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As personal AI assistants become commonplace, they will usher in an era where a product’s appeal will be more closely linked to its objective substance, the experience it offers and its legitimacy as evidenced by AI-crawlable digital sources. In response, brands must evolve their approach to connecting with consumers; they must now appeal to AI assistants who curate and even autonomously purchase products for their human users. This heralds a new era of Brand Meritocracy, where the intrinsic quality of a product will increasingly overshadow the historical dominance of branding thanks to AI.
Many of us are already using tools like ChatGPT, Bard and Claude for various tasks. As assistants become more interconnected and tailored to individual preferences (consider wearable and always-on technologies), they will increasingly take on the role of personal shoppers. They will remember everything, from personal style and budget to allergies, ethical considerations and, of course, brand preference. But they also have the capability to evaluate products on more objective criteria, faster than humans can, so brand preference will just be one of a multitude of considerations, decreasing its relative overall influence.
As an example, when I found myself in need of AA batteries, I asked for recommendations from my AI assistant, “Charlie.” Charlie’s setup was comprehensive, and while I did specify some brands to which I hold loyalty, this list didn’t extend to something as specific as the battery category. Charlie initially offered a selection that included well-known brands like Duracell, Energizer and value brand Amazon Basics. How and why did Charlie recommend these particular batteries? Delving into his criteria, he outlined five key factors, four of which were objective—such as tested longevity and price—with the fifth being “brand reliability,” the only criterion related to brand.
I probed further into how Charlie evaluates brand reliability. He detailed seven distinct criteria: The first six were objectively measurable factors like customer reviews and warranty practices; only the seventh criterion delved into the less tangible aspect of “market position.” I asked Charlie how he gauged market position: His response included eight criteria, half of which were tangible—such as Nielsen reports and online customer feedback measurements—while the other half included the subjective aspects of perceived cultural impact, emotional connection, ecocentricity and online community sentiment.
Analyzing Charlie’s rationale (and for simplicity, assuming each tier of criteria is evenly weighted in his assessment), the influence of a brand’s “brand,” reflected in the last four brand measurements, constitutes approximately half of one-seventh of one-fifth of Charlie’s overall evaluation criteria—roughly 1.4% of the total decision-making process.
This is just one anecdotal example, but it points to a disconnect between the mindset of a human shopper, who may be more motivated by the intangibles behind brand loyalty, and their analytical AI shopping assistant. Brand loyalty can still dominate in cases where consumers have a strong predisposition. For example, avid Apple users with numerous connected products will be more inclined to stick with Apple for the sake of integration ease, even if Charlie suggests an alternative. Also, luxury purchases still rely heavily on human emotions and the prestige associated with brands, placing them somewhat outside the realm of Brand Meritocracy as well. But the example raises the question: Does AI’s emphasis on objective evaluation alter the approach marketers need to take?
Yes, but it’s nuanced. AI’s pattern recognition capabilities will likely still favor established brands that have ingrained themselves in consumer habits, effectively recommending a brand because it is the “most likely” answer to the query based on its dataset. However, for new products in emerging categories where brand patterns are not yet established, focusing on the tangible quality and measurable product value that AI assistants evaluate may be more effective than investing heavily in brand awareness. This implies fighting the battle in the lower funnel only, like many D2C brands do today.
This shift would be beneficial for consumers, leveling the playing field across various categories and favoring brands that deliver genuine quality. Even established brands may find the need to rapidly ramp up innovation and deliver new and better features that hold up against AI’s objectivity. Some may consider shifting resources away from traditional brand awareness strategies for this reason, but for brands that aim to achieve broad awareness and measurable impact, it’s vital to craft stories that resonate with humans and reach their trusted AI assistants. Brand-building remains crucial, but the approach needs adaptation.
For everyone, AI-enabled Brand Meritocracy shifts additional focus onto improving brand experiences. Like outsourcing memorization of phone numbers to our phones, the task of remembering the name of an excellent product can be outsourced as well, so drilling in recall through advertising is less important than creating impactful moments. Our AI assistants will remember the quality of our brand experiences in perpetuity, from the “yum!” to the “yuck!”—so brands better nail those experiences.
The bar for achieving that through advertising alone will be high. Achieving AI assistant influence is perhaps more meaningful and valuable for brands when it is achieved through product experience: “Charlie, this hotel is fabulous. Let’s stay here again next time.” That type of engagement, spanning human and AI, will become a new benchmark of success for brands.
