Why AI is Not Going To Build Your Brand a Moat
Let’s get this out of the way: AI is not the competitive advantage you think it is – it’s simply the new baseline.
If you believe a $60-a-month “automated SEO” SaaS or a few AI workflows can replace your SEO team, you’re 100% wrong. That’s not me being protective over an industry, it’s just the economics of parity. When everyone can access the same tools, at the same price, with the same outputs… there’s no moat. There’s just a lot of average content and link spam swirling around.
And that’s the bit I don’t understand about the “AI can do that” rhetoric when it comes to content, link building, and strategy. Yes – small businesses can now afford to produce content at scale. Yes – enterprises can scale faster than ever. These tools have lowered the barrier to entry at different levels, but your competitors can do exactly the same thing.
An automated link-building tool used by 50 businesses in the same industry doesn’t give any of them an advantage in the SERPs. The competitive advantage lies in the activity that is not easy to do, in the targets that are not easy to achieve. It’s not easy to win a piece of coverage or a backlink in Vogue, The Guardian, Marketing Week or any other highly valued publication in your niche – and that’s why it’s a competitive advantage if you do.
You might feel productive scaling your link building and pumping out content, but you’re just running on a treadmill with 49 other brands.
Here’s the uncomfortable truth: AI raises the barrier to entry for content and technical execution, but the playing field levels out the moment everyone catches up.
Your moat isn’t the tool or the automation – it’s your strategy, execution, and brand equity.
The Parity Trap of a $60/Month AI Tool
The “AI as advantage” story sounds good in a sales pitch, but the reality is a textbook case of commoditisation.
- Same inputs → same outputs → same outcomes.
- When everyone can instantly scale blog posts, videos, or backlink outreach, differentiation dies.
- The only real result is a race to who can produce more, faster and in a commoditised race, margins shrink and value gets diluted.
Take the “SEO heist” example. LinkedIn influencer and content marketer Jake Ward shared an AI content case study, where he was able to pull in millions of AI-generated clicks. Sounds great – until you learn that, weeks later, the client’s SaaS had only 300 subscribers. The traffic looked impressive on a chart, but it was low-intent, low-value, and low-impact.
That’s the parity trap in action: all clicks, no compound value.
If your competitors can replicate your “advantage” by next Tuesday, you don’t have an advantage, you have a temporary head start. And in SEO, head starts without moats are worth very little.
Defining the ‘Clicks That Count’
We’ve moved past the point where click volume alone is a meaningful KPI, with more and more searches resulting in zero clicks.
For us, Clicks That Count are the ones that directly contribute to business growth. That means:
- Revenue: Are the clicks turning into sales, contracts, or recurring subscriptions?
- Profit margins: Are they coming from channels that don’t erode margins (think: improving your organic share to offset paid spend)?
- Visibility vs competitors: Are we increasing our share of voice and impression share against the brands that matter in our space?
What we prioritise:
- Revenue and profit impact.
- Share of voice and impression share in high-value markets.
- Search presence across the customer journey (not just last-click conversions).
What we deprioritise:
- Raw click counts.
- Vanity traffic (keywords with volume but no intent).
- Rankings for terms that don’t meaningfully contribute to revenue or brand growth.
In the AI era, success isn’t about “how many” but “how much they matter.” And that shift in thinking is where many SEO strategies still haven’t caught up.
AI in Technical SEO: The 98% Rule
Here’s my prediction: 98% of technical SEO will be handled by AI in the near future.
Not “could be.” Will be.
Crawling, indexing checks, schema generation, internal linking suggestions, site monitoring, regression tests – these are all black-and-white tasks. They’re perfect for machine execution because they’re rules-based, repeatable, and measurable.
That means SEO teams won’t need the same human headcount for technical implementation. Instead, humans will step into a quality control and exception-handling role:
- Edge cases where AI doesn’t understand business context.
- Strategic tech decisions like deciding when to consolidate vs expand site architecture.
- Governance – ensuring automation aligns with brand, compliance, and business priorities.
For agencies like ours, that’s a gift.
If AI can run the plumbing, we can redirect time and energy into strategy, content quality, brand equity, and building the moat – the work AI simply can’t replicate.
Non-Replicable Moat Assets (You Can Build in 60–90 Days)
If AI creates parity in execution, your moat comes from assets that can’t be copied overnight. These type of assets most often take the form of content that only your brand can create – whether that’s because of the resource you have, the product or service, first party data, research; anything that you’re in a unique position to comment on or create.
Here are a few that tick that box and can be rolled out quickly:
These work they’re resource-intensive, relationship-driven, and inherently unique to your brand’s positioning. Competitors can imitate the format but they can’t replicate the trust, data, or community you’ve built into it.
Distribution Stack: Beyond “Publish & Pray”
One of the biggest mistakes I see? Brands assuming that hitting “publish” is the end of the job.
In an AI-parity world, distribution is where you win.
Here’s our preferred stack for getting content seen, shared, and cited:
- Network of relevant bloggers & writers – we approach armed with ready-made hooks, multimedia assets, and story angles.
- Newsletters – building an owned audience that engages directly with your content.
- Paid social amplification – strategic boosts to ensure high-value content reaches the right eyeballs.
- Brand partnerships – co-created content and cross-promotion with aligned businesses.
- Syndication & Paid Seeding – placing your content in relevant industry publications, communities, or aggregators.
The key is to design distribution before you create the asset.
You’re not asking, “How do we get people to read this?” after it’s live, you’re baking the audience, channels, and hooks into the plan from day one.
Brand Mentions as a GEO Lever
In the AI search era, brand mentions are the currency of authority.
Large Language Models (LLMs) and AI Overviews pull from brands that are consistently mentioned and cited in trusted sources.
Here’s how we operationalise that:
- EGC (Employee-Generated Content): Encouraging employees, partners, and advocates to post genuine insights, opinions, and experiences on LinkedIn and other platforms. This naturally increases mentions in social search and niche communities.
- Digital PR & Newsjacking: Leveraging trending stories to position our clients as expert voices, earning both mentions and backlinks.
- Expert Profiles: Optimising the profiles of employees or partners so they’re media-ready – journalists can find them, quote them, and link back to your brand.
- Shareable High-Quality Content: Pieces people want to reference. Not just another “Top 10 Tips” article, but original research, compelling narratives, or highly visual explainers.
When you combine these with strong technical signals and entity optimisation, you increase the odds of your brand being cited in AI-generated answers, which is the very definition of GEO success.
Guardrails Against Spammy Automation
It’s not AI itself that’s the problem – it’s how people use it.
We had a client come to us with a manual action.
Not because they’d used AI.
Because they’d scaled thousands of human-written, low-quality pages that added no value.
That’s the cautionary tale: bad is bad, whether it’s written by a human or a machine.
Our guardrails:
- Editorial Review: Every piece of content is reviewed for accuracy, originality, and usefulness before it goes live.
- No Over-Scaling Without Quality: If it can’t maintain standards at scale, it doesn’t get scaled.
- Measure Impact, Not Volume: We track engagement, conversions, and brand lift – not just output quantity.
- Stay Aligned to Brand & Audience: Automation must serve brand trust and user needs, not just rankings.
Contrarian but True Statements
These are the lines I’m willing to put my name to and the ones I know will ruffle feathers on LinkedIn, at conferences, and in client boardrooms:
- AI will never kill SEO – it will make agencies more desired.
The more automation handles, the more valuable strategic human oversight becomes. - AI is not the competitive advantage you think it is.
At best, it’s parity. Your brand, positioning, and execution are the real differentiators. - Use AI so you don’t get left behind but don’t mistake it for your moat.
The moat comes from assets, relationships, and IP no one else can duplicate. - Your moat is unique to your brand – inherently product- and customer-led.
If your “advantage” can be bought off-the-shelf, it’s not an advantage.
If you’re unsure whether you’re using AI in the right way, get in touch and we can help you build a strategy that focuses on the clicks that truly count.
