Xia Jiechang and Wang Wenji: Projections for the Integrated Development of Artificial Intelligence and Consumption During the "15th Five-Year Plan" Period
While strengthening traditional consumption momentum, stimulating new types of consumption through technological transformation and institutional innovation is becoming the key to accelerating the release of internal demand potential. At a symposium for non-Party personages on July 23, General Secretary Xi Jinping proposed a series of important requirements, including "vigorously stimulating consumption." On August 21, the State Council issued the Opinions on Deeply Implementing the "AI Plus" Action, providing a systematic deployment for improving the quality of consumption through "AI Plus." Looking toward the 15th Five-Year Plan [1] period, "AI Plus consumption" will reconstruct supply-demand relationships and optimize resource allocation. By reshaping consumer behavioral patterns and value identification, it will become a pivotal force leading the deep transformation of consumption modes, propelling the consumption system toward a new stage marked by digitalization, intelligence, and personalization.
1. Phased Characteristics of "AI Plus Consumption"
As of December 2024, the scale of generative AI product users in China has reached 249 million. Application scenarios continue to expand, making AI a vital support for leveraging a new round of consumption upgrading. Correspondingly, from the General Office of the CPC Central Committee and the General Office of the State Council issuing the Special Action Plan for Stimulating Consumption in March 2025 to the release of the Digital China Construction 2025 Action Plan in May, the national level has continuously released policy signals to promote "AI Plus consumption." Facing the 15th Five-Year Plan, relying on China’s ultra-large-scale market advantage and its foundation of rich consumption scenarios, "AI Plus consumption" is expected to transition from a technology-driven phase to an ecological integration phase, serving as a strategic lever to release internal demand potential and lead consumption transformation.
From the perspective of technological evolution, large models are driving "AI Plus consumption" toward an ecological and systematic approach. In the coming years, the compound growth rate of the AI large model market will reach 40%, and AI development will enter a new stage characterized by general-purpose utility, platformization, and ecosystem building. Regarding underlying technology, computing hardware continues to evolve toward high efficiency and low energy consumption, while data resource quality and processing capabilities improve simultaneously. In terms of integrated applications, AI is deeply merging with transportation, healthcare, finance, education, and government affairs, driving the intelligent systemic reconstruction of various social industries. This trend not only expands the boundaries of technical application but also provides a solid foundation for the multi-dimensional synergy and functional integration of consumption scenarios. In the consumption sphere, "AI Plus consumption" is shifting from empowering localized scenarios to penetrating the entire system chain; consumers are evolving from data providers to intelligent participants, and consumption patterns are becoming more personalized, contextualized, and immersive. Meanwhile, platform enterprises are moving from single-technology deployment toward ecosystem construction. Through the synergistic support of "data + algorithms + computing power + scenarios," they are reshaping the relationship between "people, goods, and places" and commercial organizational forms. This evolution is expected to significantly enhance consumption efficiency and expand scenario boundaries, injecting new momentum into releasing internal demand and restructuring the supply system.
From the perspective of supply-demand structure, AI consumption has become an important lever for cultivating a new internal demand system. During the 15th Five-Year Plan period, the traditional demographic dividend will further weaken, and consumption expansion will enter a stage that places greater emphasis on quality, efficiency, and matching. Against this backdrop, AI activates new internal demand and cultivates new drivers by reshaping consumption scenarios and supply-demand logic. On one hand, consumer demand is increasingly exhibiting trends of stratification and personalization. From middle-income groups to the "silver-hair" demographic [2], and from first-tier cities to sinking markets [3], various groups show significant differences in consumption preferences, service expectations, and willingness to pay, driving consumption from mass products toward customized supply. Relying on big data and algorithm-driven capabilities, AI realizes a shift toward scenario embedding, emotional interaction, and value co-creation, significantly improving the quality and efficiency of supply-demand adaptation. On the other hand, consumer philosophies are quietly changing, shifting toward value-based consumption that emphasizes experience, emotion, and participation. Consumers’ comprehensive expectations for "function + emotion + service" are forcing enterprises to reconstruct their production logic. This conceptual shift prompts companies to focus on interactivity, emotionality, and companionship in product design and service processes, driving the rapid rise of new service formats such as virtual assistants and intelligent companionship. Overall, AI is moving the supply-demand relationship toward dynamic adaptation, providing a practical path for building a more efficient, flexible, and sustainable internal demand system.
From the perspective of inclusive development, "AI Plus consumption" faces the dual challenges of the "intelligence gap" and demand mismatch. While the deep integration of AI and consumption continuously releases new momentum, risks of insufficient inclusivity and structural polarization may exacerbate the "intelligence gap" and demand mismatch. On one hand, the application of technology is widening the gap between different groups in terms of entry barriers and benefit levels. High-education and high-skill groups, possessing higher digital literacy and stronger purchasing power, are often able to more fully enjoy personalized recommendations, precision services, and consumption subsidies. Conversely, many low-to-middle-income or elderly groups find themselves on the periphery of the intelligent consumption system, leading to a new form of "digital consumption exclusion." On the other hand, supply-demand matching mechanisms dominated by algorithms have also intensified mismatches in consumption behavior. Some platforms, when making algorithmic recommendations, may induce irrational consumption or exacerbate addictive usage, gradually weakening the space for consumers’ autonomous choice. When so-called personalization is increasingly replaced by labeling and repetition-driven mechanics, the consumption experience easily falls into convergence, even obscuring diversity and creativity. Once this "circle-layer consumption" [4] and "algorithmic aesthetics" become solidified, they may affect the overall vitality and fairness of the consumer market. Therefore, while promoting the expansion of intelligent consumption, it is necessary to strengthen the design of inclusive mechanisms to prevent the technological dividend from becoming a barrier of polarization.
From the perspective of the institutional environment, promoting the development of "AI Plus consumption" urgently requires the formation of a systematic and forward-looking governance framework. As the deep integration of AI and consumption progresses, the development of intelligent consumption is no longer merely a matter of technological drive or market evolution; it faces challenges in reshaping institutional systems and reconstructing governance logic. Currently, key issues such as unclear data ownership, insufficient algorithm transparency, and blurred platform responsibility boundaries still lack unified and actionable institutional norms. Tensions between data security, algorithmic fairness, user rights protection, and market efficiency are gradually emerging. Existing policies focus on demonstration pilots and industrial cultivation, but in governance links such as the determination of platform responsibility, cross-domain regulatory coordination, and consumer rights protection, there still exist responsibility vacuums, missing rules, and fragmented law enforcement. At the same time, the trends of digital platforms' cross-sector operations and technological evolution outpacing regulatory updates are increasingly evident. Traditional regulatory systems divided by industry struggle to adapt to the new consumption ecosystem under the background of comprehensive intelligence. There is an urgent need to build a layered, classified, and dynamically adjustable intelligent consumption standard system. Facing the 15th Five-Year Plan, policy orientation should emphasize both development and governance, accelerating the formation of a structured, clear, and highly responsive intelligent consumption governance system to safeguard the high-quality development of "AI Plus consumption."
2. Promoting the Deeply Integrated Development of "AI Plus Consumption"
Focusing on the construction of an intelligent supply system and promoting the high-quality iteration of products and services. The primary point of focus for the deep integration of "AI Plus consumption" lies in building a future-oriented intelligent supply system. During the 15th Five-Year Plan period, as breakthrough AI technologies emerge, the supply side is undergoing a fundamental shift from product-driven to intelligent service-driven models. By accelerating integrated innovation in key areas such as intelligent manufacturing, digital content, smart homes, and cultural tourism/entertainment, AI is becoming a vital engine for improving supply quality, enriching consumption scenarios, and guiding new types of demand. Enterprises must deeply tap into the value-added potential of "AI Plus" technology in product design, functional expansion, and emotional interaction, creating more high-value-added products that combine intelligence, personalization, and experiential quality. Especially in terminal sectors such as home appliances, wearable devices, and automobiles, products should be pushed beyond their tool-like attributes to upgrade into emotional carriers. Enhancing human-computer interaction experiences will satisfy consumers' higher-level emotional identification and life imagination. Centering on intelligent services, we must reshape traditional supply logic and accelerate the evolution of retail, health, and education toward companionship-based, customized, and immersive consumption. Revolving around the user’s full life cycle and diversified needs, we should build service mechanisms for intelligent recommendation, proactive response, and continuous interaction, creating a new user-centered dynamic supply model. Platform enterprises should be encouraged to transform into intelligent ecosystem operators, building integrated ecosystems that cover product design, service output, and user operations. By opening up upstream and downstream supply-demand chains and linking small and medium-sized enterprises, industry chain partners, and content creators, a multi-participant, data-interconnected, and value-co-creating intelligent supply system can be formed, enhancing overall supply efficiency and collaborative innovation capabilities.
Expanding application ecosystems for key scenarios and stimulating diverse intelligent consumption demands. Deepening the integration of "AI Plus consumption" requires promoting deep linkage between technology and consumption around key scenarios, expanding immersive, interactive, and multi-terminal application ecosystems to give rise to new business formats, shape new experiences, and release new needs. During the 15th Five-Year Plan period, as the penetration rate of intelligent terminals increases and the application of generative AI becomes more widespread, consumption scenarios will evolve from single channels toward cross-scenario, cross-platform, and cross-spatial integration. First, focus on key areas of people's livelihoods such as livelihood services, cultural tourism, and elderly healthcare to accelerate the landing of AI application scenarios. Taking health and elderly care as an example, AI assistants, intelligent monitoring, and personalized health plans build a user-centered companionship service system, making service supply more "warm" and efficient. Second, emphasize innovation in integrated online-offline scenarios, promoting cross-border linkage in fields such as e-commerce live streaming, unmanned retail, and smart homes to create a more participatory intelligent consumption environment. The combination of cutting-edge technologies like digital humans, virtual spaces, and augmented reality will also continuously expand the boundaries of perception and imagination, shaping more diverse and sustainable consumption experiences. Third, strengthen systematic public policy support for scenario construction. By establishing pilots and improving incentive mechanisms, we can open channels for the landing of AI in consumption scenarios. Focusing on scenarios with high-frequency rigid demand, strong interactivity, and replicable models, we should cultivate a batch of leading, demonstrative, and diffusive "AI Plus consumption" integrated applications, laying the foundation for AI to integrate more deeply into daily life and build a high-quality intelligent consumption ecosystem.
Strengthening the construction of the underlying capability support system to solidify the long-term foundation for integrated development. To achieve the deep integration of "AI Plus consumption," it is essential to build a solid and reliable underlying capability system to ensure the stability and security of the intelligent consumption ecosystem. During the 15th Five-Year Plan period, intelligent consumption’s dependence on underlying resources such as computing power, data, and algorithms will increasingly grow, placing higher demands on institutional rules and public support capabilities. We must promote the inclusive accessibility of computing power, optimizing infrastructure layout and lowering service thresholds to improve accessibility to intelligent technology for SMEs and non-central regions. Support local governments in building regional computing centers to promote the formation of a "cloud-edge-terminal" collaborative service system. Accelerate the push for high-quality public data sharing, focusing on key areas closely related to consumption such as transportation, logistics, payment, markets, and user behavior. We must improve mechanisms for public data collection, de-sensitization, and openness, promoting data synergy and sharing among diverse actors. Guide platform enterprises to explore "data public welfare pool" mechanisms to release the potential of data factors while ensuring privacy, enhancing the adaptability and inclusivity of algorithm models. Improve foundational algorithm capabilities, encouraging the development of more adaptable general models and industry-specific models, supporting the construction of open-source ecosystems, and promoting the enhancement of model capabilities to serve small platforms and diverse consumption scenarios more broadly. By strengthening the resource base and clearing technical bottlenecks, we can provide stable, inclusive foundational support for "AI Plus consumption," ensuring the integration process proceeds steadily and sustainably.
Constructing a flexible and inclusive institutional guarantee system to fortify the governance foundation for integrated development. The integrated development of "AI Plus consumption" is not only the result of technological progress and market evolution but is also inseparable from the strong support of the institutional environment and policy system. Currently, in key links such as data rights confirmation, algorithm regulation, and consumer rights protection, there are still issues like inconsistent standards, missing rules, and blurred responsibility boundaries, which have gradually become constraints on the healthy development of intelligent consumption. We must push the institutional system forward and deeper. First, strengthen ex-ante regulation and risk early warning, focusing on key hidden dangers such as algorithmic discrimination, information misleading, and false interaction. Establish a comprehensive governance mechanism covering data security, algorithm compliance, and platform responsibility to intervene early and in a timely manner, preventing the accumulation and expansion of problems. Second, improve a collaborative and efficient policy execution system, breaking down departmental barriers and information silos. Promote the linkage and coordination between multiple fields—such as industry, data, culture, and finance—and regulatory departments, exploring the establishment of governance pilots covering different consumption scenarios. Encourage local governments to introduce "AI Plus consumption" support policies tailored to local conditions, providing precise support in computing power platform construction, data resource openness, and the cultivation of new consumption formats, gradually forming an institutional ecosystem that balances development with regulation and vitality with order. Third, build a layered and classified "governance toolbox" to enhance the flexibility and precision of institutional responses. Explore adaptable regulatory rules and responsibility mechanisms for different industries, platform sizes, and technology types. For large platforms, external accountability and transparency obligations should be strengthened; for SMEs, technical guidance and inclusive regulation should be provided. In this way, we can gradually establish an intelligent consumption governance system marked by graded regulation, classified policy implementation, and dynamic optimization.
(Authors: Xia Jiechang is a researcher at the National Academy of Economic Strategy, CASS; Wang Wenji is a specially invited researcher at the Jiangsu Center for the Study of Xi Jinping Thought on Socialism with Chinese Characteristics for a New Era and an Associate Professor at the School of Management, Nanjing University of Posts and Telecommunications.)
Source: Guangming Daily, September 8, 2025, Page 6. Web Editor: Tongxin