Serving as a member of the National Committee of the Chinese People's Political Consultative Conference is both a high honor and a significant responsibility. This experience has underscored that committee members must not only engage at the grassroots level but also connect deeply with it, bringing industry challenges, corporate feedback, and frontline insights to the national meetings. "Working directly in the robotics and smart manufacturing sector, I feel the industry's pulse daily—from the hum of machinery in smart factories to the brainstorming in R&D labs," said Sun Zhiqiang, a National Committee member, Vice Chairman of the Guangzhou Federation of Industry and Commerce, and Chairman of Guangzhou Risong Intelligent Technology Co., Ltd. As the 2026 National People's Congress approaches, Sun revealed that his focus this year will be on building a talent system to support high-quality development in smart manufacturing.

Why emphasize talent? Sun explained that China's smart manufacturing sector faces a critical contradiction: companies urgently need professionals skilled in both industrial AI models and manufacturing processes, yet graduates often lag behind industry demands. This dual shortage of talent has become a direct bottleneck for industrial upgrading. Sun proposed creating a dynamic, high-efficiency ecosystem that responds to industrial changes and maximizes talent value through strategic leadership cultivation, deeper industry-education integration, and reforms in evaluation mechanisms.

The 2025 Government Work Report emphasized directing more resources toward "investing in people" to serve public welfare, a point reiterated at the Central Economic Work Conference in December 2025. For manufacturing, Sun noted, this means not only investing in equipment and facilities but also in talent and skills. "I hope to see fiscal funds and technological resources increasingly倾斜 toward talent development, creating a virtuous cycle of 'talent investment—industrial upgrade—efficiency gains—reinvestment.'" He also stressed that practical contributions, such as resolving major production line failures, should receive recognition equal to publishing high-level academic papers.

Domestic robotics has made significant strides, entering a market-driven phase. A visit to Risong's subsidiary, Guangzhou Risong Robot Technology Co., Ltd., revealed its newly mass-produced high-precision, high-speed PLR robot. Designed to support semiconductors and ultra-precision manufacturing, the robot has been validated by leading domestic and international enterprises. On-site demonstrations showed the robot's six-axis arm swiftly aligning and inserting flexible printed circuits—a task previously done manually—boosting production efficiency dramatically. The PLR robot has passed authoritative testing, achieving sub-micron precision with high operational stability.

Sun highlighted the progress of domestic robotics, noting China's robust industrial chain advantages. With the world's most complete robot supply chain, ample core components, dense manufacturing resources, and short iteration cycles, China outperforms others in transitioning from prototypes to mass production. In 2024, domestic industrial robot brands captured over 50% of the domestic market, and 2025 saw historic net exports, signaling that local robots are no longer mere substitutes but market leaders. China is evolving from a traditional "world factory" participant to a co-builder of the global smart manufacturing ecosystem.

Applications for domestic robots have expanded from automotive and electronics to new energy, semiconductors, photovoltaics, lithium batteries, biopharmaceuticals, and food processing. Leveraging deep understanding of local processes and responsive services, these robots are deeply integrated with industrial needs. Humanoid robots, in particular, have advanced from "performing" to "working," now operating in new energy battery production lines, while wheeled robots penetrate retail and cleaning sectors. "One in three robots nationwide is made in Guangdong," Sun proudly stated, citing the province's concentrated core component suppliers and resilient产业链. Guangzhou has built a complete robot industrial chain covering "core components—whole machine manufacturing—system integration—scene application," ranking among China's strongest regional industrial support systems.

"The real decisive factor in 2026 will be the deep integration of embodied AI models with industrial knowledge," Sun asserted. The competitive high ground in Chinese smart manufacturing will lie in cognitive intelligence for human-machine collaboration. Whoever first achieves autonomous learning and contextual understanding in open environments will define industry standards for the next decade. Since last year, national policies have密集 promoted AI-manufacturing integration. "The key is translating top-level plans into workshop results—addressing bottlenecks like scarce, hard-to-share high-quality industrial data and avoiding low-level redundancy in vertical industry models, which requires more detailed supporting measures," Sun added.

To advance emerging industries, Sun offered four recommendations. First, adopt a "scenario-driven" approach to overcome conversion bottlenecks by promoting demonstration projects for disruptive technologies and encouraging maximum application of new innovations, especially during critical windows, to turn research into marketable products. Second, nurture long-term innovation with "patient capital" by innovating investment mechanisms, easing traditional financial metrics, and establishing tolerance for fund decision-makers. National and state-controlled funds should strategically invest in tech firms, with exploration of a "National Smart Manufacturing Talent Development Fund" for teams engaged in long-term攻关. Third, reshape innovation direction with "multi-dimensional evaluation," establishing a diverse talent assessment system based on innovative value, capability, and contribution, covering technical攻坚, engineering implementation,成果转化, and效益贡献. Flexible channels like "dual university-enterprise appointments" and "industry professors" can break down barriers between academia and industry. Fourth, enhance policy synergy through "cross-department coordination," creating a regular mechanism for smart manufacturing talent development involving education, science, technology, industry, human resources, and finance departments for integrated planning and resource allocation. A national "Smart Manufacturing Talent Big Data Platform" could enable smart talent-job matching and precise policy delivery, ensuring support reaches急需 enterprises and talent.