Does a brand’s strength actually differentiate in an AI-driven market?
One of the biggest risks of AI-driven marketing is that brands start to sound the same because they’re all using the same AI models to generate blogs, ads, and messaging. Brand strength comes from breaking out of that mold.
Instead of generic, safe, AI-optimized social media posts, try to build a brand voice around something different (i.e., humor, sarcasm). Though you have to be careful with humor – what’s funny to you isn’t funny to others – finding a “niche” differentiator will do the trick. Then, your tone will be unpredictable, human, and distinctly not AI-generated—it will stand out. And avoid over-optimization—AI will always default to “safe” messaging, but people respond to bold, authentic communication.
Emotion Speaks Louder Than Words
AI makes marketing more efficient, but efficiency alone doesn’t build customer loyalty. People remember how a brand makes them feel, not just what it sells.
In 2015, Kevin Roberts, the Executive Chairman of Saatchi & Saatchi, one of the top agencies in the world at the time, produced a “red” paper about brand loyalty.
Roberts’ credentials are unmatched. The red paper is called “Brand Loyalty Reloaded” and it is highly recommended reading. The essential thought behind loyalty is what he called Lovemarks (something they invented), and the concept was disarmingly simple:
Take a brand away and people will find a replacement.
Take a Lovemark away and people will protest.
In other words, Love is one powerful emotion. Emotions like love (and loyalty) are very elusive when trying to quantify using language. Which is what Roberts tried to do in one word: Lovemarks.
In particular, “Lovemarks proposes that mastering the emotional dimensions of marketing is by far the most important requisite of an enterprising life in business” he wrote in his paper. “Lovemarks go beyond rational factors into the emotional territory of Mystery, Sensuality and Intimacy.”
But do consumers really love products? I mean, really? Why would you buy Alexander McQueen sneakers rather than Sketchers? There are some people reading this who never heard of McQueen. There are some people reading this who wouldn’t buy anything else.
One might argue that both sets of buyers are “loyal” to their brand.
The same argument can be made of ANY brand, which is why Roberts’ paper is so interesting. Emotions can certainly play an important role in any purchase, but there are probably more purchases that don’t involve emotion at all, but rather, habit.
The product-shopper relationship has always been interesting and much studied. But, if you start with the premise that all shoppers are yours to lose, it makes understanding “loyal” easier. In other words, the product gives you the reason to be loyal, or not. And the stimuli around the product helps the loyalty ebb and flow.
Use AI for personalization, but layer in human storytelling and real customer experiences. It’s hard to love an algorithm.
Why “It’s Hard to Love an Algorithm”
Consumers might appreciate AI-driven convenience, but they don’t form emotional attachments to algorithms. They build relationships with brands that feel human, responsive, and genuinely invested in their success. That’s why AI should be seen as a tool, not the face of the brand. The most successful companies use AI to enhance human interaction, not replace it.
For example, an AI might:
- Identify a key pain point based on a customer’s browsing behavior.
- Trigger an automated follow-up email with relevant content.
- But the real impact happens when a sales rep follows up with a personalized video, addressing the customer’s concerns in a way AI cannot replicate.
AI as an Enabler, Not a Replacement
The future isn’t AI vs. humans—it’s AI and humans. Businesses should use AI to deliver the right message at the right time while ensuring that the voice, tone, and content reflect real human experiences. The goal is precision without sacrificing personality—because at the end of the day, people want to do business with people, not just predictive models.