AI @ General Motors
Summary
- From 2021 to early 2026, General Motors (GM) has progressively integrated advanced AI technologies across vehicle design, manufacturing, supply chain, and autonomous driving, evidenced by strategic partnerships with NVIDIA and Google and hiring of AI leadership such as Chief AI Officer Barak Turovsky.
- AI applications at GM have transitioned from experimental pattern recognition systems like MENNDL (2021) to comprehensive AI-driven manufacturing improvements, quality control, EV charging infrastructure optimization, predictive supply chain management, and plans for commercial deployment of conversational AI and eyes-off autonomous driving by 2028.
- GM's AI adoption shows clear increasing trends aiming to reduce costs, improve quality and safety, enhance customer experience, and increase revenue through data-driven production adjustments and autonomous vehicle technology, positioning GM as a leader among automotive OEMs in AI innovation.
VIBE METER
6 AI Use Cases at General Motors
Autonomous Driving2025Customer Facing
Supply Chain Resilience2025
Manufacturing Optimization2025
Dealer Demand Forecasting2025
EV Charging Optimization2025Customer Facing
Motorsports Analytics2024
Timeline
2026 Q1: no updates
2025 Q4
GM announced plans for eyes-off autonomous driving by 2028, rollout of conversational AI powered by Google's Gemini technology, and a centralized computing platform exemplified by the Cadillac ESCALADE IQ to deepen AI integration in vehicles and supply chain management.
2025 Q3
GM expanded AI adoption in vehicle production, marketing of EVs, and global supply chain resilience with in-house tools like SupplyHealth and SupplyMap to proactively manage risks and improve responsiveness; GM also recruited elite AI talent and emphasizes AI as a practical, transformative force.
2025 Q2
GM's AI implementations prioritize improving safety, quality, and efficiency in manufacturing plants, transforming toward a software-driven automotive leadership.
2025 Q1
GM significantly expanded AI adoption across manufacturing with AI-driven quality control, safety improvements, and efficiency gains; appointed Barak Turovsky as Chief AI Officer; partnered with NVIDIA on next-gen vehicle and factory AI; used AI for EV charger site optimization and dealer vehicle order recommendations.
- Forbes: GM Develops New AI-Driven Quality Control Tech
- Reuters: GM Hires Chief AI Officer Barak Turovsky
- NVIDIA Newsroom: General Motors and NVIDIA Collaborate on AI for Next-Gen Vehicles and Manufacturing
- Inspenet: GM Uses AI to Expand EV Charging Infrastructure in the US
- Automotive News: GM Creates AI-Powered Engine to Help Dealers Order New Vehicles
2024 Q4
GM utilized AI and machine learning to run continuous, sophisticated vehicle software tests enhancing quality and safety; also deployed AI in motorsports to optimize performance.
2024 Q3
GM deployed predictive AI tools for resiliency, including supply chain real-time event monitoring and supply chain mapping to mitigate disruptions.
2024 Q2
GM initiated its centralized 'data factory' strategy to break down silos and unify AI and machine learning projects, with strategic vision to incorporate generative AI.
2024 Q1: no updates
2023 Q4
Published analyses highlighted GM's AI use cases in enhanced driver assistance and vehicle software improvements to boost safety and performance.
2023 Q3
GM announced a broad partnership with Google to explore and implement AI technologies within automotive industry applications.
2023 Q2
GM focused on upskilling its workforce in industrial AI, with executives like Jeff Abell promoting AI education for better workforce readiness.
2023 Q1: no updates
2022 Q4: no updates
2022 Q3: no updates
2022 Q2
GM partnered with Untether AI to develop next-generation autonomous vehicle perception systems leveraging at-memory computation technologies.
2022 Q1: no updates
2021 Q4: no updates
2021 Q3: no updates
2021 Q2
GM licensed the MENNDL AI system from ORNL, which uses evolutionary techniques to design optimal convolutional neural networks for automotive pattern recognition tasks.