversion quality
- Historical performance
- Commercial viability
4. Use It as an Assistant — Not a Decision Maker
Right now, Ads Advisor works best as:
- A secondary analysis tool
- A source of ideas
- A starting point for optimisation
Not as a fully autonomous campaign manager.
Final Thoughts
Google’s Ads Advisor represents an important glimpse into the future of PPC management.
AI-driven optimisation is clearly becoming central to Google Ads.
And while this beta product still has major limitations, it also shows genuine promise.
The key takeaway is simple:
AI can assist with optimisation, but experience is still essential.
The advertisers who succeed with systems like Ads Advisor will be the ones who know:
- Which suggestions to follow
- Which suggestions to ignore
- And how to align AI recommendations with actual business goals
That human judgement still matters — and probably will for quite some time.
