The 15th Five-Year Plan proposal explicitly advocates the comprehensive implementation of the ‘AI Plus’ initiative, targeting the pinnacle of artificial intelligence industrial applications to inject all-round empowering momentum into myriad sectors. This deployment signifies that artificial intelligence has transcended mere technological boundaries, becoming the core engine for consolidating the foundations of the real economy, constructing a modern industrial system, and cultivating new productive forces during the 15th Five-Year Plan period.
A profound leap from technological exploration to large-scale empowerment
‘AI+’ represents not merely a superficial technological overlay, but a profound transformation that challenges the very essence of cognition, reshapes industrial ecosystems, and propels productivity into a new era. As fertile ground for new business models and formats, a cohort of AI-native enterprises has emerged. Their foundational architecture and operational logic are centred on AI technology, giving rise to novel product interaction paradigms, commercial structures, and corporate organisational frameworks. In the hardware domain, next-generation intelligent terminals—including smart connected vehicles, AI-enabled devices, intelligent robots, and smart home systems—are accelerating their adoption, establishing an all-scenario intelligent interaction ecosystem. Concurrently, the cross-disciplinary integration of AI with frontier technologies such as quantum computing, bio-manufacturing, hydrogen energy, brain-computer interfaces, embodied intelligence, and 6G is carving out new industrial frontiers, emerging as fresh catalysts for economic growth.
Within traditional industrial upgrading, ‘AI Plus’ plays a pivotal role in enhancing the efficiency of all production factors, driving systematic intelligent transformation across manufacturing, agriculture, and services. This represents not merely equipment renewal, but a comprehensive reshaping of the value chain spanning production, management, operations, and service delivery. In the industrial sector, AI-driven industrial internet enables intelligent coordination across design, pilot testing, production, and service processes. This optimises manufacturing techniques, enhances product yield rates, establishes flexible supply chains, and creates precise supply-demand matching systems, significantly boosting total factor productivity. In agriculture, intelligent machinery and agricultural drones enhance perception, decision-making, and control capabilities during production. AI-assisted breeding technologies enable precision cultivation, harvesting, and post-harvest operations, boosting efficiency and resource utilisation. Within services, widespread adoption of smart terminals and intelligent agents has spawned numerous unmanned and human-machine collaborative scenarios across finance, logistics, commerce, and legal sectors, expanding service boundaries and elevating development quality.
Future industrial development will undergo three paradigm shifts: Firstly, transitioning from tool to agent – AI will evolve beyond providing information and decision support to become proactive task executors and digital partners driving industry transformation; Second, from pursuing certainty to dynamic optimisation, human-machine collaborative decision-making replaces pure experiential judgement, enabling continuous adaptation and upgrading in uncertain environments; Third, from Software as a Service to Intelligence as a Service, intelligence will become a cloud-based public service accessible on-demand across industries.
Fortifying the foundational support and institutional safeguards for the implementation of ‘AI+’
The large-scale deployment of ‘AI+’ necessitates the simultaneous enhancement of three core capabilities: computing power, data, and talent. Regarding computing power, accelerating technological breakthroughs and engineering applications of hyperscale intelligent computing clusters is essential, while concurrently advancing the cloud migration of various industries to ensure computing capacity through cloud-based intelligence. Regarding data, we must both leverage big data technologies to extract over 90% of unstructured ‘dark data’ within industries (encompassing text, images, speech, video, etc.) and facilitate the digital transformation of tacit knowledge held by industry experts, converting experiential wisdom passed through oral tradition and practical demonstration into high-value data resources. Regarding talent cultivation, the focus should be on developing versatile professionals who are proficient in model architecture, algorithmic principles, and the boundaries of AI capabilities, while also possessing deep understanding of business processes and industry logic. These individuals will serve as the core bridge connecting AI intelligence with actual productivity.
Simultaneous organisational evolution is equally critical, requiring the dismantling of traditional process inertia and authority structures to accelerate and enhance the implementation of ‘AI+’. Firstly, drive full-staff participation in transformation through initiatives like smart innovation challenges and hackathons, making grassroots contributions visible. This transforms employees from passive users into active co-creators, enhancing collective ownership through performance incentives and agile, incremental approaches. Secondly, reconfigure the organisational DNA by shifting from function-centric to scenario-driven approaches. Establish cross-departmental hybrid teams integrating data scientists, engineers, and product managers. Embed data workflows, decision-making authority, and feedback loops at operational levels to shorten decision chains and enable rapid iteration of scenario models, embedding AI deeply within the organisational fabric. Finally, establish a digital trust framework centred on service capability standards. Quantify platform and model stability, accuracy, and response speed into Service Level Agreements (SLAs), while integrating large-model security governance into business processes. This transforms trust from subjective perception into verifiable service contracts.
Looking ahead, competition in the realm of ‘AI Plus’ will not hinge solely on the capabilities of individual models, but rather on the coordinated operation of the five-ring system encompassing computing power, data, models, scenarios, and governance. Only through systematic and synergistic upgrades in technology, data, talent, and mechanisms can we reach the critical inflection point for industrial advancement, propelling our nation into a new phase of comprehensive development towards a smart economy and smart society.
