What challenges did Stellantis face before AI implementation?

Accelerate software development and deployment for new digital products in vehicles. Deliver personalized and AI-enhanced in-vehicle user experiences. Improve predictive maintenance accuracy using machine learning.

What was the impact of the AI solution?

Reduced time to market for digital automotive products through cloud and AI tools. Enhanced vehicle user experiences with personalized, AI-driven infotainment and assistance. Improved accuracy of predictive maintenance to optimize vehicle uptime. Upskilled workforce to support software-defined vehicle development. Started deployment of BEV electric vehicles with integrated AWS AI capabilities.

Source

Amazon and Stellantis Collaborate to Advance Software-Defined Vehicle Platforms with AWS AI

Use case typePredictive maintenanceUpdated Jun 13, 2026

Stellantis, a global automaker, aimed to accelerate time to market for new digital products, offer personalized in-vehicle experiences, and improve predictive maintenance accuracy using AI and cloud technologies. They selected AWS as their preferred cloud provider and collaborated with Amazon to deploy AI-enhanced applications for infotainment, voice assistance, navigation, vehicle maintenance, and e-commerce integration within the STLA SmartCockpit platform. Stellantis and Amazon launched cloud-based product development tools, global innovation hubs, and began deploying battery electric vehicles with integrated AI and cloud capabilities. They also initiated workforce upskilling programs and developed a virtual engineering workbench for improved software development and testing.

Organization: Stellantis
Industry: Automotive
Location: Netherlands
Published: January 2022

Reported outcomes

Strategic outcomes

New product / capabilityDeployed AI-enhanced vehicle applicationsNew product / capabilityCreated a virtual engineering workbenchInnovation & cultureLaunched global innovation hubsEmployee experienceInitiated workforce upskilling programs

Primary read

Use case focus

Showing 3 of 4

1Software-Defined Vehicle Platforms
2AI-Enhanced User Experience
3Predictive Maintenance

Accelerate software development and deployment for new digital products in vehicles.
Deliver personalized and AI-enhanced in-vehicle user experiences.
Improve predictive maintenance accuracy using machine learning.

Partnered with AWS to deploy AI-powered applications including Alexa-enabled voice assistance and predictive maintenance models.
Implemented a cloud-based data mesh and product development environment (Virtual Engineering Workbench) for scalable, collaborative software engineering.
Established AWS-powered global innovation hubs for accelerating development.
Launched training programs to upskill engineers on AWS and cloud technologies.

Technologies

AWS Machine Learning Amazon Alexa AWS data mesh

Reduced time to market for digital automotive products through cloud and AI tools.
Enhanced vehicle user experiences with personalized, AI-driven infotainment and assistance.
Improved accuracy of predictive maintenance to optimize vehicle uptime.
Upskilled workforce to support software-defined vehicle development.
Started deployment of BEV electric vehicles with integrated AWS AI capabilities.

Architecture

Stellantis leverages AWS cloud and AI services including AWS Machine Learning, Amazon Alexa, and AWS data mesh to power its STLA SmartCockpit digital vehicle platform. The architecture supports AI-enhanced infotainment, voice assistance, navigation, and e-commerce services. Cloud-based development tools and global innovation hubs enable rapid software iteration and deployment.

Sources & evidence1

Groundedness: 5/5

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