At dawn, an alarm flashed across the control screen of a Shanghai waste-to-energy plant: Furnace Line 3 temperatures were spiking dangerously. Before operators could respond, an AI vision-integrated control system automatically adjusted fuel supply. Within minutes, critical parameters stabilized. This real-time intervention exemplifies Schneider Electric’s industrial AI co-innovation with ecosystem partners, combining computer vision with advanced process control for precision combustion management.

“This project demonstrates our ecosystem-driven approach,” emphasized Yi Xiong, Senior VP of Strategy & Business Development at Schneider Electric China. “Through our ‘Go Green’ initiative, we fuse Operational Technology (OT) with IT expertise to build tailored AI solutions that deliver tangible value in vertical sectors like energy recovery.”

The New Phase of AI Industrialization
As AI moves beyond policy visions into gritty industrial settings, Xiong notes that isolated technologies cannot overcome industrialization barriers. “AI scaling is a relay race powered by ecosystems,” he stated. Collaborative networks must address three core needs:
Technology Integration: AI’s complexity—spanning infrastructure, algorithms, and applications—requires multi-party collaboration to complete the “technical puzzle.”
Scenario Expertise: Successful applications demand deep industry knowledge. For example, predictive maintenance solutions fail without understanding mechanical workflows. This requires specialized partners to “take the baton.”
Scaling Networks: Transitioning from pilots to mass adoption relies on developer communities and platform synergies. “The ecosystem’s scale defines AI’s industrial stage,” Xiong asserted.

Three Pillars for Sustainable Ecosystems
Xiong outlined foundational strategies:

1. Open Collaboration: Companies must break internal silos and promote cross-industry cooperation. Schneider embeds “shared success” in its core values.
2. Technical Leadership: Ecosystem influence stems from irreplaceable expertise. Leveraging 20+ years in digitization, Schneider deploys AI through products (e.g., machine vision), operations (e.g., predictive upkeep), and services (e.g., energy optimization).
3. Talent Cultivation: AI ecosystems thrive on cross-functional experts. Schneider’s “Digital Citizen” and “AI for All” programs will upskill 90% of its China workforce by 2025.

Ecosystem in Action
Internally, Schneider’s cross-departmental AI teams generated 144 innovations in its 2024 “AI Cup,” with 30% already implemented.
Externally, its multi-tier partnerships include:

• The “Go Green” initiative with MIIT, engaging 1,250+ SMEs to deliver 40+ co-created solutions;
• Joint R&D with NVIDIA on power and cooling systems for AI factories;
• The world’s first hydrogen equipment digital twin lab with Zhejiang Hydrogen Innovation Center.

The company also publishes insights like the “AI for GREEN” report, advocating industry-wide cooperation on energy challenges. Its Wuxi “Sustainability Lighthouse” and Shanghai “End-to-End Lighthouse” factories showcase real-world AI transformation.

At WAIC 2025 (opening July 26), Schneider will exhibit next-gen industrial AI solutions with partners. “This relay race demands full commitment from every ecosystem player,” Xiong concluded, urging collective action to accelerate AI’s industry-wide impact.

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