"Why" Comes Before A and I
"Why" Comes Before A and I
Better decisions about baking AI into your products start with the end user in mind.
In last week’s article, my CognitivePath partner and Substack co-author Geoff asked whether the AI hype bubble is about to burst. He posited that, if and when it does, it’ll be a good thing. Now, you might debate whether AI is overhyped, under-hyped, underrated, or overrated. But, the reality about AI does seem to be setting in. Decision-makers are starting to realize that investing in technology for technology’s sake isn’t a formula for success.
As Geoff concludes:
“Too many times, organizations look at AI and ask how they can incorporate it. If a technology does not serve a use case and/or resolve a specific business need, it simply does not belong regardless of hype… Just because a new technology is hot, does not mean it is right for your organization.”
It also doesn’t mean AI is right for your customer.
In fact, the evidence is mounting that consumers are growing wary (and weary) of organizations’ rush to embed AI into everything. Even one of generative AI’s most popular applications — the customer service chatbot — isn’t a clear winner. Gartner has found that 64% of people would prefer companies not to use AI in their customer service. Even worse, 53% of customers would consider switching to a competitor if they found out a company does.
To be fair, the average consumer has been using AI for quite some time, reaping its benefits, and hardly batting an eyelash. Analytical AI and predictive AI (good old-fashioned machine learning) are at work in a wide range of widely used products and services. It guides your Amazon shopping experience. Recommends movies you might like on Netflix and songs you may enjoy on Spotify. It ranks and recommends web pages on search engines, completes your sentences in email, maps your route on Waze, and curates your social media feeds.
But this doesn’t mean consumers are clamoring for shiny new generative AI in their cars, kitchen appliances, toothbrushes, or toilet seats (yes, toilet seats). In fact, recent research led by a team at Washington State University found that the mere mention of AI leaves consumers cold.
According to one of the study’s authors, “We looked at vacuum cleaners, TVs, consumer services, health services. In every single case, the intention to buy or use the product or service was significantly lower whenever we mentioned AI in the product description.”
The authors of the WSU study ultimately concluded that AI-obsessed marketers have a messaging problem. That the solution (or part of it, at least) lies in pitching consumers on the benefits AI brings, rather than pitching the technology itself. And certainly, this could help.
But I think the challenge for businesses runs deeper than messaging alone. As I note in this clip from my recent keynote at the Leading Marketing & Sales Conference in Santiago, Chile, AI decision-makers need to keep the customer’s needs in mind from the very start. This requires organizations to put customer beliefs and behaviors about AI at the center of product and service decisions. It means having a robust understanding of what your customers want, what they value, and why they choose to do business with you.
Most importantly, it challenges companies to choose not to use AI when this turns out to be the smarter decision. To paraphrase Michael Porter, strategy is what you choose not to do — and this applies to AI as much as it does anything else.
To be clear, I’m not arguing outright against AI, although I would certainly argue against AI as a gimmick or a grift. AI in general, and generative AI in particular, are indeed powerful. They hold a tremendous amount of potential for companies and their customers — when approached with the end in mind.
But looking at AI-enabled toothbrushes and toilets, I have to question whether some of the companies in question understand their own customers well enough to know whether AI will create or crater demand. It seems that the executives in these organizations were so enamored of the idea of “AI” that they didn’t bother to ask, “Why?” — or maybe, didn’t listen hard enough for the answer.
And that brings me back to Geoff’s point about the importance of identifying high-potential use cases. Taking that one step further, with any consumer-facing use case, the focus must be on real value creation, aligning AI’s capabilities with true customer needs and preferences.
AI must enhance, not alienate. It’s not about jumping on the AI bandwagon because it’s trending; it’s about making deliberate, strategic choices that prioritize the customer experience. By understanding when and where AI truly adds value — and when it doesn’t — businesses can foster trust, loyalty, and long-term success. And being smart enough to know that the boldest move may be knowing when to step back and say, “This isn’t the right thing isn’t the right thing, right here, right now.”
So, what do you think? Where’s the line between worthwhile and wrong when it comes to AI in your business? And as a consumer, where’s your personal line in the sand?