In Summary
Discover the risks of relying on AI for digital marketing strategy, and why real data, current platform knowledge and specialist experience still matter.
AI is becoming a much bigger part of how businesses review and question their marketing strategy. It’s increasingly common to use platforms like ChatGPT or Claude to audit websites, review SEO performance or ask what could be done differently with Google Ads.
There’s nothing inherently wrong with that. AI can be useful for research, generating ideas and raising questions that are worth investigating. The issue comes when its recommendations are treated as definitive, particularly when they conflict with the advice of specialists who have years of experience and work hands-on in these platforms every day.
AI can provide a very detailed explanation of what it believes is wrong and exactly what should be done about it. What isn’t always obvious, however, is whether it had the right information to make that assessment in the first place.
When an AI Audit Gets It Wrong
So, what can go wrong if AI doesn’t have access to the right information? A recent client had AI audit their website and flag that an important service page hadn’t received the same content upgrades as other service pages across the site. It was a believable finding, and potentially an important one, but the content upgrades had already been completed.
The AI was referencing a saved version of the page from around a year earlier, before the upgrades were rolled out. In other words, it had identified a problem that no longer existed because it wasn’t looking at the current website.
This is where the confidence of AI can become misleading. There was nothing obviously questionable about the recommendation itself because, based on the version of the page it could access, the finding made sense. What wasn’t clear was that the information behind it was out of date.
For a business owner or marketing manager without that context, there would be little reason to question the recommendation before acting on it.
AI Can Only Work With What It Knows
As the above example illustrates, AI can only base its recommendations on the information it has access to, and there’s no guarantee that information is complete or current. It may not have access to analytics, conversion data, account history or previous work, all of which can change how a website or campaign should be assessed.
This is particularly relevant in digital marketing, where Google, advertising platforms and website technology are constantly evolving. Advice based on older information can quickly become outdated, while gaps in the information available can also lead AI to make assumptions or generate incorrect information.
The difficulty is that these gaps aren’t always visible. Without knowing what information AI has relied on, or having the experience to critically evaluate what it produces, it’s difficult to judge how much weight a recommendation should carry.
The Question You Ask Can Change the Advice You Get
That need for scrutiny becomes even more important when you consider how easily the question itself can shape the response. AI will often accept the premise it’s given and then produce an explanation that supports it.
Take a service page as an example. You could ask AI:
“Why has the performance of this page been so poor?” – and receive a list of potential problems with the content, keyword targeting, internal links, search intent or technical elements.
“Why is this page performing so well?” – and receive an equally convincing list of reasons those same elements may be contributing to its success.
The page hasn’t changed. The premise of the question has.
If that page is actually the highest-performing service page on the website, asking why it is performing poorly has already sent the analysis in the wrong direction. AI is being asked to explain a problem before it’s been established that the problem exists.
Performance data needs to come first. A page should be considered in the context of how other pages are performing, its historical results, search demand, rankings, traffic, conversions and any changes that have already been made.
Being Able to Find an Issue Isn't the Same as Knowing What to Do
Even when AI correctly identifies an issue or opportunity, that doesn’t necessarily mean it warrants action.
A technical SEO issue may have little bearing on rankings or traffic. A service page may not follow every current SEO recommendation but still rank well and generate enquiries. A Google Ads campaign may look unusual against general best practice because it has been structured around the specific goals and performance of that account.
Deciding what to act on means considering the likely impact, other priorities and the risk of changing something that’s already working. Otherwise, businesses can spend time and money implementing changes that deliver little value while overlooking opportunities that could make a greater difference.
Why Experience Still Matters in the Age of AI
A specialist with 20+ years in SEO or Google Ads isn’t relying on what they learned two decades ago. That experience is continually evolving through hands-on work with changing platforms, algorithms and user behaviour.
Generative Engine Optimisation (GEO) is a perfect example. The rise of generative AI has introduced an entirely new layer to search marketing, requiring specialists to understand and respond to how businesses are discovered through AI search as well as traditional search engines.
That day-to-day exposure provides context AI doesn’t necessarily have. AI can be a valuable tool within the process, but it can’t replace the experience needed to properly assess its recommendations and decide what makes sense for a particular business.
Making AI Work for Your Marketing Strategy
AI isn’t the problem. Relying on its recommendations without the expertise to interrogate them is. Used alongside real performance data, current platform knowledge and specialist judgement, AI becomes another powerful tool for making better-informed marketing decisions.
At CLIQ MC, we believe the strongest approach isn’t choosing between AI and human expertise, but knowing how to use both effectively. We combine the latest technology with decades of hands-on digital marketing experience and proven results, while continually adapting to changes across search, advertising and the wider digital landscape.
Get in touch to discuss how we can help strengthen your digital marketing strategy.