Mercedes-Benz needed to digitalise global product development, connect development, procurement, production, sales, and after-sales data end to end, and help teams make better decisions earlier so new products and technologies could reach series maturity faster without compromising quality or safety.
Reported impact
Mercedes-Benz says PLM.AI can bring new technologies to series maturity up to 30 percent faster, deliver efficiency gains of up to 50 percent in individual engineering processes, and over time could reduce physical testing by half through earlier analysis and validation.
Mercedes-Benz’s PLM.AI is an in-house, AI-native product lifecycle management backbone for global vehicle development. It ingests and connects development information with procurement, production, sales, and after-sales data through standardized data models and end-to-end integration, creating an intelligent knowledge base and seamless digital thread. CONTACT Elements provides the open PLM core layer that integrates product data, processes, and applications, giving Mercedes-Benz a modular and scalable foundation for future AI technologies. On top of that foundation, PLM.AI coordinates AI agents and AI-powered simulations that analyze cross-functional trade-offs such as cost, crash behavior, hardware and software effects, and production impacts. Siemens contributes AI-enabled design, simulation, and digital validation capabilities for the digital twin so engineering domains can work from a shared data and process foundation. The resulting insights are served back to development teams for earlier validation, faster coordination, and quicker progression to series maturity.
Mercedes-Benz connects development data with procurement, production, sales, and after-sales information through standardized data models in PLM.AI. CONTACT Elements provides the shared PLM core where product data, processes, and applications are integrated. AI agents and AI-powered simulations run on that digital thread, and the resulting cross-domain insights are delivered back to development teams and later linked with product, service, and operating data in after-sales.
"AI agents support a wide range of tasks, from optimising material costs or certification and homologation processes to detecting and resolving faults or supporting software development."
"AI-powered simulations and development processes enable more targeted use of physical testing, which could be reduced by half over time."
"CONTACT Software provides the open PLM core layer with CONTACT Elements. This gives Mercedes Benz the modular and scalable foundation needed to integrate product data, processes and applications along the product development process and to flexibly incorporate future AI technologies."
"PLM.AI (Product Lifecycle Management), Mercedes-Benz is creating an AI-native digital backbone. It establishes an end-to-end, intelligent knowledge base that connects development, procurement, production, sales and after-sales."
"This can reduce development time by up to 30 percent, with efficiency gains of up to 50 percent expected in individual engineering processes."
Review how this reference was scored and trace each normalized claim back to its documented source.
Scoring methodology
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Traceability
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
Related
In-house Sample Jun 18, 2026 GM GM wanted to replace a sequential, handoff-heavy vehicle development process that slowed feedback, required too much physical iteration, and exposed programs to late-stage surprises across design, engineering,… cut roof crush analysis runs from 8-40 hours to less than 5 minutes AI · AI-powered virtual wind tunnel · augmented reality (AR) In-house Sample May 12, 2026 Mercedes-Benz Group Mercedes-Benz needed to move AI-powered automation from isolated pilot projects into secure, governed day-to-day business processes across functions including development, production, sales, financial services, human… More than 1,500 employees developed AI and automation applications at a company-wide hackathon. n8n In-house Sample Jan 27, 2026 Audi Audi needed to scale AI-enabled production and logistics across factories while reducing reliance on stationary factory computers, improving flexibility and quality control, and giving employees real-time support in… around 100 robots Edge Cloud 4 Production (EC4P) · P-Data Engine · ProcessGuardAIn 