Jiangsu Province has rolled out a new initiative aimed at embedding artificial intelligence into every stage of industrial software development, signaling a major push to modernize the sector. The provincial Department of Industry and Information Technology recently issued the "Jiangsu Province 'AI+' Industrial Software Breakthrough Action Plan (2026–2028)", designed to accelerate the dual empowerment of AI and industrial software, ultimately bolstering the province's drive to become a manufacturing powerhouse.
The plan zeroes in on the need for intelligent transformation within industrial software, calling for AI technologies to be woven deeply into all facets of the software lifecycle. This approach is intended to achieve a comprehensive upgrade in capabilities while enhancing efficiency and quality across the board.
Among the core strategies is a foundational development initiative focused on cracking key technical challenges in AI-integrated industrial software. Efforts will prioritize merging AI capabilities with existing software frameworks, accelerating the intelligent overhaul of traditional tools, and fostering the growth of AI-native software and industrial intelligent agents. These steps aim to solidify the technical groundwork for future innovation.
A separate track targets the modernization of software enterprises themselves, encouraging them to upgrade their operations to boost R&D efficiency and innovative output. The plan promotes novel business models such as "model-as-a-service," "agent-as-a-service," and "outcome-as-a-service," alongside new pricing structures like pay-per-result and pay-per-usage. These shifts are expected to drive fresh momentum in both service delivery and commercial strategy.
The initiative also extends to manufacturing, where it seeks to build high-quality industrial datasets and foster better alignment between data and model optimization. It encourages the deployment of intelligent operating system upgrades, iterative breakthroughs in industrial software, and broader commercialization. By opening up typical smart manufacturing scenarios, the plan aims to facilitate demand-driven matchmaking across industries and use cases, creating a virtuous cycle where real-world applications and software improvements reinforce each other.
To support long-term growth, the plan calls for the establishment of dedicated industrial software research institutes and the cultivation of interdisciplinary senior talent. Local governments are urged to build innovation platforms tailored to their regional strengths—covering areas like pilot testing, compatibility verification, and application promotion—to create a well-structured, tiered industrial innovation landscape.
Ecosystem development is another key pillar, with emphasis on strengthening computing power supply and services. Measures include distributing computing vouchers, model coupons, and token subsidies to reduce the entry barrier for enterprises adopting AI. The plan also champions open-source platforms and encourages activities centered on ecosystems like OpenHarmony and openEuler, aiming to cultivate a collaborative and mutually beneficial industrial environment.
Local authorities are encouraged to align with their specific industrial bases, development goals, and resource advantages to find effective entry points for enhancing their manufacturing support capabilities. The plan also advocates for the creation of angel funds dedicated to industrial software, guiding investors to back early-stage, small-scale, and long-term projects. Dedicated financial resources will be allocated to secure progress in critical areas such as key technology research, model and agent development, enterprise digital upgrades, and innovation infrastructure construction. Additionally, efforts will be made to deepen the role of AI and industrial software academies, bring entrepreneurs into classrooms, refine curricula, and promote collaborative talent training bases between industry and academia.
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