The power of language-based artificial intelligence is understood by anyone who has had writing assistance from ChatGPT or Google’s Bard. By constantly analyzing the words used across an unimaginably huge internet data pool, AI has proven remarkably adept at understanding the underlying relationships between language-based concepts and, as a result, the collective wisdom of humanity.

These concepts, it’s fair to say, represent the building blocks of human cognition, consisting of thoughts, ideas, people, places, symbols, products, intentions, hashtags—all the things conveyed within our language. In the simplest of analogies, they might be thought of as the descriptors of our memories: When we think about “diamonds,” we might immediately associate “sparkle,” “ring,” “rare” and “valuable.” We instantly bring together the memories and associations of these individual concepts within the context of “diamond.” 

How does this apply to marketing? Let’s take a workwear retail brand as an example. Think about all the different ways people of all walks of life might define this brand, the associations we’d access if we got inside their minds: We’d expand our understanding of this audience exponentially and uncover the various and elusive reasons why people care about the brand. In fact, this is how marketers have always wanted to define their brands, but they have been constrained by the limits of consumer data. 

Now imagine being able to consume and associate all publicly available information that exists in the world about this brand and its products. The concepts that define what entices consumers would emerge—everything from its association with celebrities who wore the gear to partnerships the brand has formed, to granular associations based on age, aesthetics or sustainable practices. Imagine making media buy decisions with that knowledge. How many other marketing opportunities might emerge?

This is the magic of language-based AI made plain, and the technology already exists. But it doesn’t stop with simple associations. Each identified concept, and its associated concepts, can in fact be quantified in terms of their relative importance to the marketing objective. Sentiment, frequency, recency, trend and even demographics can be assigned to these concepts, and doing so transforms them into units of knowledge that begin to approach that of memory. When actionable within media, this translates into new audience opportunities, each of which can be judged qualitatively and quantitatively. 

And it’s not just the power of AI that makes it revolutionary, it’s the accessibility of the information that trains AI—it can now read, understand, enhance and act upon these learnings in near real time without huge research budgets and large teams of analysts—and, perhaps most importantly, without the need to limit audiences to a handful of expensive and ultimately limited set of the same targetable consumers everyone else is using.

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