OpenAI Wants to Design How You Live With AI

OpenAI is best known for ChatGPT, a tool people type prompts into. Now, the company wants to control what you type into and talk to, touch, carry, or even wear.

In May, OpenAI agreed to acquire Jony Ive’s AI hardware startup, IO, for $6.5 billion in stock. About 55 engineers and designers, many of them former Apple employees, are joining OpenAI. Ive’s design firm, LoveFrom, will remain independent but oversee the development of OpenAI’s first hardware products.

The deal signals a shift in OpenAI’s strategy: from backend software provider to full-stack AI experience company. After all, when you own the platform, you own the experience.

The deal also raises a lot of questions. What kind of devices is OpenAI planning to build? Why take the risk of jumping into hardware now? And what happens when an AI company starts thinking like a platform? Here’s what’s happening and what it means.

From AI Engine to AI Ecosystem

So far, OpenAI has played the role of infrastructure. Its models power Microsoft Copilot, support third-party developers via API, and run inside apps and web browsers. But many of the platforms where users access these tools, such as Microsoft’s ecosystem, Apple’s devices, and browsers like Google Chrome, are controlled by others. OpenAI builds the intelligence, but the environment around that intelligence often belongs to someone else.

This acquisition is about changing that. By owning hardware, OpenAI gains control over the entire interaction flow. It no longer has to embed itself into someone else’s interface. It can design the experience end-to-end. That’s the opportunity. OpenAI wants to build a new kind of device, one built from the ground up around AI. Not a phone with a chatbot app; something entirely reimagined for a world where AI is the starting point, not the add-on.

The Potential Upside: Experience, Data, and Revenue

The first benefit is experience. Hardware gives OpenAI the freedom to define how AI behaves in context. That includes voice-first interactions, gesture-based controls, or ambient computing features that go beyond screens and keyboards. OpenAI can dictate how fast the model responds, what kind of interface wraps around it, and how personal or persistent the agent becomes.

Second is data. When OpenAI owns the device, it gets first-party access to behavioral signals that are hard to gather otherwise: tone, timing, follow-ups, and habits across multiple sessions. This kind of data is crucial for training models that are more adaptive, nuanced, and personalized.

Third is monetization. Today, OpenAI makes money through enterprise APIs and ChatGPT Plus subscriptions. A device opens the door to more: premium services, AI-powered apps, and perhaps even a new kind of app store centered around autonomous agents.

So yes, this is about the product. But it’s also about the pipeline and business model.

The Risks: Hardware Is a High-Stakes Game

Despite all that upside, there’s a reason most software companies don’t make devices. Hardware is expensive, slow to develop, and hard to scale. The margins are lower. The logistics are messier. The failure rate is high. Amazon’s Fire Phone failed. Meta is still searching for a hit outside of Quest.

OpenAI has no experience in this space. Building hardware at scale means navigating supply chains, customer support, and firmware issues, which are not exactly adjacent to prompt engineering. Then there’s the reputational risk. A botched launch could damage OpenAI’s brand. A successful launch that mishandles user data could spark regulatory scrutiny or backlash from consumers. So this is not a low-risk play. It’s a calculated leap into an entirely new domain.

The Role of Design: Framing the Future of AI

One reason OpenAI may be ready to make the leap into hardware is the design leadership it’s gaining. Jony Ive and his team are known for making beautiful products, and they’re known for making technology disappear. Their work on the iPhone and Apple Watch was about designing interactions so natural that they reshaped behavior at scale.

That matters. Because today’s AI still feels like software: modal, reactive, and often awkward. You prompt it, it responds. It’s powerful, but it lacks flow. A well-designed AI device can reimagine that dynamic by reducing friction. The aim is not to make AI visible, but livable.

This is where product design and user experience design come together. It’s about how it works when you use it. Good design creates affordances, or subtle cues that help you understand what you can do with a device. A button invites you to press it. A light pulse signals that the system is listening. A slight vibration lets you know it heard you.

These are the building blocks of intuitive interaction. They shape whether an AI feels like a helpful companion or a frustrating interface. If OpenAI gets these signals right, its devices could make working with AI feel seamless and natural. If it gets them wrong, the tech will feel awkward, no matter how smart the model inside may be.

OpenAI’s bet is that the next leap forward won’t come from model architecture alone. It will come from creating the right frame (physically, visually, and behaviorally) so that AI can become part of everyday life without demanding attention. That requires deep knowledge of gesture, motion, feedback, and rhythm. It requires understanding how users move, hesitate, and decide.

The Data Question: More Than a Side Effect

Of course, any discussion of AI must factor in the privacy angle. When OpenAI builds its own device, it won’t just learn more about how people use AI. It will have more permission to learn. That changes the rules.

Training large models is becoming more difficult as data restrictions tighten. Publishers are pushing back on scraping. Courts are weighing copyright concerns. Regulators are stepping in. A first-party device sidesteps a lot of that. It lets OpenAI build its own dataset through user consent, in controlled environments, with higher-quality signals. This could give the company an edge in training next-generation models.

But it also puts pressure on OpenAI to handle that data responsibly. Any perception of overreach, or even indifference, could trigger serious blowback. Transparency, control, and opt-in defaults will be essential.

Why Now? And What Comes Next?

So why make this move now? The short answer is timing. AI is entering a new phase. The hype has matured into a platform race. Google is shipping AI search and assistants. Apple is baking GenAI into iOS. Meta is seeding Llama across its ecosystem. Everyone is racing to own the interface.

OpenAI has arguably the strongest AI core. But it doesn’t own a platform. This deal aims to change that. With Ive’s team on board, OpenAI has a chance to create the first consumer device that is truly AI-native, not adapted. The first product is expected to ship in 2026.

The Big Picture

This deal is about where AI goes from here. It’s a signal that OpenAI sees design, experience, and trust as just as important as model performance. That AI’s next frontier will be about context, as well as capability.

The company is betting that the future of AI will live in the object you carry, the voice you speak to, and the moment you reach for help. And it wants to be the one who built that moment.

Will it work? It’s too soon to tell. But the logic is clear. If the future of AI lies in daily, personal interaction, OpenAI wants to design that future. And now, for the first time, it has the team and the vision to try.