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Reading: Why Apple Might Put Cameras Into Its Next AirPods
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Online Tech Guru > News > Why Apple Might Put Cameras Into Its Next AirPods
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Why Apple Might Put Cameras Into Its Next AirPods

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Last updated: 5 June 2026 13:41
By News Room 5 Min Read
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Why Apple Might Put Cameras Into Its Next AirPods
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If you were to ding Apple’s privacy credentials in one move, you could do worse than to launch AirPods with cameras. Whether or not they come to market, all of Apple’s existing ubiquitous earbuds would become a question mark for everyone in their vicinity: Are they recording me right now?

According to Bloomberg’s well-sourced Mark Gurman, Apple has designed camera-equipped AirPods to allow Siri “to see” the wearer’s surroundings. They’re in the late stages of testing with Apple employees as part of an “AI device push.”

However, a source who asked to remain anonymous because they are not authorized to speak publicly about the matter tells WIRED that Apple will likely delay the camera AirPods. While the hardware is ready, Siri’s visual intelligence is not up to par. Apple executives are also worried that the company is introducing a significant privacy risk with earbuds’ cameras without compelling use cases. Apple did not immediately respond to WIRED’s request for comment.

That brings us to the main question: What advantages would Apple be seeking by adding cameras to its AirPods—especially at a time when consumers’ privacy concerns about casual surveillance through smart glasses’ cameras, doorbell cams, and even phone cameras are on the rise?

Navigation, Shopping, and a Smarter Siri

According to Bloomberg, these AirPods have larger stems to house low-resolution cameras—they act as Siri’s eyes as visual context for spoken requests. They’re not built to capture photos and video, like smart glasses. A few use cases mentioned in the report include landmark-based navigation and identifying foods to help with grocery shopping.

“Vision-based location is the most obvious one,” says Anshel Sag, principal analyst at Moor Insights & Strategy. “It’s got to be a very passive kind of experience, and that’s why I think using it for location-based accuracy, to rectify GPS, makes sense.” Google is also using cameras in its upcoming smart glasses to understand a user’s bearings when using walking navigation with Google Maps.

Other potential features will be familiar to anyone up to date on smart glasses. Peter Richardson, vice president at Counterpoint Research, likes the idea of standing in front of the fridge and asking the AI assistant what to make for dinner, as an example in which data from multiple devices could work together.

“That’s something that requires visual information,” Richardson says. “There’s lots of context: Is it the middle of the week? Have I got training in the morning? Is it a Friday when maybe I like to have a glass of wine? Are my friends over?” Similarly, combined with the Apple Watch, visual data could make Siri more intuitive. “If I’m in Paddington Station and I’m running, maybe I’m late for a train, so maybe don’t send a call to me,” he says.

As with many niche wearables, there are also some interesting accessibility applications. 9to5mac suggests that an all-seeing Siri via AirPods, perhaps with infrared capabilities in the mix, could enhance the capabilities of Apple’s Image Explorer and Voice Over features for visually impaired users. In all these scenarios, a key piece of information that we still don’t have is whether the cameras would be forward-facing or world-facing. Gurman indicates that a “small LED light” will turn on when visual data is being fed into the cloud.

Visual Data for AI

At first glance, the reasoning here might be obvious: a real-world data grab. As Big Tech AI model makers and enterprising startups push further beyond text-based large language models, into imaging, mapping, and robotics, Apple’s popular, affordable accessory could be transformed into the 2026 equivalent of Google’s StreetView cars.

“Getting information in, visual or even acoustic, that’s new information that’s never really been used to train AI,” Richardson says. “But it’s only useful if it can then be used to train it.”

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