In Part 1, we looked at why AI Max matters and what it tells us about the future of Search advertising. We explored how Google is moving further towards intent-led automation, and why marketing managers need to understand the direction of travel rather than seeing AI Max as just another setting inside Google Ads.
But once you've got past the headlines and the hype, there's a more practical question to answer that businesses really want to know the answer to.
How do you actually get the best out of it?
In fact, one of the biggest misconceptions around AI-powered advertising is that it somehow makes the fundamentals less important. If anything, the opposite is true.
AI Max doesn't really change what good marketing looks like, it simply puts more pressure on the things that already matter. Accurate tracking, reliable data, clear website content and well-structured campaigns all give Google's systems better information to work with.
Get those things right and AI Max has a much stronger base to build from. Get them wrong and the platform may still optimise, but it could be optimising around the wrong signals. That's why a good AI Max implementation strategy shouldn't start with AI Max itself. It should start with everything the AI is going to rely on.
Start With Your Conversion Tracking
If there's one thing we'd recommend checking before introducing AI Max, it's your conversion tracking. That might not be the most exciting place to start, but it's easily one of the most important.
Google's AI relies heavily on the signals it receives, which means the quality of your data directly influences the decisions the platform makes. Better signals lead to better optimisation. The challenge is that many businesses assume their tracking is working perfectly when, in reality, there are often gaps hiding beneath the surface.
We've audited plenty of accounts where everything looked healthy at first glance, only to find duplicate conversions inflating performance figures, key actions missing entirely, or valuable offline sales never making their way back into Google Ads. Nothing looked obviously wrong, but the data feeding the platform wasn't as accurate as initially thought. And that's a problem when you're asking AI to make decisions on your behalf.
Before enabling AI Max, it's worth taking a step back and asking a few simple questions:
- Are all meaningful conversions being tracked?
- Are qualified leads being measured separately from lower-quality enquiries?
- Are offline sales or CRM outcomes being imported where possible?
- Are you optimising towards the metrics that genuinely matter to the business?
Because AI Max can only work with the information it's given. If the data is accurate and reliable, Google's systems have a much better chance of identifying valuable opportunities. If the data is incomplete or misleading, the platform may simply become very efficient at optimising towards the wrong objective.
Your Website Has Become Part of the Campaign
Historically, most conversations around Google Ads focused on keywords, bidding strategies and ad copy. The website was important, of course, but it often felt like a separate conversation. AI Max is changing that.
Google's systems are becoming increasingly reliant on website content to understand what a business does, who it's relevant to and when its ads should appear. In many ways, your website is no longer just the place users land after clicking an advert. It's helping Google understand your business in the first place.
That means the quality of your website matters in ways it perhaps didn't before. If your service pages clearly explain what you offer, who it's for and the problems it solves, Google's AI has a much stronger foundation to work from. If that information is buried across old pages, inconsistent messaging or outdated content, understanding your business becomes a much harder job.
We've all landed on websites where it's difficult to work out exactly what a company does within the first few seconds. If a visitor struggles to make sense of it, there's a good chance Google's systems will have a harder time too. That's why website content is becoming a bigger part of paid media performance.
The strongest AI Max implementations are unlikely to come from businesses that simply switch on a new feature. They're more likely to come from businesses whose websites clearly communicate their expertise, services and value proposition.
What’s interesting is that this brings paid media and website optimisation closer together than ever before, they're no longer separate conversations. The quality of your website increasingly influences the quality of your advertising performance, which means both need to work together if AI Max is going to reach its full potential.
Look at the Campaigns You Already Have
One misconception around automation is that it can fix an underperforming account, unfortunately, it doesn't really work like that.
AI Max is much better thought of as an amplifier than a rescue plan. If your campaigns already have reliable conversion data, sensible account structures and a clear history of performance, Google's systems have something useful to build on. If those foundations are missing, the AI has far less context to work with.
That doesn't mean every account needs to be perfect before AI Max is tested. Very few accounts are.
What it does mean is that you should understand how your campaigns are performing today before introducing another layer of automation.
After all, if you don't know what's already working, it becomes much harder to judge whether AI Max is genuinely improving performance or simply changing where budget is being spent.
Before testing AI Max, it's worth reviewing a few key areas:
- Which campaigns are consistently driving valuable results?
- Where is budget currently being spent?
- Which keywords are already performing well?
- Are audience signals helping improve performance or adding noise?
- Does the account have enough conversion history for Google's systems to learn from?
The clearer your starting point, the easier it becomes to measure the impact of any changes you make.
Because ultimately, the goal isn't to switch on AI Max. The goal is to improve performance. Understanding the health of your existing campaigns makes it much easier to tell the difference.
Decide What Success Actually Looks Like
One of the easiest mistakes to make when testing AI Max is focusing too heavily on conversion volume. After all, more conversions sound good. They're easy to report, easy to compare and easy to get excited about. But more conversions don't always mean better business outcomes.
We've all seen examples where lead numbers increase, only for sales teams to report that lead quality has fallen. The campaign looks healthier inside Google Ads, but the commercial results tell a different story. That's why it's important to decide what success looks like before making any significant changes.
For some businesses, that might be lower acquisition costs. For others, it could be higher-quality leads, stronger revenue performance or an improvement in return on investment. The right answer depends on the business, but it shouldn't start and end with conversion volume alone.
Before testing AI Max, it's worth establishing clear benchmarks around metrics such as:
- Cost per lead
- Conversion rate
- Customer acquisition cost
- Lead quality
- Revenue generated
- Return on investment
AI Max may well uncover new opportunities and increase campaign activity, but those opportunities still need to make commercial sense. A campaign that looks stronger inside Google Ads is only truly stronger if it's helping the business achieve better outcomes outside of it.
Keep Brand Consistency in the Conversation
One area that often gets overlooked when discussing AI Max is brand control.
AI-generated assets can be incredibly useful, helping improve relevance, increase coverage and reduce some of the manual work involved in campaign management. However, they still need oversight, particularly for businesses that have invested significant time in developing a clear position in the market.
While Google's systems are designed to improve performance, they don't always understand a brand in the same way the people behind it do. A headline might attract clicks and a description might improve engagement, but if the messaging feels out of character or doesn't accurately reflect the business, it can create problems further down the customer journey.
That's why reviewing AI-generated content should remain part of the process. Marketing managers should continue checking that generated assets align with brand guidelines, tone of voice and customer expectations, rather than assuming strong performance metrics tell the whole story.
The most effective use of AI Max isn't to hand over complete control, but to combine automation with human judgement. Google's introduction of features such as Text Guidelines and URL Exclusions gives advertisers greater influence over how AI-generated assets align with their brand, helping prevent messaging that feels off-brand or directs users towards unsuitable content. Used thoughtfully, these controls allow businesses to benefit from AI-driven efficiency while maintaining a consistent customer experience.
Measure the Quality of the Leads, Not Just the Quantity
This is probably one of the most important considerations when testing AI Max.
Automated campaign expansion can create more opportunities, but not all opportunities carry the same value. A lead that becomes a profitable customer is worth far more than a lead that never moves beyond an initial enquiry.
That sounds obvious, but it can be surprisingly easy to lose sight of when campaign reports start showing more conversions.
If lead volume increases after AI Max is introduced, the next question shouldn't simply be "How many leads did we generate?" It should be "Were they the right leads?"
Are they better qualified? Are they progressing through the sales process? Are they turning into customers? Is revenue growing alongside enquiry volume?
These are the questions that ultimately determine whether a campaign is becoming more effective or simply becoming busier.
That's why close collaboration between marketing and sales is so important when testing AI Max. Platform metrics can tell you what happened inside Google Ads, but they can't always tell you whether those results translated into meaningful commercial outcomes.
Lead quality should be part of the conversation from the very beginning, not something reviewed months later once performance has already shifted.
Because while AI Max may help uncover new opportunities, success isn't measured by how many leads it generates. It's measured by how much value those leads create for the business.
To Wrap It All Up
After all the discussion around AI Max, it's worth remembering that it is still just a tool, a potentially powerful one, but a tool nonetheless.
The things that make campaigns successful haven't suddenly changed, good tracking still matters, clear messaging still matters, website quality still matters, strong account structure still matters, and understanding your customers still matters. If anything, those things have become even more important.
In many ways, AI Max shines a brighter light on what is already there. Strong foundations give Google's systems something valuable to build on, while weak foundations become much harder to hide. That's why a successful AI Max implementation doesn't really start with AI Max itself. It starts with making sure the fundamentals are in place.
Get those foundations right and automation has a much better chance of uncovering new opportunities, reaching new audiences and improving performance.
June 25, 2026
