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Schneider Electric drives Generative AI productivity and sustainability solutions by integrating Microsoft Azure OpenAI

Schneider Electric customers and employees use GenAI (Generative AI) capabilities which deliver productivity gains and new ways of working

Schneider Electric, the leader in the digital transformation of energy management and automation, is harnessing the capabilities of Generative artificial intelligence (GenAI) to empower customers and transform its internal operations.

Building on the foundations of a long-standing collaboration with Microsoft, Schneider Electric is integrating Microsoft Azure OpenAI to develop solutions that leverage algorithms to generate text, code, and other types of content. This has empowered Schneider Electric to reimagine its approach to various operational processes, streamlining time-consuming tasks, optimizing resource allocation, and gaining speed and efficiency. At the same time the Group continues to apply GenAI to advance innovation in its offer portfolio.

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The key highlights of Schneider Electric’s use of GenAI include:

  • Resource Advisor Copilot – using Large Language Model technology through Microsoft Azure OpenAI, Schneider Electric has securely built Copilot as a convenient digital companion embedded inside Resource Advisor. Copilot equips customers with enhanced data analysis, visualization, decision support, and performance optimization, and the ability to seamlessly process intricate industry knowledge and Resource Advisor system information.
  • Jo-Chat GPT – internal conversational assistant based on Microsoft Azure OpenAI Service allowing employees to profit from Generative AI capabilities in a secure way.
  • Finance Advisor – this conversational assistant provides an easy and effective way to find precise information for financial analysts in accounting and other functions within global finance. It helps to achieve consistent, compliant, and timely decision-making.
  • Knowledge Bot – conversational assistant helping customer care representatives find precise information to customer queries and proposing appropriate answer based on large internal documentation.
  • Conversational search – helping our customers search for the products they need in a natural conversation style using semantic search capability.

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Schneider Electric is also looking to integrate Github Copilot to further enhance its offer creation processes and operations as well as Sales Copilot to further empower frontline employees.

Commenting on these technological and business advancements, Philippe Rambach, Chief AI Officer at Schneider Electric, stated, “Generative AI is a game-changer and we are investing in this technology. It has already allowed us to enhance internal productivity, and it aligns perfectly with our commitment to continuous improvement and impactful innovation focused on sustainability.”

The AI hub organization at Schneider Electric was launched in 2021, before the GenAI technology became prevalent. With the emergence of these new tools, the company created a dedicated GenAI core team to work closely with internal and external stakeholders to detect early application opportunities.

Schneider Electric’s adoption of Generative AI and integration with Microsoft Azure OpenAI underscores their commitment to staying at the forefront of technological innovation in energy management and industrial automation. The companies are focused on leveraging advanced technologies to drive efficiency gains, foster innovation, and achieve sustainable growth.

“Microsoft Azure OpenAI allows Schneider to develop agile, scalable, cost-effective and AI-powered solutions which are in line with our shared ambitions for a sustainable and digitalized future,” said Dominik Wee, Corporate Vice President, Manufacturing and Mobility at Microsoft.

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Schneider Electric portfolio of solutions built on Microsoft Azure offers its customers next-generation cloud-based, IoT (Internet of Things) solutions as well as advanced data and AI capabilities.

Together, the two companies help customers bridge the gap between setting ambitious sustainability goals and achieving them.

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