If you've noticed more software companies suddenly announcing earbuds, wearables, or mysterious AI gadgets, you're not imagining a trend. Companies that spent years insisting they were "platforms, not products" are now designing physical devices, and it's happening across the industry at once. This isn't a random coincidence – it's a fairly logical response to a few pressures that have been building for years.
The pattern shows up in a few distinct ways. Meta has continued pushing its Ray-Ban smart glasses line, treating hardware as a serious long-term bet rather than a side project. OpenAI has been working with former Apple design lead Jony Ive on a dedicated AI hardware device, signaling that even a company built entirely on software and APIs sees value in owning a physical form factor. Amazon and Google have long straddled this line with Echo devices and Pixel phones, but the pace and ambition of new entrants has clearly picked up. Even smaller players, like Humane with its AI Pin and Rabbit with its R1 device, tried to stake claims in this space, showing that the appetite for AI-native hardware extends well beyond the biggest names.
None of this means every software company is rushing to build gadgets. Plenty of major players, including Anthropic, have stayed intentionally focused on software and infrastructure rather than consumer devices. But enough companies are moving in the hardware direction that it's worth understanding what's actually driving the shift, rather than treating it as an isolated headline.
For years, software companies could reach users through existing devices – phones, browsers, operating systems built by someone else. But that arrangement comes with a cost: platform owners like Apple and Google control the rules of access, take a cut of revenue through app store fees, and can change those rules at any time. Building your own hardware sidesteps this dependency entirely, giving a company direct control over how users experience its product without a gatekeeper in between.
This matters more now specifically because of AI. A chatbot or assistant embedded inside someone else's phone operating system is constrained by that system's permissions, background processing limits, and design conventions. A company that owns its own hardware can build an experience specifically shaped around how an AI product should work – always listening in a designed way, integrated with sensors, optimized for a specific interaction style – rather than working around constraints set by a rival platform.
A lot of the current hardware push is tied to a genuine belief that the next phase of AI products won't feel like today's apps at all. Chat interfaces on a phone screen are useful, but they're still bound by the phone's existing interaction model – tapping, typing, glancing at a screen. Companies betting on wearables, glasses, or standalone AI devices are effectively betting that the next meaningful AI interface will look and feel different from a smartphone app, and that owning the hardware is the only way to fully realize that different interaction model.
This is a real, testable hypothesis, not a guaranteed outcome. Some of the earliest attempts at this, including Humane's AI Pin, faced significant criticism over battery life, functionality, and price relative to what a smartphone already does, which is a useful reminder that wanting AI to feel different doesn't automatically mean a new device format will succeed. Hardware is a genuinely difficult, capital-intensive business, and plenty of ambitious devices in tech history have failed to find a market despite strong underlying software.
Software subscriptions are relatively easy for users to cancel, especially when multiple competitors offer similar features. A physical device changes that dynamic considerably – once someone has purchased and set up a piece of hardware, switching away involves more friction than canceling a subscription, and the hardware itself can become the anchor for a broader software and services relationship. This is part of why companies like Amazon have long sold hardware at thin margins or even at a loss, treating the device as an entry point into a longer-term software and services relationship rather than a standalone profit center.
For AI companies specifically, hardware also creates a natural way to collect the kind of continuous, real-world usage data that improves models over time, though this raises its own set of privacy questions that companies are still working through publicly and through regulation.
For someone using these products, this shift mostly shows up as more choice, along with more decisions to make. Instead of one AI assistant living inside your existing phone, you may increasingly face options between a phone-based assistant, a wearable device, and eventually other form factors entirely, each with different capabilities, prices, and privacy tradeoffs. This can feel exciting for early adopters who want to try new interaction models, but it can also feel like fragmentation for people who'd rather have one consistent AI experience across their devices.
It's also worth watching how this affects pricing and business models more broadly. Hardware requires upfront costs that pure software doesn't, which may mean some AI-native devices carry higher price tags or require ongoing subscriptions to unlock full functionality, similar to how some current wearables already operate.
This trend doesn't mean traditional smartphones are going away anytime soon, nor does it mean every software company will eventually build hardware. Plenty of successful AI and software businesses will likely continue operating purely through existing platforms, and building hardware remains a genuinely risky, expensive bet that not every company is positioned to make well. The companies pursuing this path tend to have either significant capital reserves, existing hardware expertise, or a specific belief that their product genuinely needs a new physical form to work as intended.
It's too early to say definitively which of these hardware bets will pay off, and it's worth treating early product launches and rumored devices with reasonable skepticism rather than assuming success is guaranteed. What does seem clear is that the current wave of AI-driven hardware experimentation reflects real strategic reasoning – around distribution control, interaction design, and business model durability – rather than companies simply chasing a trend for its own sake. Whether users actually want a device beyond their phone for AI interactions is still very much an open question the market hasn't fully answered yet.
Is this just about AI, or is it a broader hardware trend? AI is the biggest driver of the current wave, but companies have moved into hardware for platform-control reasons for years before AI became central to the conversation, including with smart speakers and wearables.
Do software companies make money on hardware directly? Not always – many treat hardware as a lower-margin entry point that supports a broader software and subscription relationship, rather than expecting the device itself to be highly profitable.
Are these new AI devices meant to replace smartphones? Most current products position themselves as companions to smartphones rather than replacements, though some companies have expressed longer-term ambitions toward reducing phone dependency.
Why did some early AI hardware devices struggle? Devices like the Humane AI Pin faced criticism over battery limitations, unclear value compared to existing smartphone capabilities, and pricing that made the tradeoff harder to justify for most consumers.
