努比亚、阶跃、荣耀 谁在定义AI手机？

This article sorts out core details of three AI Agent-enabled smartphones showcased at the 2026 World Artificial Intelligence Conference and outlines the current state of the AI smartphone industry, providing clear guidance for general consumers.

1. The three showcased AI handsets pursue distinctly different development paths: ZTE nubia focuses on the application layer, adopting MCP/A2A protocols to enable native interoperability with mainstream apps instead of relying on simulated click operations; Stepverse pursues a system-level approach, building a native AI agent operating system from scratch; Honor takes a perception-focused route, launching a new handset equipped with a retractable mechanical gimbal that supports perception of the physical world.

2. Four core benchmarks define a qualified AI smartphone: it must understand fused multi-input user intent, execute tasks across apps via standardized protocols, retain and store user personal preferences, and deliver security through on-device encryption and revocable operations. All compliant AI handsets must also complete on-device AI filing with China's Cyberspace Administration of China (CAC).

3. The three new flagship models will launch sequentially in the second half of 2026. General consumers are advised to wait for post-launch market validation before deciding whether to upgrade their devices, rather than rushing to be an early adopter.

Global smartphone shipments have declined for multiple consecutive quarters, and AI Agent phones are widely recognized across the industry as the core new growth driver to upgrade demand. The distinct approaches explored by three brands provide multi-dimensional insights for handset makers.

1. Consumer demand trends are clear: users are no longer satisfied with "pseudo-AI phones" that only add a cloud-based chatbot, and instead want AI agents that can actually complete practical tasks. By 2026, four conditions—on-device models, computing power, regulatory frameworks, and market demand—have all fallen into place, opening the commercialization window for AI Agent phones.

2. The strengths and weaknesses of each development path are clear: the core challenge for the application-layer interoperability approach is negotiating a sustainable benefit-sharing model with internet platforms; the native system-level approach requires time to build out a partner ecosystem; the physical form innovation route must resolve issues related to new component cost, yield, and durability.

3. Compliance requirements are explicit: all brands launching AI phones must complete CAC filing for on-device generative AI services, or face regulatory risks. Brands should complete the filing process in advance. As global players are all rushing to lay out groundwork in this track, early positioning is critical to seize the chance to define the new product category.

AI Agent phones are currently the only major new growth area with significant upside in the smartphone industry, bringing new incremental opportunities for phone sellers, who also need to watch for potential risks and adjust operating strategies accordingly.

1. On the opportunity side: Global smartphone shipments have fallen for multiple straight quarters, and the entire industry needs new selling points to drive upgrades. AI Agent phones are the core priority for all major manufacturers. Counterpoint forecasts that the global penetration rate of generative AI phones will reach 45% in 2026, and as the next evolution of AI phones, AI Agent devices offer a sufficiently large market opportunity.

2. Risk reminder: None of the three development paths have been validated by the market yet. The system-level route has not finished building its ecosystem, the form innovation route faces unstable cost and yield, and the application-layer route has not resolved the ecosystem benefit-sharing issue. Sellers should avoid bulk stocking inventory too early.

3. Operational recommendations: Sellers should focus on three key launch windows in the second half of the year: Honor's new launch in August, Stepverse's new model in October, and nubia's second-generation flagship launch. Adjust stocking strategies based on market feedback for the three products, and prioritize promoting models from brands that have already completed compliance filing.

The rapid development of AI Agent phones has generated new product demand and business opportunities for handset manufacturers and component factories, while also pointing a clear direction for factories pursuing digital transformation.

1. Product design and manufacturing requirements have changed noticeably: AI Agent phones need to run on-device large models, pushing up requirements for chip computing power and battery capacity significantly. Honor's perception-focused approach has also created demand for entirely new components such as the 4-degree-of-freedom titanium alloy mechanical gimbal, raising the bar for component precision, yield, and durability. Hardware is now being purpose-built for AI agents—for example, chips now integrate personal knowledge graph modules.

2. Business opportunities are significant: AI Agent phones are a new track being pursued simultaneously by all global handset makers. Not only domestic Chinese leading brands are advancing the space, but overseas giants including Samsung, Google, and Apple have already laid out groundwork, creating massive new demand for production of new structures and new components. Factories that expand relevant production capacity ahead of time will win more orders.

3. Insights for transformation: New AI phone iterations are moving much faster, raising requirements for production precision and supply chain responsiveness. Factories need to accelerate digital upgrades to adapt to the production requirements of the new category and keep up with the industry's iteration pace.

AI Agent phones are currently at a critical inflection point moving from demo prototypes to mass production, generating a wave of new demand and unmet pain points that create new business opportunities for service providers serving the handset industry.

1. Industry development trends are clear: AI phones have evolved from the early stage of simply adding a cloud chatbot to a new phase of native on-device AI agents. The industry has settled on three distinct development paths: application-layer interoperability, system-level reconstruction, and perception-layer innovation. A full user experience will eventually require integration of all three layers. Regulatory rules explicitly require on-device AI services to complete official filing, with privacy protection as a core requirement.

2. Core customer pain points are prominent: Players on each path face unique challenges: application-layer players need to build a sustainable ecosystem benefit-sharing mechanism; system-level players need to rapidly expand ecosystem partnerships; form innovation players need to resolve new component cost and yield issues. The entire industry also shares the common pain point of low completion rates for cross-app multi-step tasks.

3. Recommended business positioning: Service providers can focus on opportunities including on-device AI model optimization, on-device privacy encryption technology, ecosystem integration services, and technical services for new structure manufacturing. By targeting solutions for the specific pain points of different players, they can capture the new growth brought by industry upgrading.

The rise of AI Agent phones has brought new changes and requirements to internet platforms and handset ecosystem platforms, which need to adjust their strategies to adapt to new trends and mitigate potential risks.

1. The impact of AI phone development on platforms has shifted: Early AI agents that relied on GUI simulated clicks reduced user app open frequency and engagement, cutting into platform advertising revenue, leading most platforms to block this type of access historically. The new protocol-based approach uses native底层 interface calls instead, forcing platforms to rebuild their cooperation models.

2. New cooperation models have already emerged, and leading platforms have shifted their stance: WeChat has partnered with multiple handset makers to launch the A2A protocol, while Alipay has reached a system-level partnership with Stepverse to open up AI interfaces, shifting from a blocking stance to open cooperation.

3. Compliance and operational risks to note: Platforms need to cooperate with regulatory requirements to push for filing of all connected AI services, while exploring a benefit-sharing model with AI handset makers. They need to find a sustainable cooperation model that opens up capabilities while protecting their own commercial interests and user privacy security, to avoid the risk of ecosystem fragmentation.

2026 marks a critical inflection point for AI Agent phone development, with multiple new industry trends and unaddressed emerging problems that offer significant research value for analysts focused on consumer electronics and AI industrialization.

1. Clear new industry trends: Regulators have for the first time introduced a separate filing category for on-device generative AI services on smartphones, paving the way for scaled development of AI Agent phones. In 2026, four conditions—on-device computing power, model capability, regulatory framework, and market demand—have simultaneously been met for the first time, with global vendors all laying out groundwork. The industry has diverged into three fully distinct technology paths: application-layer interoperability, system-level reconstruction, and perception-layer innovation.

2. Prominent unsolved new problems: The industry still faces challenges including low overall success rates for cross-app multi-step tasks, no established benefit-sharing mechanism between handset makers, model providers and internet platforms, long ecosystem build timelines for the system-level route, and long commercial validation cycles for form innovation. No viable business model has been proven yet.

3. Research insights: The regulatory filing system has laid a foundation for standardized industry development, and human-computer interaction is entering a new round of upgrading. A full AI Agent phone experience will ultimately require integration of all three paths. Researchers can track the market performance of the three core new flagship models launching in the second half of 2026 to validate the feasibility of different paths, and study new industry division of labor and business models.