AutoScout24 Transforms Its Engineering with OpenAI's AI

AutoScout24: A Major Player in the Online Automotive Market

AutoScout24 Group positions itself as the largest online marketplace for cars in Europe and Canada. Each month, over 30 million users access a vast database comprising more than two million vehicle listings. The company operates under several brands, including AutoScout24 in Europe and AutoTrader.ca in Canada, and collaborates with a network of 45,000 dealership partners. With around 2,000 employees worldwide, AutoScout24 strives to meet the growing expectations of consumers regarding products while managing the increasing complexity of systems.

In the face of these challenges, the company has felt increased pressure to innovate more rapidly without compromising reliability. The goal is to continuously enhance the buyer experience in searching, evaluating, and purchasing vehicles, as well as to optimize how dealers market and sell their inventory. However, incremental improvements were no longer sufficient in the face of large-scale migrations and a growing demand for engineering. The emergence of large language models has provided a unique opportunity to fundamentally rethink how software is built, tested, and evolved, making OpenAI a natural partner for this transformation.

The Impact of AI on AutoScout24's Processes

Frederik Kraus, Chief Technology Officer of AutoScout24 Group, stated that AI is changing not only how the company builds its products but also what it can offer its users and dealership partners. Faster iterations translate into better experiences for buyers and more efficient ways for dealers to reach and convert customers.

AutoScout24 has adopted a two-layer AI strategy to balance broad enablement with deep technical impact. ChatGPT has been deployed across the organization, providing access to AI tools for approximately 2,000 employees and establishing a solid foundation of AI literacy across functions. Simultaneously, the company has integrated Codex into its engineering, data, and product workflows, equipping around 1,000 builder employees with a coding agent embedded directly into their daily processes. Codex was selected after a three-month evaluation within teams, where it demonstrated strong performance in usability, workflow compatibility, and measurable improvements in productivity and code quality.

Adoption and Concrete Results

To ensure large-scale adoption, AutoScout24 Group established a network of cross-functional AI champions. This group created a feedback loop between central management and individual teams, helping to translate AI capabilities into practical, real-world use cases. This approach encouraged organic adoption and ensured that AI was integrated into existing workflows rather than treated as a standalone tool.

Codex quickly proved its value in several high-impact use cases, including automated pull request reviews, large-scale refactoring, technical documentation, and post-incident analysis. Beyond engineering, AI tools have enabled non-technical roles to prototype ideas and validate concepts independently, thereby accelerating innovation within the organization. This ultimately supports faster delivery of improvements on the platform, benefiting both buyers and dealership partners.

Frederik Kraus added that Codex has become a key element of engineering workflows, bringing measurable impact on productivity, quality, and speed. The results are tangible: development timelines have been reduced from 2–3 weeks to just 2–3 days for certain projects. The increased engineering throughput allows for faster iterations and experimentation, while the quality and consistency of code are enhanced through automated reviews. Manual workload in pull request reviews and documentation has also been reduced, and the capacity for innovation has been expanded by enabling non-technical roles to prototype ideas.

Lessons and Future Perspectives

AutoScout24 has drawn several lessons from this integration of AI. It is crucial to combine broad access to AI with deep integration into workflows to maximize impact. Prioritizing real use cases over top-down mandates fosters adoption, and establishing cross-functional champions allows for organic knowledge dissemination. Rigorous evaluation of AI tools using measurable engineering metrics is also essential. Finally, it is important to focus on augmenting the existing capabilities of the team rather than replacing them.

AutoScout24 Group continues to expand its use of AI both in internal workflows and in customer-facing products. Future efforts will focus on deeper integration of AI into core systems, enabling even greater automation and intelligence on the platform. As the company develops its AI capabilities, it aims to further enhance user experiences, empower teams across functions, and unlock new efficiencies in how products are built and delivered.