BMW Group implemented a cloud-based mobile data recorder (MDR) system by installing IoT devices in development cars to automatically capture and transmit extensive vehicular telemetry to Microsoft Azure. They built a comprehensive platform using Azure IoT Hub, Azure App Service, and Azure Kubernetes Service, and integrated Azure OpenAI Service with GPT-4o via Azure AI Foundry to create an MDR copilot that converts natural language queries into Kusto Query Language (KQL). This solution streamlined real-time data capture, analysis, and troubleshooting, accelerating vehicle prototyping and enhancing development quality.

Localiza, a leading mobility company in Latin America, implemented Microsoft 365 Copilot to automate processes and improve efficiency. By integrating AI into their workflows, they enhanced employee productivity, optimized repetitive manual tasks, and improved inclusivity. They conducted training and hackathons to help employees effectively use Copilot, resulting in significant productivity gains across the company.

Toyota deployed a system named O-Beya integrating nine specialized AI agents powered by GPT-4o to capture and consolidate decades of engineering expertise. The solution leverages Microsoft Azure OpenAI Service with API integration via Azure Functions and a vector search–enabled Cosmos DB to process design reports, regulatory data, and handwritten documents, streamlining powertrain design workflows and preserving expert knowledge amid retirements.

JATO Dynamics used Azure OpenAI Service to develop Sales Link, an AI-driven content generator that helps car dealerships quickly produce tailored marketing content by combining market data and vehicle information.

BMW Group, in collaboration with SORDI.ai and Monkeyway, deployed a generative AI system that scans a wide range of industrial assets and uses Vertex AI to produce detailed 3D digital twins. This automated solution replaces the slow, manual asset mapping process, enabling rapid simulation of multiple industrial scenarios to optimize planning and supply chain efficiency.

Denso developed human-like autonomous robots by integrating Azure OpenAI Service for natural language understanding with Azure AI for voice recognition to enable flexible, dialogue-driven control of robotic movements. They employed GitHub Copilot to rapidly generate and refine control code and created a unique verification tool for adjusting robot functions based on real-world inputs. This integration transformed traditional pre-programmed workflows into dynamic systems supporting human-robot collaboration in diverse operational settings.

ZF Group enabled secure citizen development by deploying Microsoft Power Platform across its global workforce with an enterprise-wide governance model to ensure security and quality. They segmented developers into Citizen Developers, Citizen Pros, and a Central Team and integrated an automated Spot Assessment via Power Apps along with a custom ticketing system to digitize processes such as shop floor management. They are also exploring the use of Copilot in Power Apps for natural language app creation to further accelerate development.

Volkswagen of America built a virtual assistant in the myVW app, where drivers can explore their owners’ manuals and ask questions, such as, “How do I change a flat tire?” or “What does this digital cockpit indicator light mean?” Users can also use Gemini’s multimodal capabilities to see helpful information and context on indicator lights simply by pointing their smartphone cameras at the dashboard.

Network Rail implemented an AI-driven analytics platform called "insight" leveraging Azure Databricks and Azure Machine Learning to process vast amounts of data from its extensive railway infrastructure. The solution integrated diverse data streams—including track geometry, ultrasonic testing, and weather data—using Azure Data Factory and delivered visual insights through Power BI to enable predictive maintenance and efficient asset management. Agile collaboration with Microsoft architects streamlined maintenance scheduling and transformed labor-intensive processes into near real-time, cost-effective decision-making workflows.

Jaguar TCS Racing partnered with Google Cloud to integrate cutting-edge AI and cloud technologies into their racing operations. They implemented a real-time data capture and analytics system that processes performance metrics from the Jaguar I‑TYPE 6 as soon as it enters the pit garage, enabling engineers and drivers to make informed, live race decisions. This AI-driven solution optimizes both in‐race strategy and operational workflows for enhanced competitiveness on and off the track.

Woven – Toyota's investment in the future of mobility — is partnering with Google to leverage vast amounts of data and AI to enable autonomous driving, supported by thousands of ML workloads on Google Cloud’s AI Hypercomputer. This has resulted in 50% total-cost-of-ownership savings to support automated driving.

Mercedes Benz will infuse e-commerce capabilities into its online storefront with a gen AI-powered smart sales assistant. Mercedes also plans to expand its use of Google Cloud AI in its call centers and is using Vertex AI and Gemini to personalize marketing campaigns.

General Motors partnered with Google Cloud to integrate conversational AI into its OnStar Interactive Virtual Assistant by embedding Dialogflow-powered intent-recognition algorithms in its vehicles and digital channels. The AI was implemented across millions of GM vehicles to provide natural language routing, navigation, and emergency assistance, and chatbots were deployed on GM’s websites to deliver detailed vehicle information. This integration optimized support workflows by reducing routine call handling and enabling OnStar Advisors to focus on complex requests.