What challenges did Siemens face before AI implementation?

Siemens faced skilled labor shortages and lengthy automation code development and simulation times, limiting manufacturing efficiency and innovation. There was a need to accelerate automation workflows, reduce repetitive tasks, and improve collaboration between engineering and frontline teams across industries.

What was the impact of the AI solution?

Automation code development time reduced from weeks to minutes, significantly boosting productivity and innovation. Early adoption by Schaeffler AG shows potential for downtime reduction and operational efficiency improvements. Collaboration across engineering and frontline teams enabled on the Microsoft Teams platform, enhancing industrial lifecycle efficiency and innovation.

Source

MicrosoftExpanded

Siemens and Microsoft partner to drive cross-industry AI adoption with Siemens Industrial Copilot

Use case typeAI platformUpdated Jun 13, 2026

Siemens and Microsoft collaborated to develop Siemens Industrial Copilot, a generative AI-powered assistant aimed at enhancing human-machine collaboration and productivity in manufacturing and other industries. The copilot reduces automation code development time from weeks to minutes by utilizing Siemens Xcelerator platform data enhanced with Azure OpenAI Service. Schaeffler AG, a leading automotive supplier, is an early adopter benefiting from improved code generation reliability, reduced downtimes, and increased innovation. Integration of Siemens Teamcenter software with Microsoft Teams enables virtual collaboration across product lifecycle teams including frontline workers and engineers, expanding access to PLM functionalities.

Organization: Siemens
Industry: Manufacturing
Location: Germany
Published: October 2023

Reported outcomes

Strategic outcomes

New product / capabilityLaunched generative AI copilot for automationSpeed & agilityAccelerated automation code developmentCustomer experience & trustImproved collaboration and data accessibilityNew product / capabilityEnabled repair guidance and simulation access

Primary read

Use case focus

Showing 3 of 3

1Generative AI
2Industrial Automation
3Collaboration

Siemens faced skilled labor shortages and lengthy automation code development and simulation times, limiting manufacturing efficiency and innovation.
There was a need to accelerate automation workflows, reduce repetitive tasks, and improve collaboration between engineering and frontline teams across industries.

Siemens Industrial Copilot ingests automation and simulation data from Siemens Xcelerator platform and uses Azure OpenAI Service to allow natural language code generation, debugging, and simulation acceleration.
Integration of Siemens Teamcenter software with Microsoft Teams facilitates generative AI-powered virtual collaboration and data accessibility across product lifecycle management for diverse teams.
The copilot provides detailed repair instructions and quick access to simulation tools to maintenance staff and engineers.

Technologies

Azure OpenAI Service Microsoft Teams Siemens Xcelerator Siemens Industrial Copilot

Automation code development time reduced from weeks to minutes, significantly boosting productivity and innovation.
Early adoption by Schaeffler AG shows potential for downtime reduction and operational efficiency improvements.
Collaboration across engineering and frontline teams enabled on the Microsoft Teams platform, enhancing industrial lifecycle efficiency and innovation.

Architecture

Siemens Industrial Copilot ingests data from Siemens Xcelerator and uses Azure OpenAI Service for AI-powered code generation, debugging and simulation acceleration. Integration with Microsoft Teams via Siemens Teamcenter app facilitates virtual collaboration across product lifecycle.

Sources & evidence1

ExpandedExpanded

The same organization appears in newer AI deployment evidence.