The recent deliberations on constructing a modern industrial system and strengthening the real economy underscore a strategic pivot towards “expanding domestic demand as the strategic foundation.” This focus on building a robust domestic market and accelerating the new development paradigm is not merely a cyclical adjustment but a profound realignment of China’s growth trajectory. The Expand Domestic Demand Strategy serves as a critical engine for economic transformation, driving the shift from old to new growth drivers and fundamentally supporting high-quality development. Its significance is twofold: it activates endogenous market vitality by addressing insufficient aggregate demand while simultaneously stimulating supply-side innovation, and it solidifies the domestic circulation, enhancing its primacy within the dual circulation framework. As the world’s second-largest economy with unparalleled market potential, China’s economic advantage inherently lies in its massive domestic scale. Therefore, steadfastly implementing this strategy is paramount to fostering an economic model led by domestic demand, consumption, and endogenous growth.
Within this strategic context, the embodied AI robot industry, as a pivotal component of future industries, is accelerating from conceptualization to commercial deployment, demonstrating immense potential. Embodied AI represents a new paradigm arising from the convergence of artificial intelligence with other disciplines, providing intelligent systems with a physical, perceptive, and actionable foundation. This enables autonomous exploration, progressive understanding, and influence on the external world through continuous interaction with real environments. Its core feature is the deep integration of perception, cognition, and control systems, allowing physical devices to adapt, learn, and execute tasks in dynamic settings. In recent years, China’s embodied AI robot sector, exemplified by humanoid robots, has achieved leapfrog development, progressing from proof-of-concept to accelerated growth, and now commands a significant share of the global market. Projections suggest the embodied AI market could surpass the trillion-yuan threshold by 2035, highlighting its strategic value and broad application prospects. Consequently, the high-quality development of the embodied AI robot industry is a strategic imperative for securing first-mover advantages in global technological competition.
The Expand Domestic Demand Strategy provides a solid market foundation and strategic underpinning for this development. The powerful domestic market offers not only rich application scenarios and commercial potential but also, through demand-pull, scenario-driven, and industrial linkage mechanisms, continuously propels rapid product iteration, service optimization, and business model innovation. A key to high-quality development for the embodied AI robot industry lies in its agility to adapt to domestic demand shifts, root itself in specific scenario needs, and establish a sustainable commercial feedback loop. Therefore, under the Expand Domestic Demand Strategy, solving the practical challenge of transitioning embodied AI robots from “usable” to “usable, reliable, and affordable” becomes the central mission.
This paper explores the logic for promoting high-quality development of the embodied AI robot industry under this strategy, analyzes the pain points hindering synergistic progress across the technology chain, industrial chain, and value chain, and proposes demand-centric pathways. This inquiry is crucial for implementing the national strategy, proactively planning for future industries, and shaping new competitive advantages in the global technology landscape.
The Logic for High-Quality Development under the Expand Domestic Demand Strategy
The need to expand domestic demand is a strategic response to medium- and long-term challenges, serving as the core support for transforming growth drivers and optimizing economic structure. Within this framework, the high-quality development of the embodied AI robot industry relies on the synergistic evolution of three interlinked chains: the technology chain, the industrial chain, and the value chain.
1. Technology Chain Logic: Demand-Pull for Core Breakthroughs
China’s mega-scale and scenario-rich domestic market drives technological maturation and upstream breakthroughs through a cascading牵引 mechanism from application to R&D.
First, diverse application scenarios are key drivers for technological maturation and cost reduction. The vast market provides extensive and deep scenarios, ranging from households and enterprises to entire industries. This diversity offers invaluable real-world testing grounds for embodied AI robot technologies. The deep, iterative demand within these scenarios provides continuous feedback, which is essential for following the learning curve, reducing technological uncertainty, and ultimately lowering costs for embodied AI robot systems.
Second, high-standard market requirements compel攻坚 in core technologies. As demand shifts from novelty to functionality, stability, and utility, the market imposes a逼 mechanism on the technology chain. This forces R&D focus to shift upstream from integration to攻克 critical areas like high-precision core components, specialized chips for low-power high-compute needs, and intelligent operating systems for complex task autonomy. Historically, demand upgrades in sectors like consumer electronics have successfully driven供应链 advancement; the embodied AI robot industry can leverage similar domestic market拉力 to address “chokepoint” technologies.
Third, the domestic market offers strategic opportunities for原始 innovation and first-mover advantage. In frontier areas like brain-computer interfaces or embodied AGI, the domestic market’s application potential and supportive policy environment can provide initial commercialization validation and sustainable R&D funding cycles. Pioneering场景化 applications domestically can generate cash flows to fund high-risk basic research, reducing over-reliance on external roadmaps. This bidirectional驱动 can help transition China’s embodied AI robot capabilities from “catching up” to “running alongside” and even “leading” in specific domains.
| Market Characteristic | Impact on Technology Chain | Outcome for Embodied AI Robot Development |
|---|---|---|
| Diversity of Scenarios | Provides real-world testing, continuous feedback for iteration. | Accelerates maturation, reduces cost via learning curve effects. |
| High-Standard Requirements | Creates倒逼 mechanism for upstream R&D. | Drives breakthroughs in core components, chips, and OS. |
| Scale for Innovation | Offers validation and funding for frontier research. | Fosters first-mover advantage in niche areas of embodied AI. |
2. Industrial Chain Logic: Building a Resilient and Advanced Ecosystem
A stable, growing, and upgrading domestic demand is the foundation for a secure, resilient, and advanced industrial chain system, shaping its organization, security, and evolution.
First, demand diversity is a source of专业化分工 and ecological prosperity. The heterogeneous demand across structures, geographies, and applications makes it impossible for a single firm to meet all needs with a generic product. This creates space for SMEs to thrive in niche segments, deepening the division of labor. An organic system emerges: upstream “little giants” focus on core components; mid-stream integrators on platform design; downstream providers on industry-specific solutions for embodied AI robots. Supporting services like software platforms and testing also flourish, forming a complete, collaborative, and resilient ecosystem.
Second, the stability of the domestic circulation enhances产业链 control力和安全水平. A domestic demand-oriented supply chain configuration significantly improves resilience against external shocks. Stable domestic demand gives “链主” enterprises the confidence for long-cycle, high-risk R&D in areas like robot OS or new actuators. This helps cultivate globally competitive本土 champions, reducing dependence on external单 suppliers and securing strategic autonomy for the embodied AI robot industry.
Third, deepening application scenarios drive融合 innovation. The integration of embodied AI robots with various sectors spawns new业态 and models—flexible manufacturing,智慧 logistics, surgical robotics. This fusion process反向 defines products, shapes standards, and perfects ecosystems. Solutions and standards validated in China’s large-scale, multi-scenario applications can become a key competitive advantage for the global expansion of the embodied AI robot industry.
3. Value Chain Logic: Migration, Circulation, and Realization of Value
The expansion and upgrading of domestic demand are reshaping value creation and distribution within the embodied AI robot industry, building a more resilient and sustainable循环体系.
First, the value creation重心 is shifting from hardware to systemic solutions and services. As competition moves to solving real problems, the profit model evolves from one-time sales to全生命周期价值管理. The domestic market’s characteristics push value migration along the “smile curve”: upstream to design/algorithms/chips, downstream to integration/subscription/services. This transforms firms from device vendors to智能解决方案 partners.
Second, a virtuous cycle forms between industrial upgrade, high-skill employment, and income growth. The embodied AI robot industry creates high-skill, high-wage jobs (R&D engineers, data scientists). Increased income among these workers boosts demand for high-quality, intelligent products and services, which in turn pulls further industry innovation. This endogenous良性增长闭环 strengthens the micro-foundations of domestic demand.
Third, market integration and new infrastructure协同 enhance value realization efficiency. Building a unified national market by facilitating compliant data flow, standardizing interfaces, and互认 testing systems lowers cross-regional costs for embodied AI robot deployment.协同 deployment of new infrastructure—advanced computing networks, simulation platforms, digital twins—acts as a “highway” for technology iteration, accelerating the path from lab to real-world场景 and shortening the商业价值实现周期.
The synergistic relationship between demand and the three chains can be conceptually represented. The domestic demand (D) drives technological progress (Tech), which enables industrial chain maturity (Ind), leading to value capture (V). This, in turn, fuels further demand through income effects. A simplified feedback model can be expressed as:
$$ \Delta Tech = f(D, Ind_{-1}) $$
$$ \Delta Ind = g(Tech, V_{-1}) $$
$$ \Delta V = h(Ind, D) $$
$$ D_{t} = D_{t-1} + \alpha \cdot V_{t-1} $$
where $\alpha$ represents the marginal propensity to consume from value-added income.
Pain Points in High-Quality Development
While the Expand Domestic Demand Strategy presents significant opportunities, translating this into kinetic energy for the embodied AI robot industry requires overcoming persistent pain points across all three chains.
1. Technology Chain Pain Points
Data Element Bottlenecks: The advancement of embodied AI robot technology critically depends on high-fidelity, multimodal, contextualized datasets. However, data is often trapped in “silos” across different industries and entities, characterized by non-standardized formats and privacy concerns. The high cost and expertise required for精细标注 of complex physical interactions further constrain the development of high-quality training data. The lack of secure and efficient data marketization mechanisms severely limits the scale and compliance of data utilization, slowing algorithmic iteration for embodied AI robots.
Shortage of Specialized Human Capital: As a multidisciplinary field, the embodied AI robot technology chain requires复合型 talent proficient in AI, robotics, control, and场景理解. The supply of such asset-specific human capital lags behind demand due to gaps in interdisciplinary education and industry-academia collaboration. This shortage increases innovation costs and creates bottlenecks, slowing down overall integration and iteration for embodied AI robot systems.
2. Industrial Chain Pain Points
Fragmented Standards and Poor Interoperability: The long and interconnected industrial chain for embodied AI robots suffers from a lack of unified standards for sensors, OS middleware, and communication protocols. Inconsistent软硬件接口 lead to high integration costs and low互操作性, forcing system integrators into costly customization. This “bucket effect” reduces the overall efficiency and speed of iteration for the embodied AI robot industry.
Weak Synergy and Ecosystem Leadership: The industrial ecosystem lacks strong leading enterprises with sufficient system integration capability and platform openness to effectively lead and empower the chain. Concurrently, many innovative SMEs specializing in key components or algorithms face constraints like high R&D costs and narrow market access, hindering their ability to build不可替代性. This dual weakness prevents the formation of a stable, value-co-creating innovation network for embodied AI robots.
| Chain Dimension | Core Pain Points | Manifestation in the Embodied AI Robot Industry |
|---|---|---|
| Technology Chain | 1. Data Silos & Annotation Challenges 2. Specialized Talent Shortage |
Slow algorithm iteration; High R&D costs and bottlenecks. |
| Industrial Chain | 1. Lack of Unified Standards 2. Weak Ecosystem Synergy |
High integration cost, low efficiency; Fragmented innovation network. |
| Value Chain | 1. Immature Profit Models 2. Unbalanced Value Distribution |
Hardware losses, unproven services; Low incentive for upstream innovation. |
3. Value Chain Pain Points
Immature Sustainable Profit Models: A prevalent issue is “hardware sales at a loss, with software/service revenue unable to cover costs.” The high cost of core hardware for embodied AI robots often makes terminal sales unprofitable. Meanwhile, promising post-service models like subscriptions face hurdles such as low product penetration and underdeveloped user payment habits, failing to generate scalable, recurring revenue streams. This breaks the commercial闭环, weakening long-term investment capacity for the embodied AI robot sector.
Unbalanced Value Distribution: Value tends to concentrate excessively with terminal brands or platform companies. Upstream component suppliers and mid-stream integrators often do not receive returns commensurate with their technical贡献 and risk. This imbalance discourages sustained innovation in the mid-upstream, prevents the formation of a true产业创新共同体, and ultimately hampers the overall technological攻坚 of the embodied AI robot industry.
Pathways for High-Quality Development
To address these pain points and harness the potential of the Expand Domestic Demand Strategy, targeted interventions across the three chains are necessary.
1. Technology Chain Pathways
Building a Secure and Efficient Data Supply System: Leveraging the scale of domestic demand, a dual approach on standards and circulation mechanisms is needed.
- Standards & Specifications: Accelerate the establishment of a data standard system for embodied AI robot scenarios, covering classification, collection, labeling, and quality assessment. Industry alliances should develop specifications for multimodal data and tackle challenges in labeling complex interactions.
- Circulation Mechanisms: Explore the construction of trusted data spaces for the embodied AI robot industry. Innovate mechanisms for data use authorization, benefit-sharing, and collaborative governance to enable compliant data flow. Pilot projects on data asset registration and valuation can clarify participation in value distribution, incentivizing data sharing.
Cultivating Specialized Human Capital: An all-encompassing talent support system aligned with industry needs is crucial.
- Education Reform: Encourage universities to establish interdisciplinary programs in embodied AI, combining mechanics, electronics, and AI. Deepen industry-academia collaboration for curriculum development, labs, and scenario-based project modules. Vocational training should be aligned with industry needs for high-skill roles.
- Policy Support: Include core embodied AI robot talent in紧缺人才 catalogs, providing配套 support. Establish industry-recognized competency certification systems. Invest in open-source communities and innovation platforms to foster a collaborative culture.
2. Industrial Chain Pathways
Implementing a “Standards First, Mutual Recognition” Strategy:
- Standardization: Industry associations should lead working groups to develop and promote key interface and communication protocol standards for embodied AI robots, focusing on OS middleware, control buses, and sensor data formats. Encourage de facto standards from leading enterprises.
- Testing & Ecosystem: Establish third-party interoperability testing and certification platforms. Grant marks to compliant components and systems, guiding procurement preferences. Support ecosystem activities like developer contests to foster innovation based on unified standards for embodied AI robots.
Fostering an Integrated Innovation Ecosystem (“Strong Chain, Nurture Chain”):
- Empowering Leaders: Support leading integrators/platforms in forming innovation consortia or open-source communities. They can开源基础软件, share scenario data, and publish technology需求清单 to drive collaborative R&D for embodied AI robots.
- Empowering SMEs: Develop regional public service platforms within industrial clusters to provide SMEs with shared R&D equipment, pilot lines, and testing services. Establish specialized industrial chain investment funds guided by government capital to provide patient capital to “little giants” in core component areas for embodied AI robots.
3. Value Chain Pathways
Forging Sustainable Business Models:
- Cost Optimization: Leverage domestic market scale to promote standardization and platformization of key hardware modules (e.g., robot joints, perception modules) for embodied AI robots, driving down marginal costs through economies of scale.
- Service Innovation: Guide enterprises to shift from hardware sales to integrated solutions encompassing deployment, O&M, and upgrades. Pilot outcome-based service contracts in key sectors like industrial inspection or elderly care, where payment is tied to verifiable performance of the embodied AI robot system.
- Market Cultivation: Launch large-scale demonstration projects in strategic sectors via government procurement, scenario opening, and usage subsidies. Offer phased tax incentives or R&D deductions to firms adopting service subscription models to ease the financial transition.
Establishing Equitable Value Distribution Mechanisms:
- 利益联结机制: Advocate for value distribution frameworks based on technical contribution and risk-sharing. Encourage long-term strategic partnerships between整机厂 and upstream/midstream firms, exploring models like cross-licensing, shared R&D investment, and layered profit-sharing for embodied AI robot development.
- Common Platform Development: Support the construction of open, shared R&D and testing infrastructure (high-fidelity simulators, standard datasets, algorithm libraries) through government-led, industry-academia consortia. This lowers barriers for SMEs and enhances interoperability, gradually shaping a “capability-complementary, risk-dispersed, benefit-shared” embodied AI robot innovation network.
| Targeted Pain Point | Proposed Pathway | Expected Outcome for Embodied AI Robots |
|---|---|---|
| Data Bottlenecks | Create data standards & trusted circulation spaces. | Faster, lower-cost algorithm training and iteration. |
| Talent Shortage | Reform education; Provide policy support for talent. | Steadier pipeline of specialized engineers and scientists. |
| Fragmented Standards | Industry-led standardization & mutual recognition. | Reduced integration cost, faster time-to-market. |
| Weak Ecosystem | Empower leaders & SMEs via platforms and funds. | More resilient, collaborative industrial network. |
| Immature Profit Models | Pilot service-based, outcome-linked contracts. | Sustainable business闭环, enabling long-term R&D. |
| Unbalanced Value Distribution | Establish贡献-based partnership & profit-sharing models. | Stronger incentives for upstream/midstream innovation. |
The successful implementation of these pathways can be modeled as optimizing a system’s output. The goal of high-quality development (HQD) for the embodied AI robot industry is a function of overcoming pain points (P) through targeted pathways (X), within the enabling environment of expanded domestic demand (D).
$$ HQD = \max \left( \beta_T \cdot \frac{Tech(X_T, D)}{P_T} + \beta_I \cdot \frac{Ind(X_I, D)}{P_I} + \beta_V \cdot \frac{V(X_V, D)}{P_V} \right) $$
Subject to: $X_T + X_I + X_V \leq R$ (Resource Constraint)
Where $\beta$ represents the weight of each chain, and $R$ is the total policy/industry resource available for implementing the pathways $X$.
Conclusion
The Expand Domestic Demand Strategy, central to畅通国民经济循环, provides a unique opportunity and a complete market ecosystem for the embodied AI robot industry. China’s vast, multi-layered, and scenario-rich domestic market offers an invaluable “testing ground” and continuous iterative momentum for the technology. This paper has systematically elucidated the driving logic, critical pain points, and potential pathways for high-quality development from the interlinked dimensions of the technology chain, industrial chain, and value chain. It aims to provide a framework for understanding the industry’s development规律 under this strategy and identifying policy focal points.
It is important to note that the deep integration of the embodied AI robot industry with the domestic market is a dynamic process. The analysis, pain point diagnosis, and proposed pathways presented here, based on the current stage of development, require continuous observation, evaluation, and refinement in practice. Future research could conduct more targeted empirical studies drawing on pilot experiences from different regions and scenarios,不断完善 the policy toolkit for embodied AI robot development.
In conclusion, promoting the high-quality development of the embodied AI robot industry under the Expand Domestic Demand Strategy is not only a proactive response to the national strategy but also a critical path for China to forge new competitive advantages in future industries and solidify the foundation of the real economy. This discussion provides a theoretical reference for understanding the interaction between expanding domestic demand and embodied AI robot industry innovation, and offers actionable思路 for policymakers, industry stakeholders, and practitioners navigating this transformative landscape.