Generative AI is everywhere. That is, until you ask consumers if they’re using it. A deeper, more surprising disconnect is emerging between corporate adoption and consumer engagement: while 95% of U.S. and European companies are actively implementing GenAI in their operations, only 35% of consumers report using it, at least, according to a Bain & Company’s December 2024 survey.
This disconnect raises some real issues. Do companies truly understand who their GenAI users really are, how they behave, and what they actually want? Are businesses overestimating the digital readiness of their customers? Are they designing tools for a consumer that doesn’t exist? And—most importantly— is AI itself out of touch? Has it been designed and marketed in ways that make sense to engineers and executives, but miss the mark for everyone else?
Decoding the AI consumer
Beneath the surface of all the GenAI buzz, a fragmented reality is playing out: some people are building workflows powered by ChatGPT, Grok, and Gemini, others are experimenting sporadically, and many have stepped away, or never stepped in at all.
For those who have embraced generative AI, usage is intensifying. These active adopters often cite productivity, research, and creative assistance—particularly writing—as their go-to use cases. Some turn to AI to help navigate daily challenges, while others are in it for experimentation or even play. Just imagine: on one end, people streamlining schedules and automating emails; on the other, they’re asking AI to craft bedtime stories or remix Shakespearean sonnets into rap anthems.
As with every major tech shift, early adopters are laying the groundwork for broader usage. One interesting trend: Bain found a notable overlap between AI enthusiasts and users of wearable AI devices—glasses, rings, and pendants that integrate AI assistants into daily life. And their numbers are surging; although just 5% of U.S. adults reported using AI wearables in late 2024, that segment could rise to 20% by the end of 2025, suggesting a growing comfort with ever-present, hands-free AI support.
But not everyone is jumping in.
Skepticism remains a dominant theme among non-users. The top two reasons for not using GenAI? Lack of trust and a strong preference for handling tasks without digital help. Among these more hesitant consumers, many simply haven’t tried it—often due to unfamiliarity, confusion, or discomfort with the idea. Others are “lapsed users” who gave it a go, only to eventually walk away.
Their reasons vary. For some, the appeal simply faded. It didn’t hold enough long-term value to stick. For others, the concerns were more specific: privacy risks, data-sharing concerns, or a sense that AI-generated content just didn’t meet their standards. According to Bain, around 18% of non-users had tried GenAI at some point but chose to disengage, proof that trial doesn’t always lead to conversion.
This behavioral fragmentation is where adoption truly gets complicated: some users are scaling up, others are scaling back, and a majority are still hovering at the edges. Curious, skeptical, or simply unmoved.
Lost in AI translation
Despite the growing integration of AI in retail, many consumers remain unaware of their interactions with these technologies. For instance, a Gallup-Telescope survey conducted in late 2024 revealed that nearly all Americans use AI-enabled products, yet nearly two-thirds (64%) were unaware of doing so.
This lack of awareness presents both a challenge and an opportunity for retailers. On one hand, it highlights a gap between the deployment of AI technologies and consumer recognition. On the other hand, it underscores the potential for businesses to enhance transparency and educate consumers about AI integrations, fostering trust and encouraging more conscious engagement.
At the same time, consumer interest in AI-driven shopping experiences is on the rise. A 2024 global study from the IBM Institute for Business Value indicated that 80% of consumers are eager to use AI enhancements like virtual assistants and AI apps as they shop.
To bridge this divide, retailers should prioritize transparency in their AI implementations. Clearly communicating when and how AI is used in the shopping experience can demystify the technology for even the most skeptical consumers. Additionally, providing options for shoppers to opt in or out of AI-driven features can empower them to make informed choices about their shopping experiences.
Why does this matter?
Consumers can’t trust what they don’t understand, and they won’t embrace what they don’t know is there. Making AI visible, approachable, and optional puts brands in a better position to earn loyalty, close the trust disconnect, and meet the growing demand for smarter, more personalized retail experiences.
The trust problem
Trust remains one of the most critical—and fragile—elements in the relationship between consumers and AI. While many people welcome the efficiency and personalization that Generative AI can offer, concerns about privacy, bias, and misuse still run deep.
Ethical challenges around generative AI often arise not from bad intentions, but from systems that are difficult to audit and explain. When consumers don’t understand how decisions are made, or when systems appear opaque or unaccountable, trust erodes fast.
Building that kind of trust doesn’t happen with fine print or passive disclaimers. It requires visible, intentional design choices that signal to users: this technology is working for you and not around you.
Or, as Satya Nadella, the CEO of Microsoft put it at the company’s AI Tour London event in 2024: “If you don’t trust it, you’re not going to use it.”
Rethinking AI strategy for real people
Retailers eager to integrate GenAI into their products and experiences often focus on scale, speed, and technical sophistication. But as consumer engagement patterns show, adoption isn’t uniform, and neither should strategy.
- Make advanced tools feel intuitive
Power users want smart features that can help them do more, faster, but the interface still needs to feel human. Invest in clean design, customizable outputs, and built-in learning curves.
- Build trust
Consumers wary of AI need visible guardrails. Show how their data is used, give them choices, and explain how the system works in plain language.
- Demystify the product
AI doesn’t need to be explained in code or math. It needs to be contextualized. Use storytelling, onboarding flows, and relatable examples to frame the benefit of AI tools in everyday terms.
- Let users choose when to use it
Auto-enabling AI features can alienate people who aren’t ready or don’t understand them. Give users the option to turn AI on when it feels right for them.
- Solve problems people actually have
Focus on utility before novelty. Think: “Did this save time, reduce effort, or create clarity?”
Ultimately, GenAI is a tool. And should be designed, deployed, and trusted as such. Its success hinges not just on its capabilities, but on whether real people see it as worth using, again and again.
Closing the distance
The landscape of AI consumer engagement is complex and constantly shifting. What works for one segment may alienate another. But that complexity isn’t a barrier. In fact, it’s an opportunity.
By recognizing and addressing the distinct needs, expectations, and anxieties of different consumer groups, businesses can build stronger, more loyal relationships. GenAI won’t succeed on technical capability alone. It will succeed when it meets real human needs, in ways that feel transparent, empowering, and valuable.
