JD.com's Cao Peng Proposes Six-Point Plan to Boost AI Efficiency and New Quality Productive Forces

Deep News
03/04

National Committee member of the Chinese People's Political Consultative Conference (CPPCC) and JD.com executive Cao Peng has put forward recommendations focusing on AI industry development, rural subsidy programs, and super supply chains during the 2026 Two Sessions.

Cao Peng's first recommendation centers on activating AI industrial efficiency to solidify the foundation for new quality productive forces. He proposed strengthening breakthroughs in chips and basic software, establishing a national computing power scheduling network with an inclusive system, and issuing "computing vouchers" and "model service subsidies" to make intelligent computing power accessible on-demand. He also suggested creating an efficiency-first evaluation and incentive system, implementing deep integration demonstration projects for "AI + industry," and developing integrated terminals like embodied robots and smart devices to open new growth avenues. Additional proposals include embedding AI throughout the software R&D process, building self-controlled basic toolchains and open-source communities to lower R&D barriers, integrating AI deeply into elderly care and government services for convenient "chat-and-handle" services, and leveraging leading enterprises to enable full-chain digital-intelligent transformation toward data-driven, smart decision-making "super supply chains."

His second recommendation involves using product standardization and price indices to assist corporate procurement supply chain digitalization. This includes establishing specialized assessment systems and reward mechanisms for state-owned enterprise procurement digital transformation, promoting industrial product standardization, creating and opening industrial price indices for procurement reference, advancing digital transparent procurement by local governments, and deepening integration between central state-owned enterprise operations and procurement.

The third recommendation pushes for deepening the consumer goods replacement policy in rural areas. Cao Peng identified obstacles such as insufficient promotion, lack of special fund guidance, and offline stores lacking qualifications in rural regions. He proposed increasing publicity for rural subsidies through inter-ministerial coordination, setting up dedicated subsidy funds for rural markets, relaxing eligibility criteria for offline participants to include more small businesses, and comprehensively activating rural consumption through corporate and policy efforts.

The fourth recommendation focuses on using AI to deepen medical supply-side reform and accelerate new quality productive forces in health. Suggestions include strengthening AI innovation in specialized diseases, promoting AI-driven "diagnosis-testing-treatment-pharmacy" closed-loop models, accelerating hospital digital-intelligent infrastructure, implementing grassroots medical AI enhancement initiatives, empowering doctors' clinical and research capabilities with AI tools, and ensuring medical AI security through national health data platforms.

The fifth recommendation highlights leveraging super supply chains to expand domestic demand. Cao Peng emphasized that super supply chains can facilitate supply-demand interaction, reduce internalized competition, and support local employment. Proposals include utilizing brands and supply chains for consumption-led industrial upgrading, encouraging R&D investment for technological integration, strengthening anti-monopoly enforcement, and improving social security systems for grassroots workers.

The sixth recommendation aims at enhancing service guarantees for new employment groups like delivery riders. Cao Peng advocated for promoting full-time "direct employment" models with full labor contracts and social insurance, increasing policy and financial support for socially responsible enterprises, and directing more social resources toward rider welfare facilities and holiday subsidies.

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