Branding Beats AI: Why the Brand Is the No. 1 CMO Priority in 2026

In the year in which everyone is talking about artificial intelligence, the people who run marketing have made a remarkably quiet decision. In its „State of Marketing Europe 2026“ McKinsey surveyed 500 senior marketing decision-makers in Germany, France, Italy, Spain and the UK. The result: branding is the No. 1 priority for 2026. Generative AI ranks 17th out of 20 priorities. Let me say this clearly, because the headline invites a misreading: this does not mean „ignore AI“. It means the brand is the foundation and AI is the lever – in that order. Anyone who deploys generative AI on top of an interchangeable brand merely scales their own replaceability. Anyone who builds a distinctive brand first turns AI into a genuine multiplier.

I find this finding clarifying rather than surprising. After years in which the discourse equated „modern marketing“ with „more technology“, the pendulum is swinging back to the question that was always the actual one: what does this brand stand for, and would anyone recognise it without the logo? In this piece I want to show why the brand is returning precisely now, what the science behind recognition says, why „brand or AI“ is a false dilemma, and which five principles, in my experience, carry a brand through 2026.

Why the brand is coming back of all times now

The simplest explanation is saturation. When everyone can produce content at near-zero marginal cost, content stops being a differentiator. The market noticed this so quickly that language itself reacted: „slop“ – low-quality digital content, mostly generated by AI in bulk – is Merriam-Webster's word of the year 2025. The specific phrase „AI slop“ is the Macquarie Dictionary's word of the year 2025. According to Meltwater, mentions of „AI slop“ rose roughly ninefold from 2024 to 2025. A culture does not coin a word of the year for something marginal. It does so for something it can no longer ignore.

The flip side of the slop fatigue is an authenticity premium that can be measured. Edelman 2025 finds that 87 percent are more likely to pay more for brands they trust. Stackla and Nosto report that 86 percent consider authenticity important when choosing a brand. And the scepticism toward AILed output is real, not anecdotal: Bynder 2024 found that 50 percent can recognise AI-written text and 52 percent engage less afterwards; Gartner (September 2025) reports that 53 percent distrust AI-generated search results; Deloitte 2024 puts the share concerned about deception at around 70 percent. The pattern is consistent. The more generic content the world produces, the more a brand that visibly carries a human signature is worth.

The science behind recognition

There is a body of research that explains, rather than merely asserts, why this matters. The Ehrenberg-Bass Institute, and in particular Byron Sharp and Jenni Romaniuk, have shown that brands grow primarily through being easy to notice and easy to recall – what Sharp, in „How Brands Grow“ (2010), calls mental availability. The vehicle for this is what Sharp and Romaniuk term distinctive brand assets: colours, shapes, logos, characters, sounds, a tone of voice that the brain can attach to the brand without conscious effort.

From this work comes the position that distinctiveness beats differentiation. The argument runs like this: people do not usually compare brands analytically along rational advantages; they choose, in a split second, the brand they recognise. A distinctive asset therefore does more work in the real buying moment than a clever positioning claim. I find this persuasive – but I owe you honesty: this is a position of Sharp and the Ehrenberg-Bass Institute, and it is contested within the field. Mark Ritson, among others, argues that differentiation and distinctiveness are not rivals but complements, and that strong brands need both meaning and recognisability. I treat distinctiveness as the more reliable lever, without pretending the debate is settled.

The thinking error of „brand OR AI“

The most expensive mistake I see right now is reading the McKinsey ranking as a verdict against AI. It is not. The same study contains a figure that should give every sceptic pause: 94 percent of marketing organisations have not yet advanced their generative-AI maturity – and the mature 6 percent already realise around 22 percent in efficiency gains. That is not an argument for ignoring AI. It is an argument for sequencing it correctly. The brand decides what you say and why anyone should believe it. AI decides how fast, how personalised and how cheaply you can deliver it. Confuse the order and you automate emptiness.

It helps to see the actual numbers side by side rather than as competing slogans.

Read top to bottom, the table tells one story: budgets are rising, the brand leads the agenda, and AI is an under-exploited efficiency reserve – not a substitute for the work the brand does. The 72 percent who are raising their budgets in 2026, up from 49 percent a year earlier, are not betting against AI. They are betting on having something worth amplifying.

What this means for the German mid-market

For the German mid-market this is more than a European headline; it is a near-term competitive question. The German Brand Monitor 2026 (gmk Markenberatung and the German Design Council, fielded in May 2025 among 311 managers across the DACH region) puts a hard number on the value of brand strength: 45 percent of strong brand companies achieve sustainable growth – something only 17 percent of weaker brands manage. That is not a soft „branding is nice“ statement. It is a growth gap of more than two and a half to one, in favour of the companies that have done the brand work.

The same study reveals where the mid-market actually stands on AI – and the picture is sober rather than triumphant. 67 percent of the companies surveyed have made first experiences with AI, but only 25 percent already integrate it systematically. Read alongside the McKinsey finding, this is reassuring rather than alarming. The mid-market is not behind on AI in any catastrophic sense; almost everyone is. The advantage is up for grabs precisely because so few have claimed it – and it will go to the companies that build the brand first and then let AI carry it further.

Brand as foundation, AI as lever

If I had to compress the whole argument into one sentence, it would be this: build the brand as an entity, then use AI to make that entity ubiquitous. The interesting part is that this is no longer only a human concern. Brands are increasingly perceived not just by people but by AI systems that answer questions on their behalf. And here the data points in a direction that should reassure anyone who has invested in brand: an Ahrefs analysis of 75,000 brands (2025) found that brand mentions correlate roughly three times as strongly with visibility in Google AI Overviews as backlinks do (Spearman 0.66 versus 0.22). Ahrefs itself is careful to add that correlation is not causation – and so am I. But the direction is hard to ignore: in a world where AI answers questions, being a frequently and consistently named entity is plausibly worth more than the classic link-building playbook.

In practice that is exactly the brief we work to. The visible side of the brand – the identity, the voice, the recognisable assets – is what we treat in detail under our services, and the craft of building a recognisable identity in the anti-slop era is the subject of a related piece on brand identity in 2026. The machine-readable side – consistent naming, structured data, the brand as a clean entity across the web – is what turns that identity into AI visibility. Both sides have to say the same thing. A brand that reads one way to humans and another way to machines is exposed at the first AI query.

Five principles for a brand that holds in 2026

From everything above, five principles follow that I would put in front of any AI initiative. None of them is anti-technology. All of them assume that the brand comes first.

Principle 1: Distinctiveness before differentiation. Invest in distinctive brand assets – colours, shapes, a logo, a tone of voice – that the brain can attach to your brand without effort, rather than in interchangeable „premium“ aesthetics that look like everyone else's. The goal is mental availability: that your brand is the one that comes to mind, and is recognised, in the split second of the buying decision. Recognisability beats cleverness when no one is comparing analytically.

Principle 2: A visible human signature. Treat authenticity signals as a deliberate answer to slop fatigue. Named photographers instead of generic symbolic imagery, documented decisions instead of anonymous output, small intentional imperfections instead of machine-smooth uniformity. In a market where 52 percent disengage once they spot AI text and 87 percent pay more for brands they trust, the visible hand of a human is not nostalgia – it is a margin.

Principle 3: Brand as foundation, AI as tool. Use AI for what it is genuinely good at – scaling, personalisation, efficiency – and keep it away from the identity itself. The mature 6 percent in the McKinsey data earn their 22 percent efficiency gain by applying AI to execution, not to the question of what the brand stands for. Let the machine carry the message further; never let it decide the message.

Principle 4: Make the brand machine-readable. Ensure consistent brand mentions and structured data so that your brand appears as an entity in AI answers. This is the operational consequence of the Ahrefs correlation: name the brand the same way everywhere, describe it in schema, and make it easy for an AI system to recognise as one coherent thing. A brand that machines cannot parse is invisible in the layer where more and more decisions begin.

Principle 5: Tie brand strength to growth. Make brand management measurable rather than a matter of taste. The logic of the German Brand Monitor is the management case for branding: strong brands grow, weak ones do not, and the gap is large enough to plan against. Define what brand strength means for you, track it, and hold it accountable to the same growth metrics as any other investment.

Conclusion

„Branding beats AI“ is not a rejection of technology. It is a statement about order. The marketing leaders McKinsey surveyed have understood that the brand is the scarce asset and AI is the abundant tool – and that you build the scarce thing first. For the German mid-market the opportunity is unusually clean: brand strength already predicts growth, most competitors have not yet claimed the AI advantage, and the two reinforce each other when sequenced correctly. Build the brand as an entity. Then let AI make it ubiquitous.

If you are weighing where to put your next marketing investment – into the brand or into another tool – that is exactly the conversation I am happy to have, up front and without sales pressure.

Frequently asked questions about branding and AI 2026