The tech landscape in February 2026 is witnessing a profound shift in how users interact with artificial intelligence. We are moving beyond the era of 'AI as an app' and into an era where AI defines the hardware itself. However, this transition has sparked a significant ideological and technical conflict: the preservation of open-source ecosystems versus the rise of vertically integrated, AI-first proprietary hardware.
Overview: The Battle for the Interface
According to recent reports, two major movements are currently shaping the future of mobile and home computing. On one side, the 'Keep Android Open' campaign is sounding the alarm regarding Google's increasing control over the Android ecosystem. As reported by F-Droid, there is a growing concern that the 'open' nature of Android is being hollowed out by proprietary AI components that are not part of the Android Open Source Project (AOSP).
Simultaneously, OpenAI is reportedly preparing to bypass existing mobile OS constraints altogether. According to The Verge, OpenAI is developing its first dedicated ChatGPT hardware—a smart speaker equipped with a camera, potentially followed by AI glasses and a smart lamp. This marks a strategic pivot for OpenAI, moving from being a service provider on other platforms to owning the physical interface.
Technical Details: From AOSP to Agentic Hardware
For engineers, the technical divergence between these two paths is critical. The 'Keep Android Open' movement highlights a shift where core system functionalities are increasingly tied to proprietary Google APIs, making it difficult for de-Googled versions of Android to offer a competitive user experience. This reflects a broader trend we discussed in AIエージェント時代のソフトウェア開発：エンジニアは「コードを書く人」から「AIを指揮する人」へ, where the operating system is evolving into an 'Agentic OS'.
OpenAI’s hardware project, internally known as 'Project A,' represents a different technical challenge. Unlike traditional smart speakers that rely on keyword triggers and cloud processing for simple tasks, OpenAI’s device is expected to leverage multimodal capabilities (vision + voice) natively. This necessitates:
- Low-latency Multimodal Inference: Integrating camera feeds with LLMs requires significant on-device processing or highly optimized edge-cloud pipelines.
- Vision-Language Models (VLM) at the Core: The camera isn't just for video calls; it's the primary sensor for the AI to perceive the user's environment in real-time.
- Hardware-Software Co-design: By building their own hardware, OpenAI can optimize the NPU (Neural Processing Unit) specifically for their 'Reasoning' models, similar to the trends identified in our analysis of the クラウド依存からの脱却：『ローカル実行』と『専用ハード』が加速させるAI実装のパラダイムシフト.
Engineering Insights
Positive: Opportunities for Innovation
From a development standpoint, OpenAI’s entry into hardware could break the 'app sandbox' limitations that currently hinder AI agents on iOS and Android. A dedicated device allows for 'always-on' ambient computing without the battery and permission constraints of a general-purpose smartphone. For developers, this could open up a new SDK for 'Spatial AI' interactions that don't rely on a screen.
Negative/Concerns: The Risk of Total Lock-in
However, the engineering community must remain critical. The 'Keep Android Open' movement is right to worry about vendor lock-in. If AI becomes the primary way we interact with technology, and that AI is tied to a specific hardware stack (like OpenAI’s speaker or Google’s proprietary Gemini-Android layer), the spirit of interoperability dies.
Furthermore, the security implications are massive. As we noted in our piece on AIコーディングエージェントに潜むリスク：プロンプト注入攻撃の脅威とミス発生時の責任の所在, adding a camera to an 'always-listening' AI device introduces unprecedented privacy risks and potential for 'Physical Prompt Injection' where visual cues could manipulate the AI’s behavior.
Conclusion
The year 2026 is proving to be a watershed moment for the 'Open vs. Closed' debate. While OpenAI’s hardware promises a frictionless, multimodal future, it threatens to further centralize power within a single proprietary stack. Meanwhile, the struggle to keep Android open represents the last line of defense for a customizable, transparent mobile ecosystem. As engineers, our role is to advocate for open standards and local execution capabilities, ensuring that the next generation of AI hardware remains a tool for empowerment rather than a black box of surveillance.