- Geely is scaling AI-driven manufacturing to enable fully automated and flexible production systems
- Strategic partnerships aim to accelerate global innovation and ecosystem transformation
Geely’s push toward next-generation factory intelligence took center stage during its 2026 digital manufacturing showcase, highlighting a shift toward AI-driven, fully connected production ecosystems. Hosted at the Hangzhou Bay SEA Plant, the initiative reflects the company’s ambition to redefine automotive manufacturing through advanced automation, data integration, and flexible production systems capable of adapting to dynamic market demands.
AI-driven manufacturing vision and transformation roadmap
Over the coming five years, Geely Automobile Group plans to establish a globally competitive intelligent manufacturing system powered by artificial intelligence and large-scale data capabilities. The transformation aims to integrate every stage of production, from order intake and automated scheduling to robotic collaboration and mass customization. By embedding AI into operational workflows, the company seeks to enhance efficiency, reduce production complexity, and enable seamless transitions between different manufacturing configurations.
Core technology focus areas shaping future production
The company has outlined a structured roadmap centered on strengthening its AI backbone. This includes expanding computing infrastructure, advancing large-scale AI models, and leveraging big data analytics to optimize manufacturing precision. Integration of virtual simulation technologies alongside embodied intelligence will further enable predictive production planning and real-time process optimization, ensuring higher efficiency across facilities in China and global operations.
Strategic collaborations accelerating innovation
To scale its intelligent manufacturing ambitions, Geely is actively pursuing partnerships with global technology leaders such as Nvidia, Siemens, and Alibaba Cloud. These collaborations are designed to fast-track the deployment of cutting-edge AI technologies, enhance industrial software capabilities, and foster innovation through joint research with academic institutions and technology ecosystems worldwide.
From manufacturing scale to ecosystem-driven growth
Beyond production efficiency, the initiative marks a strategic transition from traditional manufacturing to a broader ecosystem-oriented approach. Geely aims to evolve from scale-driven operations to technology-led competitiveness, while also shifting from standalone production systems to globally interconnected networks. This transformation will support the company’s long-term vision of integrating manufacturing with digital services, enabling smarter mobility solutions and enhanced lifecycle value creation.
Frequently Asked Questions
What is Geely’s digital intelligent manufacturing strategy?
Geely’s digital intelligent manufacturing strategy focuses on integrating artificial intelligence, big data, and automation across the entire production process to create a flexible and highly efficient manufacturing system. This approach enables seamless coordination from order management to robotic production and customization. Over time, it aims to improve productivity, reduce costs, and support innovation by combining advanced computing, simulation technologies, and global collaborations to build a future-ready automotive manufacturing ecosystem.
How will AI impact Geely’s production capabilities?
Artificial intelligence will significantly enhance Geely’s production capabilities by enabling predictive planning, real-time optimization, and automated decision-making across manufacturing operations. AI-driven systems can improve efficiency, reduce errors, and allow flexible production adjustments based on demand. Additionally, integration with robotics and simulation technologies supports faster innovation cycles and higher-quality output, positioning Geely to compete globally while transitioning from traditional manufacturing to a technology-focused and ecosystem-driven production model.
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