Over the last year, as AI tools have become more integrated into the everyday lives of marketing teams, and increasingly other teams within businesses, there has been a noticeable shift towards publishing more website content.
AI has removed much of the friction from writing. Marketing teams can now produce blog posts, landing pages and long form content far quicker than before, and often at a lower cost. Naturally, that has led to a simple internal question in many businesses; If we can produce more, shouldn’t we?
It feels logical; More content means more topics covered, more topics mean more potential keywords, and more keywords should mean more visibility.
That said, as an agency that reviews search performance across competitive industries on a daily basis, particularly in B2B and service markets, we’ve noticed that this logic does not always hold up.
The ability to produce more content hasn’t automatically made it easier to rank, since while AI becomes more capable of generating content, it’s also become more capable of evaluating it.
Why Many Teams Believe More Content Improves SEO Visibility
The assumption driving much of this behaviour is understandable. If AI allows a marketing team to publish twice as much content, it seems reasonable to expect increased search visibility. Cover more questions, address more problems, rank for more queries.
In theory, publishing more relevant content can increase your surface area in search. The issue, however, is that everyone now has access to the same production advantage.
The constraint that once limited output has largely disappeared. That means volume alone isn’t a competitive edge in the way it once may have been.
The more useful question is not how much can we publish, but why would search systems choose our version over the alternatives. That is where AI and SEO strategy have to become more deliberate.
How AI Has Changed the Way Search Engines Evaluate Content
No agency can claim to know exactly how every algorithm works, which is why I’m not about to pretend we do. However, what we can observe is that search systems are significantly better at evaluating substance.
They can assess whether content genuinely explores a topic or simply references it. They can identify thin coverage. They can detect when an article repeats common knowledge without adding meaningful insight.
Just a few years ago, comprehensive structure, strong on page optimisation and solid link building could often carry a page. Today, two companies can write about the same subject and see very different outcomes. That difference most often comes down to clarity, specificity and demonstrated understanding.
This is closely linked to what Google refers to as Experience, Expertise, Authoritativeness and Trust. E-E-A-T is not a single ranking factor, but it reflects how search systems attempt to evaluate credibility. When content clearly demonstrates real experience, practical insight and domain knowledge, it becomes easier for search systems to interpret it as authoritative.
As has always been the case, that evaluation doesn’t stop at the content published on your website.
Search visibility is increasingly influenced by off-site context as well. How your brand is mentioned across the web, the language used in reviews, industry commentary, partnerships and third-party content all contribute to how clearly your expertise is understood. A business that is consistently described in a specific way, and associated with a clear audience or specialism, gives search systems stronger signals to work with.
Why Clear Positioning Trumps Content Volume in SEO
AI assisted discovery allows users to provide more context about themselves and their needs than a traditional search box ever did. They describe company size, industry, objectives and constraints. Search systems then attempt to match them with the most appropriate solutions.
If your positioning is vague, you become harder to match.
Consider a software business designed specifically for enterprise sales teams of 100 seats and above. If that positioning is not clearly reflected across the website, and if the content does not consistently address enterprise level challenges, then there is little to distinguish it from more general competitors.
However, if the same company consistently discusses enterprise rollout complexity, procurement processes, integration challenges and internal stakeholder friction, then it becomes far easier for search systems to understand when it is the right fit.
This is not about stating your positioning once. It’s a matter of reinforcing it through every piece of content.
Two businesses may both publish an article about CRM implementation. The one that clearly reflects its ideal client in the language, examples and challenges discussed is more likely to align with the right search queries.
Clarity in your positioning, and a clear understanding of the entity you’re writing about, increases the likelihood of being surfaced.
The Commercial Risks of Quantity Over Quality in SEO
There is a real opportunity cost to pursuing volume-first thinking.
If a marketing team spends its time producing ten surface level articles, it’s not spending that time researching one exceptional piece that could genuinely stand out. One well researched, insight driven article can outperform multiple generic ones in competitive markets.
Cannibalisation is another risk, and we have seen it more frequently over the past year. As output increases, topic overlap becomes harder to manage. Multiple pages begin targeting similar queries, which can dilute visibility rather than strengthen it.
There is also the impact on brand perception. If content becomes repetitive, thin or overly templated, it signals a lack of depth. In B2B and service-based industries, buyers notice when content feels generic, and increasingly search systems do as well.
What an Effective AI and SEO Strategy Looks Like Today
AI should absolutely be used within your website content and SEO strategy as an efficiency tool.
That being said, in our opinion and from our experience, it should be used to make you more efficient in producing higher quality content, not simply to justify producing more content.
If drafting is faster, the time saved should be invested in research, insight and clarity. Marketing teams should ask not only whether a piece of content targets a relevant search term, but whether it demonstrates genuine understanding.
A stronger starting point is the core problem your audience is experiencing. Build the most insightful response possible around that problem. Include nuance, lived experience and practical considerations that competitors would struggle to replicate.
Before publishing, ask whether the content would stand out in your market. Ask whether it reinforces who you are for, and whether it reflects real expertise.
Keywords, structure and technical SEO still matter, but expertise and alignment should lead.
The Strategic Shift Marketing Teams Need to Make
If I were speaking directly to a marketing director under pressure to do more with AI, the shift I would suggest is this.
Move from thinking about content as something you produce to rank, to thinking about content as something you produce to demonstrate understanding.
Start with the real customer problem, and develop a clear perspective on it. Add insight that only your business can provide, then optimise it properly.
AI has removed much of the friction from writing, but that doesn’t mean the bar has dropped. If anything, the bar has risen.
Search visibility hasn’t become easier – It’s become more selective.
The brands that win will not be the ones publishing the most. They will be the ones that are clearest about who they serve and what they know, which has always been the foundation of strong SEO.
