AutoScout24 Group, Europe's largest pan-European and Canadian online car marketplace, reduced development cycles from 2–3 weeks to 2–3 days for select projects by integrating OpenAI's Codex and ChatGPT into its engineering workflows.
The company, which connects 30 million monthly users with over two million vehicle listings and supports 45,000 dealer partners, faced mounting pressure to accelerate innovation as system complexity grew and product expectations increased. Large-scale migrations, legacy systems, and rising engineering demand made incremental improvements insufficient for the company's goals of improving how buyers search and evaluate vehicles, and how dealers market inventory.
**The Rollout Strategy**
AutoScout24 Group implemented a dual-layer adoption approach. ChatGPT was rolled out across the organization, giving approximately 2,000 employees baseline access to AI tools and establishing AI literacy across functions. In parallel, Codex was embedded into engineering, data, and product workflows, equipping around 1,000 builder employees with a coding agent integrated directly into their daily processes. The company selected Codex after a three-month evaluation across teams, where it demonstrated strong performance in usability, workflow compatibility, and measurable improvements in productivity and code quality.
To ensure adoption at scale, AutoScout24 Group established a cross-functional AI Champions network—a feedback loop between central leadership and individual teams that translated AI capabilities into practical, real-world use cases. This approach encouraged organic adoption and embedded AI into existing workflows rather than treating it as a standalone tool.
**Impact and Use Cases**
Codex quickly proved valuable across several high-impact use cases, including automated pull request reviews, large-scale refactoring, technical documentation, and post-incident analysis. Beyond engineering, AI tools enabled non-technical roles to prototype ideas and validate concepts independently, accelerating innovation across the organization.
According to the company's Chief Technology Officer Frederik Kraus, "Codex has emerged as a key enabler in our engineering workflows, delivering measurable impact in productivity, quality, and speed." The integration enabled faster iteration and experimentation, improved code quality and consistency through automated reviews, and reduced manual workload in pull request reviews and documentation.
**Leadership Lessons**
AutoScout24 Group's approach offers several takeaways for large-scale AI adoption: combine broad AI access with deep workflow integration to maximize impact; prioritize real-world use cases over top-down mandates to drive adoption; establish cross-functional champions to scale knowledge organically; evaluate AI tools rigorously using measurable engineering metrics; and focus on augmenting—not replacing—existing team capabilities.
The company continues to expand its use of AI across both internal workflows and customer-facing products, with future efforts focused on deeper integration into core systems to enable greater automation and intelligence across the platform.