AutoScout24 and AI engineering: how Codex speeds up development

The context: AutoScout24 and the pressure on development speed

AutoScout24 is one of Europe's leading platforms for buying and selling vehicles. It operates in multiple markets and manages a complex technological infrastructure. Therefore, the speed of development cycles is a critical competitive variable.

During 2025, the group kicked off a structured AI adoption program within its engineering teams. The goal wasn't just to experiment. It was to scale. So, they chose tools that were already mature: Codex and ChatGPT from OpenAI.

The case study published by OpenAI shows the results of this integration. Plus, it breaks down how the tech team actually works day-to-day. It's a handy reference for anyone thinking about taking a similar route.

The adoption timeline: three distinct phases

AutoScout24's program didn't start with massive implementation. Instead, it followed an incremental logic. First, the team identified the most repetitive tasks: generating boilerplate, writing unit tests, and reviewing technical documentation.

Later, adoption extended to code review workflows. Codex was integrated as an assistant in the CI/CD pipeline. Thus, developers started receiving contextual suggestions directly in their work environment.

Finally, in the third phase, the focus shifted to code quality . ChatGPT was used to analyze recurring error patterns and suggest targeted refactoring. As a result, the number of production bugs has measurably decreased.

The numbers emerging from the case

The OpenAI document doesn't publish all metrics in detail. However, some indicators emerge clearly. Development cycles have shortened. Test coverage has increased. Furthermore, time spent on low-value-added tasks has significantly decreased.

These results are not isolated. Similarly, research by McKinsey on the economic potential of generative AI indicate that developers using AI tools complete tasks up to 50% faster. Therefore, AutoScout24's data fits into an established trend.

In particular, the case highlights an often underestimated aspect: the impact on the onboarding of new developers . With Codex ready to help in context, onboarding times got shorter. This is a real competitive edge, especially when tech talent is hard to find.

Winners and losers in the engineering ecosystem

Who benefits from a well-structured adoption like AutoScout24's? First and foremost, senior developers. Freed from repetitive tasks, they can focus on architecture and complex problem-solving. Additionally, QA teams benefit from broader and automated test coverage.

On the contrary, junior profiles who don't adapt are at risk of losing their position. However, this isn't new information. It's a pattern already observed with every technological automation cycle. Therefore, the correct response isn't to resist adoption, but to accelerate training.

Among other things, there is a third player who gains less visibly: the business . Shorter cycles mean reduced time-to-market. Consequently, the ability to respond to market changes improves. For AutoScout24, operating in multiple European countries makes this advantage even more relevant.

SHM Studio's take: what applies to Italian SMEs

The AutoScout24 case is often seen as an example reserved for large organizations. We at SHM Studio we do not share this interpretation. In fact, the operational principles applied are scalable downwards.

An SME with a team of 3-5 developers can adopt Codex for test generation and code review. Additionally, it can use ChatGPT to speed up technical documentation and debugging. The costs to access these tools are affordable. Therefore, the barrier is not economic: it's organizational.

The real obstacle for Italian SMEs is the lack of a structured adoption framework . Without a clear methodology, AI is introduced sporadically. Consequently, results are discontinuous and difficult to measure. This is exactly the problem AutoScout24 solved with its three-phase approach.

To learn more about structuring a similar path, it is useful to explore the SHM Studio AI services , designed specifically for medium-sized businesses.

Still under construction: unresolved challenges

The AutoScout24 case study is a positive one. Still, it wouldn't be right to paint it as totally smooth sailing. Some hurdles are still there, even for a well-organized setup like this.

First of all, the prompt governance . When dozens of developers use ChatGPT autonomously, output consistency is not guaranteed. Therefore, internal guidelines on the use of AI tools need to be defined. This requires time and organizational oversight.

Furthermore, there is the issue of vendor lock-in remains open . Relying exclusively on the OpenAI ecosystem exposes you to lock-in risks. Gartner research on the AI Hype cycle highlights how tool diversification is a best practice for mature organizations.

Finally, the issue of ROI measurement . Reducing development cycles is measurable. But quantifying the impact on long-term architectural quality is more complex. This is a work in progress that AutoScout24, like many other organizations, is still building.

Next moves: what to do now so you don't fall behind

The AutoScout24 case suggests some concrete operational directions. Therefore, it's useful to translate these into priority actions for Italian teams.

• Map repetitive tasks in the current development workflow. These are the ideal candidates for initial AI integration. Furthermore, they are the ones with the quickest ROI to measure.
• Define baseline metrics before introducing the tools. Without a starting point, it's impossible to measure improvement. Consequently, adoption remains anecdotal.
• Train the team on using Codex and ChatGPT effectively. It's not just about having access to the tools. Specifically, it's about building skills in prompt engineering and critically reviewing the outputs.
• Structure governance with internal guidelines on using AI in code. This includes policies on copyright, security, and output quality.

For SMEs that want to start this journey, the digital marketing services and the web solutions from SHM Studio can support the team in defining a coherent roadmap. Furthermore, for those operating in B2B, the LinkedIn campaigns represent an effective channel for communicating technological evolution to your stakeholders.

Also, it is worth considering how AI adoption impacts the SEO Strategy and on content production. In particular, the SEO copywriting benefits from the same tools used in engineering, applied to editorial production.

In short: a model to study, not to copy

AutoScout24 has built a solid case study. However, the value is not in replicating it verbatim. Instead, it lies in understanding the underlying principles: incremental adoption, rigorous measurement, structured governance.

These principles are valid regardless of the organization's size. Therefore, even an SME with limited resources can draw concrete operational insights from this journey. The difference between those who adopt AI effectively and those who experiment without results is almost always methodological, not technological.

To delve deeper into the topic or to receive an assessment of your context, you can contact SHM Studio or explore related articles on Blog . Finally, for those evaluating investments in google ads campaigns integrated with AI workflows, the time to structure a coherent strategy is now.