AI手机 开始革自己的命

This article summarizes a key new industry development from the 2026 World Artificial Intelligence Conference: the concurrent launch of multiple agent-powered smartphones, marking the official start of the "Year of the Agent Phone." AI phones have finally outgrown the limitations of basic voice assistants and are evolving to deliver truly intelligent experiences. Key takeaways are as follows:

1. Three vendors from different sectors have launched products following distinct development paths: Nubia has partnered with Doubao to release a second-generation AI agent phone that resolves the first-generation model's compatibility issue of being blocked by mainstream apps; StepEngine has built a native底层 operating system fully adapted for AI agents; Honor has launched a robotic phone equipped with a mechanical gimbal that extends interaction into the physical world. Each player brings unique technical strengths.

2. Practical new features already available include: the second-generation Doubao agent can accurately identify user intent, remember user content saved across multiple apps, and support multi-task processing; StepEngine's agent phone can generate PPT files locally; Honor's device can automatically track moving subjects for filming.

3. The industry is still immature, and faces unresolved challenges including ecosystem rivalry, insufficient on-device computing power, and privacy and security risks. General consumers are advised to wait for the sector to mature before upgrading to a new agent phone.

AI phones have now entered a new phase of transformation driven by intelligent agents, bringing new changes to both the industry and consumer markets. Key insights are summarized below:

1. Consumer and industry trends: Users are no longer satisfied with basic AI features such as photo editing and translation. Demand has shifted to full-scenario intelligent experiences that can automatically complete complex tasks. The clear evolutionary direction for the industry is to重构底层 operating systems, shifting the interaction model from "human-operated apps" to "AI agents that complete tasks automatically."

2. Competitive takeaways for brands: There are no unified standards in the emerging agent phone track, and players with different backgrounds all have opportunities to enter the market. Strengths in model capability, system重构, and hardware integration each open up viable competitive paths, and brands can choose a route aligned with their own resources.

3. Core issues to resolve: Brands should avoid the pitfall of bypassing existing app ecosystems, prioritize an open cooperation route, and coordinate profit distribution with app developers in advance. At the same time, players need to overcome the challenges of on-device large model compression and hardware power consumption balancing, and build user trust around privacy to gain market acceptance.

Agent phones represent a new growth track for the mobile phone industry, currently in the early stage of development. Key insights for industry practitioners are summarized below:

1. Market opportunities: Generative AI services for mobile on-device deployment have completed regulatory compliance filing, moving from the concept stage to commercial implementation. Users have clear expectations for upgraded AI phone features, and no dominant player has yet emerged in the track, leaving room for both incumbents and new entrants.

2. Risk warnings: Avoid the pitfall the first-generation Doubao AI phone encountered: attempting to obtain permissions by bypassing the existing app ecosystem will easily trigger collective resistance from top applications. Players should also be alert to privacy and security risks—without reliable security boundaries, it is difficult to earn user trust. Large model companies entering the mobile phone track should also pay close attention to refining product experience.

3. Actionable insights: Vendors can choose a technical route based on their own strengths. Players with model ecosystem advantages can adopt the interface cooperation route, while players with system and hardware advantages can pursue底层 system重构. There is no need to blindly follow a one-size-fits-all solution.

The rise of agent phones has brought new demand and business opportunities to mobile phone manufacturing factories. Key insights are summarized below:

1. Changes in product design and manufacturing requirements: The core competition of AI phones has shifted from parameter comparison to model efficiency and hardware integration capability, raising higher requirements for NPU, CPU, and GPU adaptation. It also brings new challenges in balancing temperature control, battery life, and memory capacity. Some innovative models also require new hardware components such as 4-degree-of-freedom gimbals, creating new demand for hardware design and manufacturing.

2. Business opportunities: Agent phones are currently in an early growth phase, with major vendors all rolling out new product layouts. Demand for new hardware components will continue to rise, and factories with R&D capabilities can lay out production for these new categories in advance to seize first-mover advantages.

3. Implications for digital transformation: Agent phones themselves are a typical case of AI transforming traditional end products. Factories can follow this example, seize the trend of AI-enabled industrial transformation, advance digital and intelligent upgrading of their own production processes, and improve production efficiency.

Agent phones have entered the early stage of development, bringing new trends and opportunities to relevant service providers along the industrial chain. Key insights are summarized below:

1. Industry development trends: The AI industry has shifted from competing on large model parameter counts to deploying AI on end hardware. As the most frequently used intelligent terminal for consumers, smartphones are the core deployment scenario for AI.重构 agent-centric operating systems and building lightweight on-device large models are clear industry development directions.

2. Core pain points for clients: The key challenges facing agent phone vendors currently include insufficient capability for compressed on-device deployment of large models, immature power consumption balancing solutions, the absence of an established profit distribution mechanism with app developers, and a lack of trusted user privacy and security systems.

3. Business opportunities and solution directions: Service providers focused on large model compression, computing power optimization, and privacy-preserving computing will see strong growth in order demand. Ecosystem connection service providers can help agent vendors partner with top app developers, negotiate profit distribution rules, and resolve ecosystem cooperation challenges, creating significant market opportunity.

The growth of agent phones has brought new demand and trends to industry platforms. Key insights are summarized below:

1. Core industry demand for platforms: There are currently no unified industry standards for the agent phone track, with multiple vendors claiming to build the "world's first" product. The industry needs platforms to lead the development of unified standards and standardize product definitions. It also needs platforms to promote the establishment of ecosystem profit distribution rules to resolve disputes over commission allocation and user ownership between agent phone vendors and app developers.

2. Strategic directions for platforms: Platforms can lead the formation of an agent ecosystem alliance, attracting mobile phone vendors, large model developers, and app developers to join, promote the adoption of open interfaces such as A2A and MCP, and negotiate the development of general profit distribution rules. Platforms can also launch investment and support policies for new large model developers and new mobile phone brands to attract new players to join the ecosystem.

3. Risks to avoid: Platforms need to balance the interests of different players across the ecosystem to avoid collective resistance from top applications. They should also promote the establishment of unified industry standards for privacy and security to reduce user trust risks and support the healthy development of the industry.

This article discloses the latest industry developments in the AI phone field and puts forward a number of new research questions. Key insights are summarized below:

1. Latest industry developments: The core highlight of the 2026 World Artificial Intelligence Conference has shifted from large models to AI hardware deployment, with agent phones emerging as the core track. Three vendors with different backgrounds have launched three differentiated technology routes: the open interface cooperation model, the native底层 operation model, and the hardware + system-level reconstruction model. All routes point to the direction of operating system重构, and on-device large models have already completed regulatory filing and entered the compliant implementation phase.

2. New research questions to explore: These include the profit distribution mechanism of the agent phone ecosystem, compression and optimization technologies for on-device large models, hardware power consumption balancing solutions, the establishment of privacy and security boundaries for cross-app operations, the paid business model for agent phones, and consumer acceptance of token-based pricing that remains to be tested.

3. Frontier research directions: Future intelligent terminals may not take the form of traditional mobile phones. Research is needed on the evolution of terminal form with agents serving as human proxies. It is already clear that core competitiveness lies in large model capability and on-device deployment capability, and this field leaves significant room for further research.