Innovation and AI
Innovation and AI
RESPONSIBLE AI

Smart progress,
safe hands

Artificial Intelligence is a core driver of our efficiency and growth. We recognise that it can also have unintended impacts on sustainability – from increased energy and water demands to social concerns around data ethics and job security.

Our approach: Leading responsibly

Our approach to responsible AI is anchored in our Code of Conduct and various internal guidelines, where AI shall strengthen our standards for quality, security, ethics and sustainability – without compromising them. We also prioritise "human-in-the-loop" systems, in which people’s participation leads to AI enhancing human decision-making rather than replacing it.

Ethical governance and safety

We have established a governance framework that aims to minimise AI’s negative impacts and risks.

Integrating AI Risk
Our multidisciplinary AI Risk Management Committee unifies expertise so that risks, such as bias awareness and social implications, are integrated into our broader risk frameworks.
Implementing AI safely
We maintain internal guidelines covering data protection (GDPR), intellectual property and output reliability – so that the customers of our companies can use AI tools with confidence.
Mitigating bias
We work to identify and implement guardrails to reduce human biases in AI models that could lead to inequality, with the goal of ensuring our software remains fair and inclusive for everyone.

Environmental sustainability

We recognise that AI demands significant energy and water resources. We strive to decouple our AI innovation from environmental impact through various initiatives:

⏵ GreenOps

We apply GreenOps principles that lower our value chain emissions, which includes choosing EU-based public cloud locations with lower carbon intensity for AI model usage where feasible.

⏵ AI Guidelines

Our internal AI Code of Conduct, complemented by our Sustainable AI Guidelines, empowers employees to use AI responsibly and efficiently — protecting confidential data, verifying output, being selective with reviewed tools, and using 'right-sized' models and efficient prompting to reduce their digital footprint.

⏵ Operational efficiency

Beyond innovation, we explore ways to increase operational efficiency through AI. Our experience shows that when applied strategically, it can reduce the total carbon footprint of both the software development process and the products the customers of our companies use every day.

⏵ Empowering our people

Minimising AI bias

Our AI principles mandate that our systems are fair and inclusive. Although we cannot fully control biases inherent in base models, we strive to monitor and refine our systems to align with the ethical standards in our Code of Conduct.

AI Transformation Index

To monitor the human side of workplace shifts related to AI, we use an AI Transformation Index in our employee engagement surveys. This helps us measure tool access, perceived value, and organisational alignment while addressing concerns like job security or deskilling.

Taking accountability

Employees are guided to cross-check AI outputs and are instructed never to use results they do not understand, cannot explain, or that do not refer to credible sources.

For founders and partners

Our Responsible AI framework provides a secure and ethical environment to scale innovations and companies. We provide the guardrails and data ethics expertise needed to grow AI products that are compliant, sustainable and trusted by the market.