About one in three U.S. adults want nothing to do with artificial intelligence on their personal devices, and the reason most of them give is disarmingly straightforward: they simply do not need it. That finding, drawn from market analyst Circana’s Connected Intelligence research, lands at a moment when every major tech company is racing to embed AI into phones, laptops, and smart speakers. The gap between what the industry is selling and what consumers say they want has rarely been this wide.
They Know About AI. They Just Don’t Want It.
Circana’s research, based on a survey of U.S. adults aged 18 and older, found that 86% of respondents are aware of AI features being built into consumer electronics. Awareness is not the problem. Despite that high recognition, 35% of respondents said they are not interested in having AI in their devices at all. This is not a knowledge gap that better marketing can fix. People understand what is being offered and are actively declining, even as tech firms pitch AI as the inevitable next step for everything from messaging to photography.
Among those who reject device-based AI, nearly two-thirds pointed to a single explanation: they do not need it. That answer topped the list by a comfortable margin, ahead of privacy fears and cost worries. Circana analyst Sara Rosenman framed the dynamic bluntly, describing AI as a “nice-to-have” feature rather than a core purchase driver for most consumers. The phrase captures something the tech sector has been slow to absorb: features that feel optional do not move buying decisions, especially when they are bundled into already expensive products.
Privacy and Cost Fears Compound the Problem
Perceived irrelevance is the leading objection, but it is not the only one. Among AI detractors in the Circana study, 59% cited privacy concerns, and 43% worried about potential cost increases tied to AI-enabled hardware. Those numbers suggest a layered resistance. Even consumers who might see some utility in AI features hesitate when they suspect their data is being harvested or that they will pay a premium for capabilities they did not ask for. Coverage of the findings in specialist tech media underscored that many people see AI as something being done to them, not for them, and they are responding by opting out where they can.
The cost question deserves closer scrutiny. Device makers have been positioning AI as a reason to upgrade, but survey work by CNET and YouGov found that only a small minority of U.S. smartphone buyers point to AI as a key factor in their most recent purchase, while roughly half say they are unwilling to pay extra for AI capabilities. About three in ten respondents told CNET that AI is not helpful and they do not want more of it on their phones, mirroring Circana’s findings. When the upgrade cycle for a flagship smartphone already runs well above $1,000, asking consumers to pay even more for tools they view as unnecessary is a hard sell, and it risks stretching upgrade cycles further as people hold onto older devices that feel “good enough.”
Broader Public Mood Tilts Toward Skepticism
Circana’s findings fit into a wider pattern of public wariness. Pew Research Center polling indicates that the U.S. public is far more concerned than excited about increased AI use in daily life, with majorities saying they want more control over how the technology is deployed around them. That sentiment cuts across demographics and is not limited to people who lack technical literacy. Even AI experts surveyed by Pew expressed support for giving individuals greater agency over how AI touches their routines, suggesting that skepticism is not simply a product of misunderstanding.
Research from Harvard Business School offers a theoretical lens for why this resistance runs so deep, arguing that the success of AI depends not only on technical capability but on people’s willingness to adopt it. Many consumers view AI as opaque or threatening, associating it with job displacement, surveillance, or loss of control rather than convenience. When the most common response to a new feature is “I don’t need this,” the barrier is not ignorance; it is a rational cost-benefit calculation that the industry has failed to tip in its favor. Until companies can clearly show how AI solves real problems without eroding privacy or autonomy, hesitancy is likely to persist.
Tech Companies Are Building for a Market That Isn’t Buying
The disconnect between corporate AI investment and consumer appetite has real commercial consequences. Apple, arguably the most influential consumer electronics company in the world, has already stumbled. The company confirmed a delay to its upgraded assistant, pushing back a flagship AI feature that had been heavily promoted. A deeper look at the internal challenges behind Apple’s efforts revealed significant development setbacks, from technical limitations to organizational friction. If even Apple, with its enormous install base and brand loyalty, cannot smoothly deliver AI tools that consumers feel compelled to use, smaller players face an even steeper climb as they try to differentiate their products with similar capabilities.
The conventional industry assumption has been that once AI features reach a certain quality threshold, adoption will follow naturally. Circana’s Connected Intelligence work challenges that premise. The firm’s Evolving Ecosystem analysis tracks U.S. device ownership and perceptions of emerging technologies, and its findings point to a market where awareness is high but enthusiasm is flat. Consumers are not clamoring for AI on their devices; they are tolerating it when it comes bundled with other improvements they actually care about, like battery life or camera quality. That dynamic undercuts the idea that AI alone can drive the next wave of hardware upgrades.
Rethinking What “Need” Looks Like for Everyday Users
For companies betting heavily on AI, the message in the data is not simply that people are afraid of the technology. Many are indifferent, and indifference is a harder obstacle to overcome than fear. To change that, device makers will have to reframe AI from an abstract capability into something that solves specific, everyday problems. That could mean focusing on quietly useful features (like better spam filtering, accessibility tools, or more reliable voice controls) rather than splashy demos that feel disconnected from routine use. It also means being transparent about what data is collected and how models run, whether on-device or in the cloud, and giving users more granular choices about what is enabled by default.
Circana itself, which positions its market intelligence services around understanding real-world consumer behavior, is effectively warning the industry that demand cannot be willed into existence. The same research discipline that helps brands decide which products to stock on shelves is now signaling that AI is, at best, an add-on for many buyers. Even as firms expand their analytics and field operations, Circana’s own recruiting for data-collection roles shows how much effort goes into tracking shopper habits, the core takeaway remains stubborn: a substantial share of the public does not see a gap in their daily lives that AI on their devices needs to fill. Unless tech companies start from that reality, rather than from their own enthusiasm, they risk building ever more sophisticated features for a market that is content to leave them switched off.
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*This article was researched with the help of AI, with human editors creating the final content.
