The State Council's Opinions on Deepening the Implementation of the ‘Artificial Intelligence Plus’ Initiative propose accelerating the formation of a new model of smart economy and smart society characterised by human-machine collaboration, cross-boundary integration, and co-creation and sharing. Recently, numerous institutional research reports have summarised China's achievements in integrating artificial intelligence (AI) with key sectors, while outlining the developmental trajectory of AI-empowered industries.
Artificial Intelligence + Automotive: AI Technology Empowering Intelligent Automotive Development
The ‘Major Application Scenarios of Artificial Intelligence Series’, published by China Development Press and compiled under the leadership of Tsinghua University's International Governance Institute for Artificial Intelligence with support from multiple institutions including Tsinghua University's China Science and Technology Policy Research Centre, systematically summarises China's AI application achievements across over ten key sectors. Recently, AI+Finance, AI+Government Services and Social Governance, AI+Education, and AI+Automotive were released during the 2025 World Artificial Intelligence Conference. Among these, AI+Automotive highlights how advances in artificial intelligence technology continue to propel the intelligent evolution of vehicles.
As technology matures, product prices decline, and consumer demand for intelligent driving experiences grows, smart driving features are expanding from luxury models to mid-range and entry-level vehicles, accelerating market penetration. Previously, the Ministry of Industry and Information Technology's ‘Smart Connected Vehicle Technology Roadmap 2.0’ explicitly set targets of 50% penetration for smart connected vehicles by 2025, rising to over 70% by 2030. Current development trends suggest these objectives are likely to be met on schedule.
Policy frameworks, technological innovation, and evolving demand and supply are collectively creating development opportunities for ‘AI + Automotive’. Concurrently, challenges include inappropriate technology route selection, inadequate regulatory and management systems, and data leakage and misuse.
‘Artificial Intelligence + Automotive’ proposes recommendations across four dimensions. Firstly, the government should refine the legal and regulatory framework, including establishing dedicated laws and regulations for smart connected vehicles and constructing testing and certification standards. Second, the industry should establish an ethical framework for intelligent connected vehicles, encompassing the formulation of ethical guidelines, the establishment of diverse ethics committees, and the development of ethical assessment tools. Third, enterprises should adopt a human-centred R&D philosophy, including data and algorithmic technology reviews, alongside ethical and technical training for R&D personnel. Fourth, the ecosystem should construct a multi-stakeholder collaborative governance system, including establishing collaborative governance mechanisms, international cooperative governance, and building feedback mechanisms for societal participation.
The 2025 Financial Industry Large Model Application Report: 2025 Will Mark the Inflection Point for Realising Large Model Technology Dividends in Finance
The 2025 Financial Industry Large Model Application Report (hereinafter referred to as the Report), jointly released by Tencent Research Institute and other institutions, contends that the current focus of artificial intelligence (AI) application should not be a technological race ‘for AI's sake’, but rather a return to the fundamental purpose of technology serving business – calibrating application paradigms and optimising implementation pathways using input-output ratios as the benchmark. The Report projects that 2025 will mark the inflection point for the financial sector to deeply integrate AI and realise the technological dividends of large models.
The Report reveals that nearly half of global financial institutions have initiated large model application development, signalling the industry's transition from sporadic experimentation to large-scale deployment. China's financial sector exhibits a clear top-down, phased approach to large model development: banking leads in widespread implementation, while leading securities and insurance firms pioneer diverse application models.
The report identifies several challenges hindering the deep integration of large models in finance: fragmented high-value data resources, unclear strategic planning and return on investment, technical compatibility difficulties in low-tolerance scenarios, and lagging organisational talent upgrades. To overcome these bottlenecks and transform artificial intelligence from potential into tangible productivity, financial institutions must implement systematic, coordinated strategies across four dimensions: strategy, data, organisation, and technology. Establishing an integrated capability framework encompassing ‘data + application + strategy + organisational talent’ will be pivotal to seizing the initiative in the forthcoming AI paradigm shift.
AI technology is propelling financial services towards unprecedented levels of inclusivity, intelligence, and personalisation, extending expert-level professional services to broader long-tail client segments. Concurrently, the deep integration of AI with human expertise is redefining financial operations and management models, accelerating demand for composite, innovative financial talent. Within this progression, the mining and application of high-quality proprietary data will become a core competitive advantage for financial institutions. Furthermore, the continuous maturation of AI technology and governance frameworks will enhance the efficiency and effectiveness of regulatory technology.
Mobile AI: The New Ecosystem of AI and Mobile Communications Integration: Propelling Mobile Communications into the ‘Mobile AI’ Era
The report Mobile AI: A New Ecosystem for the Convergence of AI and Mobile Communications (hereinafter referred to as the Report), jointly completed by China Telecom (601728) Research Institute and Huawei Technologies Co., Ltd., was recently released. The Report posits that 5G-A, as a crucial evolutionary stage of 5G, not only delivers a significant leap in communication capabilities but also provides a pivotal opportunity for the convergence of artificial intelligence (AI) and mobile communications. To address the rapid growth of AI services, operators urgently need to advance the bidirectional integration of ‘network-driven intelligence’ and ‘intelligence-empowered networks’: on one hand, building native network capabilities that support AI; on the other, enhancing the network's self-learning and self-optimisation capabilities through key technologies such as communication large models and digital twins. Simultaneously, centred on the integrated supply of ‘connectivity + computing power + services,’ it is necessary to explore novel business models driven by dual engines of communication and computing resources. This will facilitate operators' transformation into technology-driven enterprises and propel mobile communications into the ‘Mobile AI’ era.
The report indicates that mobile networks are evolving from ‘connection carriers’ to ‘intelligent foundations.’ The emergence of Mobile AI services has triggered comprehensive evolution in network architecture, resource coordination, and service models. Networks must achieve new capability enhancements in computing systems, data scheduling, and service provisioning to better meet the pervasive, real-time, and scalable characteristics demanded by AI services.
The report reveals that new demands for Mobile AI networks manifest primarily in three areas: computational power scheduling as a dual requirement for both networks and services; network-level collaborative processing capabilities for data and models; and the exploration of novel business models. For instance, against the backdrop of Mobile AI development, traditional traffic-based billing models are facing a plateau phase, compelling operators to urgently explore new value systems integrating connectivity, computational power, and services. Looking towards 6G, operators can flexibly combine network capabilities, computing resources, and AI services based on specific business scenarios to form diversified product offerings and novel business models.
Annual Report on New Generation Artificial Intelligence Development (2024–2025): Steady Enhancement of AI Industrial Strength in China's Major Cities
The Annual Report on New Generation Artificial Intelligence Development (2024–2025) (hereinafter referred to as the Report), jointly released by the New Generation Artificial Intelligence Industry Technology Innovation Strategic Alliance and China Economic Information Service, asserts that China consistently prioritises both development and governance, innovation and security, continuously refining its ‘Chinese approach’ to AI advancement. Major domestic cities are strategically positioning themselves in cutting-edge sectors and cultivating benchmark scenarios, resulting in steady enhancement of their artificial intelligence industrial capabilities.
The Report conducted a comprehensive evaluation of the 2024 artificial intelligence industrial competitiveness across 19 cities selected for the National New Generation Artificial Intelligence Innovation Development Pilot Zones and National Artificial Intelligence Innovation Application Pioneer Zones. Findings reveal that Beijing, Shanghai, and Shenzhen occupy the top three positions; Hangzhou, Suzhou, Guangzhou, Nanjing, Chengdu, Wuhan, and Hefei follow closely with relatively comparable comprehensive strengths; while Changsha, Xi'an, Zhengzhou, Shenyang, and Harbin form the ‘third tier,’ each with distinctive strengths striving to catch up.
Regarding industrial agglomeration, Beijing leads in listed enterprises, total registered capital, and industrial revenue scale; Shenzhen boasts the highest number of enterprises; and Suzhou stands out for its industrial tax revenue. In terms of factor supply capacity, Beijing comprehensively leads in supporting elements; Shanghai leads in computational power (intelligent computing), closely followed by Zhengzhou; Hangzhou boasts well-developed industrial infrastructure. Regarding innovation origination capacity, Beijing has maintained an R&D intensity exceeding 6% for six consecutive years, while Suzhou leads prefecture-level cities in R&D investment; Beijing and Shenzhen demonstrate abundant innovation outcomes, with Hangzhou, Suzhou, and Nanjing exhibiting distinct specialisations. In application empowerment, Beijing and Shanghai lead in large model registrations with distinct vertical model advantages; Hangzhou competes as an open-source large model hub; Nanjing boasts numerous AI enterprise project wins.
The Report recommends: China should strengthen central-local coordination to establish ‘three lists’ and advance domestic substitution of intelligent computing technologies; leverage national strategic guidance to drive high-quality data supply and efficient circulation; deploy a ‘combination strategy’ of experience dissemination, policy integration, and demonstration cultivation to deepen ‘AI+’ applications; and continuously refine governance systems to strive for a pivotal role in global AI sustainable development.
