Building autonomous vehicles is no longer just a question of sensors and software. It has become a test of how well companies can manage vast amounts of data, run large-scale simulations, and validate safety across millions of scenarios before a vehicle ever reaches the road. For automotive firms working on self-driving systems, the ability to test and retrain models at scale is now as important as the vehicles themselves.
This shift helps explain why cloud infrastructure has become central to autonomous driving development. Training and validating self-driving systems requires low-latency compute, high-throughput data processing, and the capacity to run repeated tests under changing conditions. On-premise systems often struggle to keep up with that demand, especially when development timelines stretch over several years.
One company taking this approach is Aumovio, which is using cloud-based computing and AI tools to support its autonomous vehicle work. The company has selected Amazon Web Services as its preferred cloud provider, relying on its infrastructure to support simulation, testing, and AI-driven development workflows.
Aumovio plans to integrate agentic and generative AI into its development processes, with the aim of speeding up how manufacturers build and test autonomous systems. These tools are intended to support tasks such as simulation design, software testing, and data analysis, areas where development cycles can slow as systems become more complex.
The cloud setup will be used in a customer project tied to autonomous trucking. Aumovio’s Aurora autonomous trucks are scheduled to enter production in 2027. The system includes a backup computer designed to take over if the primary system fails, reflecting the emphasis on redundancy in safety-critical systems. As part of its validation process, the Aurora Driver has met more than 10,000 requirements and passed 4.5 million tests run on AWS infrastructure.
“Our collaboration with AWS is a cornerstone of our strategy to lead the transformation to autonomous mobility,” said Ismail Dagli, executive board member and head of the Autonomous Mobility business area at Aumovio.
“We are creating a solution that combines cloud infrastructure, AI capabilities, and automotive expertise, efficiently turning data into actionable insights across complex information environments. This collaboration is not only about accelerating development for our customers, but also about helping promote safety, efficiency, and innovation in autonomous driving.”
From an enterprise perspective, the numbers matter less as marketing proof points and more as signals of scale. Running millions of tests is no longer unusual in autonomous driving. What matters is how quickly teams can repeat those tests, change inputs, and assess results without rebuilding infrastructure each time. Cloud platforms make that kind of iteration easier, even if costs and long-term dependency remain concerns.
The trend extends beyond a single company or project. Self-driving systems share similarities with large AI models used in other fields, where performance improves with more training data and more compute. In mid-2025, researchers at Waymo said autonomous vehicle scaling laws resemble those seen in large language models, where added data and compute lead to measurable gains.
That logic has pushed more automotive firms toward large cloud providers, which operate global fleets of GPUs and offer flexible capacity. In 2023, BMW said it would move its autonomous vehicle data to AWS, citing the need to handle growing volumes of sensor data and simulation workloads.
For enterprises outside automotive, the lesson is less about self-driving vehicles and more about how AI development is changing. Safety validation, redundancy, and repeatable testing are becoming standard expectations in AI systems that operate in real-world conditions. Cloud infrastructure may not solve every challenge, but it has become a practical way to manage scale without locking teams into fixed hardware decisions too early.
“At AWS, we believe the future of autonomous mobility isn’t just about technology – it’s about enabling our partners to deliver on the promise of safer, more efficient transportation at scale,” said Ozgur Tohumcu, general manager of Automotive and Manufacturing at AWS. “Our collaboration with Aumovio and Aurora exemplifies this vision, combining AWS’s AI and cloud infrastructure with Aumovio’s automotive expertise to help Aurora scale autonomous trucking while maintaining rigorous safety standards.”
Aumovio itself is a relatively new standalone company. It was spun out of the Continental Group in September 2025 and is headquartered in Frankfurt, Germany. Its use of cloud-based AI development reflects a broader industry reality: building autonomous systems now depends as much on how data and compute are managed as on advances in vehicle hardware.
(Photo by Sander Yigin)
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