One of the reasons many businesses become frustrated with content marketing is that, after several years of investment, they struggle to identify what has actually been achieved. There may be dozens or even hundreds of articles on the website, regular publishing schedules may have been maintained and various keywords may have improved, yet the commercial impact often feels difficult to pin down. The content exists, but it rarely feels central to the business itself. Senior people within the organisation may not have read much of it, sales teams may not use it and clients may never encounter it at the moments that matter most.
Part of the difficulty is that a great deal of content produced over the past decade has been what I would describe as commodity content. These are articles that exist primarily because a keyword tool suggested they should exist. They answer broadly informational questions, follow familiar structures and cover material that has already been written many times elsewhere. They are often perfectly accurate and reasonably well written, but they contribute very little that could not be found on dozens of competing websites.
The emergence of generative AI has made this issue much more visible. If a large language model can produce a competent 1,500-word article on a topic in a matter of seconds, it becomes difficult to justify publishing material that offers little more than a reorganisation of publicly available information. In truth, this was already a problem before AI arrived. Much of the content produced by traditional SEO processes had gradually become predictable, largely because many organisations were using the same tools, targeting the same terms and following the same conventions. Generative AI has simply exposed how interchangeable some of that content had become.
This does not mean informational content has lost its value. Businesses still need to explain concepts, answer questions and educate their audiences. Search engines and AI systems alike still need clear, accessible information. The distinction is that information alone is increasingly becoming the baseline rather than the differentiator. Explaining what something is may still be necessary, but it is rarely sufficient.
When I speak to business owners and senior stakeholders, one of the questions I often ask is whether they recognise the content being published in their name. Could they explain why a particular article exists? Would they feel comfortable sending it to a prospective client? Does it genuinely reflect how they think about their subject? Surprisingly often, the answer is uncertain. Content has gradually become something that happens around the edges of the organisation rather than something the organisation itself actively participates in.
That separation creates difficulties because expertise does not reside within the marketing team, the SEO consultant or the AI tool. It resides within the people who actually do the work. The engineers, consultants, advisers, directors, specialists and practitioners inside the business possess the experience that gives the organisation its value. If their perspective never appears within the content itself, the resulting material inevitably becomes more generic, regardless of how technically well optimised it may be.
This is one of the reasons I increasingly find the phrase “content production” slightly unhelpful. It implies a manufacturing process in which material moves through a pipeline and emerges at the other end. In practice, the most valuable content often begins with conversation. It emerges from opinions, disagreements, practical experiences and observations that exist within the business itself. The role of strategy is not simply to identify topics worth writing about. It is to create a structure that allows genuine expertise to become visible.
AI tools are exceptionally useful within this process, but not necessarily in the way many people assume. They are extremely good at helping us understand what is already known. They can summarise existing information, identify common themes, organise research and reveal how competitors approach a subject. What they cannot easily provide is the accumulated experience of a specialist who has spent years solving particular problems for particular clients within a particular industry.
As generative search becomes increasingly capable of summarising established information, the value of that experience may become more rather than less important. Businesses do not simply need more content. They need content that contains something only they can contribute. The challenge is no longer producing articles efficiently. It is capturing expertise effectively and presenting it in ways that both people and search systems recognise as genuinely useful.
