施耐德电气副总裁张磊指出："AI技术要发挥实效，必须紧密结合产业实际。我们依托深厚的行业经验，将AI融入生产运营全流程，助力企业实现高效与可 持续。" 此次参展也标志着施耐德电气与阿里云协同合作的新进展。双方将结合施耐德电气的能源管理技术与阿里云的AI能力，共同推进数字化解决方案落地。例 如，基于阿里通义千问大模型开发的EcoStruxure Building GPT，可实现楼宇智能运维与能效优化。为激活产业链创新，施耐德电气还通过"创赢计划"推 出"AI+赋能计划"与"业务加速计划"，携手生态伙伴推进技术融合与场景共创。 随着"人工智能+"行动持续深入，张磊表示，施耐德电气将持续加码本土研发，构建开放AI生态，携手中国伙伴共促新质生产力发展，绘制产业智能化新未 来。 施耐德电气亮相云栖大会（张云山/摄） 潮新闻客户端 记者 张云山 在今年的云栖大会上，施耐德电气以"AI领航，算电交响——赋能数据中心行业创造绿色高效影响力"为主题首次亮相，展示其AI赋能的软硬件一体化解决方 案，致力于通过技术创新与生态协作，助力中国产业加速数字化与绿色化转型。 作为机器学习与AI算法领域深耕20余年的企业，施耐德电气持续加大 ...

Core Insights - Schneider Electric launched the EcoStruxure Building GPT during the 2025 World Artificial Intelligence Conference, highlighting the transformative role of AI in building operations and energy management [2][5] - The integration of AI in energy management is seen as a strategic move aligned with national policies, marking 2025 as a pivotal year for AI deployment in the industry [3][4] AI in Energy Management - AI's implementation in energy management is driven by a strong data foundation, having evolved through automation and digitization phases, addressing industry pain points such as low efficiency and complex operations [4] - The focus of AI in energy management is on delivering tangible value by optimizing energy efficiency and simplifying operations, contrasting with traditional tool-oriented technologies [4][7] Impact of Generative AI - The rise of generative AI is democratizing technology access, reducing the skill barrier for operational staff, allowing them to interact with systems through natural language instead of requiring advanced technical knowledge [4][7] - The EcoStruxure Building GPT utilizes advanced mechanisms like "large model + RAG" and incorporates specific industry knowledge to enhance user experience and satisfaction [4][10] Product Features - The EcoStruxure Building GPT integrates extensive operational data and expert experience, ensuring it is tailored for the energy management sector rather than being a generic AI tool [8] - It offers lightweight deployment and cost control, allowing clients to easily upload necessary project information for automated processing [8] - The product supports private deployment to address data security concerns, enabling local implementation and self-managed operations [8] Economic Model - The pricing strategy for EcoStruxure Building GPT is based on value creation, linking costs directly to the savings achieved by clients in energy and labor [9] - The company emphasizes a results-oriented approach, ensuring that clients see immediate returns on their investments through AI-driven efficiencies [9] Future Outlook - Schneider Electric plans to continue advancing AI integration in energy management, with expectations of introducing new products at future AI conferences [9] - The company aims to position AI as a practical solution for real industry challenges, moving beyond mere technological showcases [9]