Branding and AI-High Tech without HighTouch?

– Professor S Ramesh Kumar
IIM Bangalore

AI is revolutionizing how brands come to life, but it also brings potential hazards. The danger of content uniformity looms, risking audience confusion and a misalignment with the brand’s true essence. Emphasizing human intervention is essential, allowing brands to navigate AI’s limitations and cultural nuances effectively. Furthermore, biases embedded in AI can erode customer trust.

“Products are made in the factory, but brands are created in the mind” — Walter Landor

The axiomatic quote made decades back has assumed refreshing significance in the AI era where brands find it almost impossible to operate without AI based applications. The digital era will herald several new normals that one may not have even thought of a decade earlier. The challenge for brand managers to keep the AI initiatives human centric to ensure that the application of AI results in making the brand that much more powerful. Human centric aspect is not just from the viewpoint of consumers but also from the viewpoint of brand decisions associated with human discretion.

Paul Daugher and James Wilson in their “How New Technology is shaping Our Future” convey the point that human expertise is needed to create human centered AI. Human-machine interface is required to ensure that brands are about human minds rather than just products and graphics. “Where can AI derail when brands employ AI in their quest for competitive strategies?” is an important question that needs to be asked before AI based initiatives are planned by the brand manager.

Forbes Communication Council (2024) had carried the views of experts on the risks associated with AI and branding. These risks address several aspects associated with the application of AI to branding processes. Several established concepts like brand positioning, brand identity, brand elements, brand salience and brand personality can be viewed with a renewed lens if these risks are taken into consideration. Some of the risks from the publication are elaborated in this article.

*Sameness of content

The homogenization of content may be the result of Gen AI being employed by several brands. This results in the dilution of brand differentiation going against the very nature of branding. A 2025 paper on the subject from the researchers at London Business School (Choran Lu, Tong Wang and S. Alex Young) shows that access to ChatGPT increased homogenization of context and reduced consumer engagement amongst restaurant brands. A 2024 campaign of Under Armour using AI had generated controversy about previous commercials being used in the campaign without proper credits being given to the creators. The point to be noted is that a brand (established or new) cannot afford to generate controversy or create fatigue when it uses AI. Brands in several categories have started using AI images and even an insignificant similarity of images across brands can affect the sub-conscious of consumers leading to brand dilution and confusion about the identity of the brands involved in sharing the similarity of associations.

*Possibility of eclipsing the very proposition of a brand

Brands are all about associations and these associations also command brand premium. As AI gets into generation of associations, the psyche of consumers may be impacted even without their knowledge. For instance, facial recognition is an implicit mechanism of the human mind. In an awe inspiring piece of research published by Robin Tanner of Wisconsin University in Journal of Consumer Research, digitally blending an unfamiliar face with 35% of Tiger Woods resulted in a composite face that was considered more trustworthy than the original face of the celebrity (before the scandal involving this celebrity), despite the fact that 100% of the respondents failed to identify any resemblance between the morphed face of Tiger Woods and Tiger Woods himself! One can infer the implications of such a fact on brands using celebrities especially in the Indian culture that idolizes celebrities from different fields. Should a brand not use celebrity? If it uses one what kinds of precautions are required? What about aspirational brands like Lux which have been using film celebrities as an inherent part of its brand proposition over several decades? Such brands associate celebrities with their offering to convey the brand proposition. Such a brand may have to think of appropriate strategies to preserve and nurture their proposition. Celebrity usage by brands in general may undergo several transformations with the advent of AI.

*Human Oversight

Taco Bell had used AI voice ordering, in over 500 drive throughs to speed up service and reduce errors but was faced with glitches and misinterpretations like a customer ordering “18000 cups of water”. Air Canada’s Chatbot provided a customer with unintended bereavement fares and the airline was forced to honor the promise!

*Cultural sensitivity

A 2025 publication from MIT titled “Cultural Tendencies in AI”, infers that generative AI is not culturally neutral. It is crucial for brand managers to be aware of the cultural tendencies embedded in them. India is a country with significant cultural diversity across its geography. Should the AI be prompted in English to generate an independent style to address a segment of urban consumers to generate ads with a self-assertive and individualistic style (for example like some of the ads of Raga brand), or should the AI be prompted in a regional language to generate dependent orientation that highlights family dependence (for example like the Cadbury Dairy Milk’s Palampur ad)?

*Biases

Insights from Kellogg School of Management (2026), ”Beware of AI’s Very human Biases” points out that several biases including psychological biases creep into AI systems. The authors provide an example of how an AI system designed for engagement can end up with an AI that promotes emotional, moral and in-group information because we engage with that information. Insights from Harvard too (“Confronting the Mirror: Reflecting on Our Biases Through AI in health care” 2024) provides the example of how AI uses across health systems in the US exhibited bias by prioritizing white patients over sicker black patients for additional care because the systems were trained on cost, not care requirements. The implications of such shortcomings in an AI system on customer satisfaction, segmentation and overall brand strategy are quite evident.

John Naisbitt (with his co-authors), the futurist had published the book “High tech / High touch: Technology and Our Search for Meaning” four decades ago, to emphasize that the success of any technology depends on the extent to which it can enhance human experiences. As long as human experiences with brands involve intrinsic emotions, / will have to wait for the era of curated emotions; until then, brands will continue to be manufactured in the mind.

Source: ET Brand Equity