Why generative AI will mean more thought leadership (and less SEO-led ‘hygiene’ content)

Introduction [read: a rant about measurability]

One of the most profound changes to the marketing landscape in the last ten years is the heightened capability to measure. As metrics became more accessible and granular, the industry saw a pendulum swing towards favouring only what could be quantified, often at the expense of activities whose impact was less immediately measurable but no less important.?

As digital platforms proliferated, so did tools to measure every click, view, share, and conversion. This allure of data gave birth to performance marketing and advanced SEO strategies, where marketers could track, in real time, the results of every change, be it a keyword adjustment or a tweaked call-to-action. The promise was tantalising: tangible ROI for every action.

This shift to prioritising measurability meant that deeper, more comprehensive forms of content, such as white papers and detailed reports, began to take a backseat. While these materials played crucial roles in establishing thought leadership, building brand authority, or nurturing leads through a sales funnel, their impact wasn't as immediately quantifiable as a PPC campaign or an SEO tweak.

The phrase "What gets measured, gets managed" perfectly encapsulates the mindset shift. Marketing strategies became beholden to metrics. While this sounds prudent, it introduced a tunnel vision. Just because something can be measured doesn't mean it's of paramount importance. Conversely, the value of some activities, while immense, might not be instantly quantifiable.

A classic example is brand equity. While it's a critical component of a company's value and plays a massive role in purchase decisions, its direct measurement is elusive. Similarly, the relationship-building value of a well-researched white paper can't be reduced to mere download numbers.

And so, I’ve witnessed growing nervousness in championing initiatives that don't promise clear, immediate metrics. Especially when budgets are on the line, there's a tendency to stick to what can be presented in charts, graphs, and percentages.?

However, this caution sidelines initiatives that, while harder to measure, have the potential for long-term impact, brand loyalty, and authority building. While metrics provide a semblance of control and predictability, it's essential to differentiate between meaningful and meaningless metrics. Just because one can measure the time spent on a page down to the millisecond, or track eye movement across content, doesn't mean these metrics translate to actionable insights or real-world value. It's easy to drown in data while missing the bigger picture.

My hypothesis

And so, to my hypothesis: that generative AI will mean that brands will have to create thought leadership to out-compete their rivals AND they will have the resources to do it.

Content can be expensive. Some brands might need hundreds of pages to be competitive in their sector. This puts organic success beyond the reach of smaller players. And, as we know, SEO can be a zero-sum game where positions 0-5 take 99% of the traffic and the rest get nothing. Generative AI has meant that those smaller companies can now create generic SEO pages quicker and easier (and more cheaply) and play catchup with established brands with large digital footprints. This will mean that their smaller budgets can be spent on content that will genuinely cut through the noise and low-value content to really connect with audiences.?

And so, as we stand on the precipice of the AI revolution, brands must reconsider their content strategies. Here's why.

1. Generative AI can produce content, but not novel insights

Models like ChatGPT can generate coherent, contextually relevant content at scale. They can mimic human writing and answer queries across a plethora of topics. But they're essentially drawing from existing knowledge.?

For brands, this means that merely producing content won't suffice. The differentiation will come from offering unique insights, genuine thought leadership, and innovative ideas that an AI cannot simply replicate.

Here are just a few reasons why generative AI cannot replace human thought leaders:

Generative AI is knowledge aggregation, not innovation

Generative AI, like ChatGPT, is fundamentally based on data it has been trained on. It amalgamates vast amounts of information to produce coherent content. While it can combine knowledge in unique ways, it cannot spontaneously create novel ideas or concepts that haven't been part of its training. In contrast, sector experts often have years of hands-on experience, intuition, and tacit knowledge that isn't explicitly written down or recorded.

Thought leadership isn't just about presenting known facts or concepts; it's about pushing boundaries, challenging norms, and introducing fresh perspectives. Sector experts are perfectly placed for this role. They are often at the forefront of their fields, interacting with the latest technologies, methodologies, and trends. Their close proximity to the action allows them to identify gaps, forecast trends, and provide innovative solutions that a generative AI, which operates on past data, might miss.

Superficial understanding vs deep expertise

Generative AI can simulate expertise by accessing its extensive training data. However, it lacks the profound depth of understanding that comes from years of immersion in a particular field. Sector experts have often encountered unique situations, faced challenges, and made discoveries that have shaped their understanding in ways that cannot be merely 'learned' from existing texts.

The human element: context and intuition

Sector experts don't operate in a vacuum. Their insights are shaped by human experiences, interactions with peers, and the socio-cultural context of their field. This context gives them the ability to perceive nuances, ethical implications, and potential challenges or opportunities that an AI might overlook. Their intuition, developed over years, allows them to 'feel' when something is right or wrong, even if they can't explicitly articulate why.

Not all ideas are good ideas

Generative AI models can produce a myriad of ideas by combining existing knowledge in novel ways. However, they lack the innate human ability to discern the potential impact, feasibility, or value of those ideas in the real world. An idea is not merely about its novelty but also its applicability, relevance, and potential for positive change. Sector experts, with their deep-rooted understanding, can intuitively gauge the worth of an idea, foresee its implications, and guide its implementation.

2. Audiences crave authenticity - especially experts

Today's discerning consumers are adept at distinguishing between genuine content and mere filler. With AI tools potentially leading to an oversaturation of generic content, audiences will value and seek out genuine thought leadership. Brands that can provide real, human insights will earn their audience's trust and loyalty.

So why, when it knows EVERYTHING, does generative AI struggle to satisfy expert audiences?

Expert audiences are not just consumers of content; they are evaluators, critics, and influencers in their fields so they need more than just well-crafted content: they need genuine insights. They can tell the difference between fluff and genuine insights and brands need to deliver high-quality insights they didn’t already know.

Expert audiences and decision-makers have this innate ability to recognise when information stems from deep expertise and lived experience. It's not just about what is said, but also how it's said, the depth of analysis, the contextual nuances, and the foresight it displays. As such, it will be increasingly important for brands to create this content to stand out as they and their competitors will be using generative AI to create endless SEO blogs, levelling the playing field for competitors.

Genuine expertise is not just about presenting novel ideas. It's about the journey of arriving at those ideas, the trials and errors, the real-world challenges faced, and the lessons learned. This narrative, rich with experience, is hard for AI to replicate.

Generative AI operates by identifying patterns in existing data and replicating or combining them in unique ways. While it can produce content that sounds authentic, it lacks the intrinsic understanding, the emotional depth, and the lived experiences that expert audiences value. AI can't recount personal anecdotes of challenges faced during a project, the eureka moments during late-night brainstorming sessions, or the ethical dilemmas grappled with.?

Importantly, fellow experts will recognise the familiar technical language, if not the struggles that their peers share. These human elements, which add layers of authenticity to content, remain beyond the reach of current AI capabilities.?

3. SEO is evolving

Search engines, recognising the capabilities of generative AI, are becoming smarter. They're not just indexing content based on keywords, but also on the value it provides to readers. Shallow, AI-generated content may soon lose its SEO appeal, while genuine content that addresses real issues and offers fresh perspectives will rise in rankings.

Importantly, Google may well stop serving links to other websites and simply provide an answer via generative AI. Why direct people to a list of recipes for bread and butter pudding when it can just serve you one directly?

4. Building thought leadership is future-proofing

Brands that establish themselves as thought leaders in their field are not only securing their present but also future-proofing their brand. As AI becomes ubiquitous, these brands will be recognised for their genuine contributions, securing their place in the industry.

Brands will become more important than ever because everyone can create a decent SEO answer to a query.

5. Authentic engagement over metrics

In the age of AI-generated content, brands that focus solely on metrics might find themselves lost in the noise. Instead, the emphasis should be on authentic engagement. Real thought leadership fosters meaningful interactions, discussions, and community-building, metrics that AI can't generate on its own.

You may get 1,000 page views of an SEO blog, but how many people LOVE your brand because of it? An annual survey of your customers or other original data presented in a creative way is more likely to create genuine advocates - people who are more likely to buy from you.

This may also mean the value of social media goes up: people want social, not just media.

6. AI can be a tool, not a replacement

Rather than viewing AI as a competitor, brands should see it as a tool. Generative models can assist in content production, data analysis and, to some degree, idea generation. But the soul of your brand, its values, and genuine insights can only come from people - your people.

Put your people front and centre and you’ll see your brand rise above the sea of mediocrity to drive real returns.

And finally…

The emergence of generative AI has democratised content creation, enabling brands to produce vast amounts of SEO-optimised blogs and articles with ease.?

However, this means that the digital space is becoming saturated with similar, often repetitive content. For brands to stand out and beat their competitors, they need to offer something unique and valuable.?

Genuine thought leadership, rooted in authentic insights, expertise and innovative thinking, provides this differentiation. While AI can generate content based on existing knowledge, it lacks the ability to create truly novel ideas or offer deep experiential insights. As such, brands that prioritise genuine thought leadership will be recognised for their depth, authority and forward-thinking approach, making them more memorable and influential in the crowded digital landscape.