Two Letters and Four Principles.

However, we are also aware of the risks associated with the use of AI. Data protection, security, or ethical questions – there are many challenges that we are addressing intensively. That is why a responsible approach to AI is a matter of course for us. We want to seize the opportunities while keeping our ethical and legal standards in mind.

To ensure that we develop and use AI responsibly, we defined our own principles for dealing with AI back in 2019 and anchored them company-wide in our integrity code. These principles serve as a guideline and help us to find the balance between innovation and responsibility.

The AI Principles are part of our risk-based AI Governance approach, which aims to ensure compliance with legal requirements and ethical standards. To keep up with the global dynamics of AI regulation, we can integrate new requirements into this adaptive approach as needed.

Both – AI Principles and AI Governance – are intended to strengthen trust in our company, our products and services – and at the same time provide all colleagues with guidance on how to deal with AI.

AI is not an end in itself. Whenever we use it, it should deliver genuine added value. This is preceded by a transparent evaluation process: Will our products, services, and processes actually become faster and more efficient through AI? What benefits does the use of this technology have for different target groups? Is our data set representative and of high enough quality to strengthen fairness and inclusion? We do not leave these considerations to a machine. Humans remain in control.

In school, our teachers taught us a special rule for solving math problems: not only the correct answer counts, but also the way to get there. It's similar with calculations that are carried out with the help of AI. For example, if a piece of software evaluates a large amount of data to make forecasts about future market developments, it should be transparent which parameters it considered in the analysis. That way, we can explain any possible unintended bias – and eliminate it.

Digital services have become an integral part of our everyday lives. They would not work without a certain amount of data. This makes it all the more important to ensure that the privacy of customers and employees remains protected. Wherever possible and reasonable, we use artificial or anonymized data sets when testing and training AI. Legal requirements are always mandatory. Data protection is a quality feature for us.

Safety and reliability are an integral part of our brand's core. We therefore apply our high quality standards to AI applications as well. Conscientious training of learning systems, scientifically validated and accepted algorithms, and the use of current technologies form the basis for this. In autonomous driving, for example, reliable AI is safety-relevant - another reason for us to work with precision and a critical mindset when developing new technologies.

This article was last updated in Oktober 2025.