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, validation, and manufacturing.
Reported impact
GM reports faster feedback loops, more concurrent collaboration, more targeted physical validation, fewer late surprises, faster plant readiness, and higher-quality, more reliable vehicle programs.
GM built an in-house, virtual-first vehicle development workflow around a shared digital foundation and integrated digital thread that carries data across design, engineering, validation, and manufacturing. Early in the process, AI is applied to hand-drawn concept sketches to generate many more design variations plus teaser animation in less than a day, giving teams faster design-space exploration. An AI-powered virtual wind tunnel then lets designers and aerodynamicists evaluate drag effects from surface changes in real time. Deeper in engineering, co-simulation links physics-based plant models with virtual controllers in a closed-loop environment so software and hardware behavior can be validated before physical hardware is available. For safety work, virtual crash simulation uses advanced machine learning to compress roof crush analysis from hours to minutes. In manufacturing, immersive XR and augmented reality help teams review assembly sequences, ergonomics, tooling placement, clearance, and access before installation, reducing prototype dependence and shortening commissioning.
Hand-drawn concept sketches and decades of engineering data feed GM’s shared digital foundation, where AI expands design options and the AI-powered virtual wind tunnel evaluates aerodynamic effects. The digital thread carries updates into co-simulation, which connects plant models and virtual controllers for closed-loop validation, then into virtual crash simulation for safety analysis. Manufacturing teams consume the same evolving models through XR and AR to validate assembly, ergonomics, and tooling before physical installation.
"GM is embedding AI into workflows from the first sketch onward to help teams refine ideas sooner."
"GM is reimagining the vehicle development process around a more connected, virtual-first model — one that uses AI, simulation, and decades of engineering data to compress feedback loops and reduce physical iteration."
"GM’s AI-powered virtual wind tunnel allows designers and aerodynamicists to evaluate how surface changes affect drag in real time"
"These virtual workflows help our plants get operational faster and with fewer late surprises, shaving weeks off our traditional mean time to commission."
"Using advanced machine learning and simulation, GM can cut roof crush analysis runs from 8-40 hours to less than 5 minutes"
"a designer can now start with a hand-drawn concept sketch and use AI to quickly produce a series of images and teaser animation, compressing a process that traditionally could have taken months into less than a day."
"co-sim... links physics-based plant models with virtual controllers in a closed-loop environment."
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.
You’ll find our headquarters in Detroit, MI.
Related
In-house Sample Oct 16, 2026 Mercedes-Benz 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… efficiency gains of up to 50 percent expected in individual engineering processes AI agents · CONTACT Elements · PLM.AI 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 