AI in branding is no longer a futuristic idea. It’s happening now – and it’s changing how companies think about creativity, communication, and the role of humans in the marketing process.
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I used to work with Intel years ago. They were a marketing powerhouse, one of those companies where even the sound logo triggered recognition and trust. Their campaigns weren’t just smart, they were precise and emotionally sharp, even in a tech-dominated space. (And they had the best MDF funding program I’ve ever encountered.)
When I read that Intel is laying off large parts of its internal marketing team and outsourcing the work to Accenture, which plans to rely heavily on AI, I paused.
Of course, it’s a business decision, and from a financial standpoint, almost understandable.
But it also marks something bigger: It signals that we’ve entered a new phase where machines no longer just supports marketing but begins to replace parts of it.
And it raises a question that’s quietly sitting in many strategy rooms, even if few are addressing it directly: If AI can do marketing, what are we still here for?
AI is scaling faster than we realise
According to the latest BOND Capital AI Trends Report, the global AI market is expected to grow from $244 billion in 2025 to more than $1 trillion by 2031. The amount of computing power used to train large models is growing by over 300 percent per year. Tools like ChatGPT have reached hundreds of millions of active users within just two years.
This kind of acceleration is impressive. It’s changing how organisations think about creativity, communication, and branding. AI is moving from a helpful assistant to a central part of the process.
But when speed increases, so do the chances of missing something important. In this case, it’s the human side of marketing that risks being left behind.
What it still can’t do
There’s no doubt that AI is powerful. It can produce text, suggest headlines, generate images, and translate across languages in seconds. It can even mimic tone and adjust messaging based on target data. But it doesn’t truly understand the people it’s speaking to.
Even before AI, many brands struggled with localisation. The belief that successful home market campaigns could simply be rolled out elsewhere was already flawed. With the new technology now in the mix, this kind of thinking is being scaled, not solved.
Faster doesn’t always mean better. Neither does ‘cheaper’ – depending on your definition on your definition of it. (But that’s a different topic for later).
Machines still can’t tell when a brand’s tone sounds off in a different culture. It doesn’t know why a certain colour combination builds trust in one country but feels cold in another. And it doesn’t understand how humour, modesty, or authority are perceived differently across regions.
Also, it doesn’t read the room. It doesn’t pause to reflect. And it doesn’t know when something just doesn’t feel right.
That is still our role as humans.
What we humans bring to the table
While machines can do a lot, there are areas where human expertise remains essential. Not because we are clinging to the past, but because we bring something what machines simply can’t.
Cultural understanding
As humans, we don’t just translate, we interpret and localize. We understand how values shift between markets, why formality matters more in some places than others, and how cultural norms shape everything from colour choice to storytelling structure. These things aren’t written in training data, but they’re lived, observed, and felt.
Emotional depth
AI can simulate emotion, but it doesn’t experience it.
Human marketers draw on memory, identity, humour, and context. We know how to build a sense of trust, how to use silence, and how to create emotional pacing that resonates. These are more than techniques. They are forms of human connection.
Strategic perspective
AI can suggest. But it doesn’t decide.
It doesn’t consider the trade-offs between short-term wins and long-term brand health. It doesn’t weigh whether now is the right time to speak or to stay quiet. Strategic judgment comes from experience, from understanding people and patterns over time.
Brand coherence
When teams across different regions and departments use AI tools independently, brand identity can quickly become fragmented. Human oversight ensures that the brand stays consistent and meaningful. This isn’t about repeating the same message, but about adapting with care.
These human contributions are not extras. They are at the heart of brand building, especially when you want to grow across markets and cultures.
The role of experts is evolving, not disappearing
This blog post isn’t about resisting change. I use it in my own work every day. It speeds up processes, opens up new possibilities, and helps with things like first drafts, outlines, comparisons, and even translation.
But machines are not creative strategists. They don’t replace human connection, and they don’t hold the long view.
They are a valuable partner, but only when guided by someone who understands the bigger picture, the emotional tone, and the cultural context.
That’s where we come in: not just as content producers, but as editors, interpreters, and brand stewards — people who know how to speak to other people, not just generate words.
Final thought on AI in branding and beyond
The Intel story is just one example, but it reflects a broader shift that many companies are facing right now. As more and more content is generated by machines, the challenge isn’t to resist this change. It’s to make sure that what we create still feels human.
This is the space I work in: I help brands grow and resonate across markets by combining cultural insight, strategic thinking, and smart use of modern technologies.
If you’re exploring similar questions, feel free to reach out or follow along. There is a lot ahead to figure out, and even more worth building.
Sources
BOND Capital (2024). Trends in Artificial Intelligence.
https://www.bondcap.com/report/pdf/Trends_Artificial_Intelligence.pdf
The annual report outlines key developments in AI adoption, investment, model scaling, and global business applications, including growth forecasts for the AI market and shifts in enterprise behaviour.
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