In an industry fixated on identifying shifts and trends, there is an equal and opposite opportunity for AI to help us better understand the consumer dynamics that stay the same over time.
I read a piece recently by Richard Shotton that stuck with me. He wrote about how evolutionary psychology is the driver of human nature, making it “ludicrous to think anything should change in five to ten years.” This rings especially true to me as a Gen Zer. I’m part of a generation that is frequently defined as fickle and ever evolving, with marketers scrambling to keep up with the latest Gen Z trends. Whilst culture undeniably moves at pace and requires constant monitoring, the core emotional needs of Gen Z, and every other generation, remain much steadier. I often see my age group flattened into stereotypes, whether it’s that self-expression is the thing that drives 100% of our purchase behavior, or that we have less brand loyalty than the generations before us.
In reality, the obsession with Gen Z behaviors can too often mistake cultural expression for psychological change. The core consumer motivations of Gen Z are not new nor exclusive to this generation; Maslow’s Hierarchy of Needs argues that everyone has a set of basic universal needs, with belonging, status, and cognitive ease chief among them. The difference, in my opinion, is that these are expressed through new platforms and media habits over time, as technology and culture evolve.
This is where AI can add meaning and value, by allowing us to understand consumers better in the long term. We can use it to analyze and detect patterns in large swathes of historical audience data, from purchase behaviors and brand tracking to reviews, search patterns and cultural language. In doing so, it can identify which consumer motivations reliably recur vs. which are the transient expressions that shift with culture, technology, and platforms. AI’s value lies less in identifying new drivers of behavior and more in validating the persistence of existing ones, preventing shifts in cultural expression from being mistaken for changes in core human needs.
Whilst we broadly understand universal human needs, AI can help us to unlock insights on how their relative importance changes by category and context. Let’s take luxury as an example. The underlying category motivation has long been rooted in status and identity signaling. Though the desire for status has not changed over time, the socially accepted ways in which this is expressed have shifted. Once communicated through overt logos and visible price cues, luxury signals have evolved into subtle branding and an IYKYK behavioral code. We can see here how emotional drivers consistently influence choice within a category, even if their cultural expressions evolve.
By helping us to differentiate between the two, we can avoid reductive audience tropes and test creative and media ideas against enduring human truths. This will allow brands to focus on modernizing how to express emotional truths that matter to consumers and build stronger, longer-lasting connections with audiences.
This is a Gen Z perspective on trend #7 in dentsu’s Human Truths in the Algorithmic Era | 2026 Media Trends report. Get your copy of the report here to see all ten trends.
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