Artificial intelligence is reshaping the insurance industry at an unprecedented pace. At Munich Re, AI is a core enabler of our multi-year strategy Ambition 2030 and is embedded across the entire organisation to enhance underwriting and claims. In this interview, Fabian Winter, Chief Data & AI Officer, explains how Munich Re is scaling AI through a structured and cost effective, enterprise-wide approach, driving efficiency and unlocking new opportunities in an increasingly data-driven world.
 

AI is currently the subject of a lot of hype. What’s your perspective?

Fabian Winter: At Munich Re, we see Artificial Intelligence as a strategic capability embedded across the entire organisation and a core enabler of our Ambition 2030. Our goal is to use AI to strengthen underwriting and claims, improve efficiency and unlock new growth opportunities.

What makes Munich Re’s approach different?

What makes our approach distinct is that AI is now being deeply integrated into our core processes. In recent years, we have built a strong foundation in data and technology across Munich Re, from e.g. advanced analytics and scalable data platforms to generative AI solutions. This gives us a solid starting point to translate the next wave of AI innovation into tangible business value. AI’s full potential in reinsurance is still unfolding, but the direction is clear: organisations that successfully combine data, technology and deep domain expertise will be best positioned to lead. With our structured approach and continued investment in innovation, Munich Re is well ready to harness AI as a driver of competitive advantage, strengthening today’s business while shaping the opportunities of tomorrow.

What enables this enterprise-wide adoption of AI?

It comes down to three key elements: technology, governance and people. We have established a global technology stack together with a group-wide AI governance framework to ensure scalability and compliance. At the same time, we invest heavily in our people through dedicated Data and AI teams, targeted recruitment and long-term initiatives such as our global Data and AI Academy. This holistic setup ensures that AI adoption is not limited to experts but becomes part of how all employees work across functions and regions.

How is AI contributing to both efficiency and growth?

AI delivers efficiency by reducing manual effort, enabling greater automation and consistency, and allowing our experts to focus on higher-value activities such as analysis and decision-making. As AI adoption increases globally, entirely new risk categories are emerging, ranging from algorithmic risks to cyber threats. This creates demand for new insurance solutions, and we are actively developing offerings to address these AI-related risks. In this way, AI is not only improving our current business but also expanding our future market potential.

Can you give an example how AI helps us shaping the future of the insurance industry?

A clear example can be found in Life and Health (Re-)Insurance. Underwriting requires significant manual effort to collect, structure and assess information. AI, greater computing power and access to larger datasets enable insurers to assess risks more accurately, leading to a deeper understanding of individual risk profiles and expanding insurability. They help us to support insurers in expanding their coverage to individuals with complex medical conditions that may previously have led to exclusions. This represents a significant advancement for the industry and the insureds themselves.

Another strong example is our generative AI platform Phoenix, which transforms unstructured documents into structured, AI-ready data. This allows us to extract and summarise information at scale, creating the basis for better decision-making and automation in processes such as claims handling or risk analysis.

The greatest value will come from the seamless integration of human expertise and AI. While AI excels at analysing data, identifying patterns, and automating routine tasks, human underwriters provide the critical judgement, contextual understanding, and responsibility required for sound decision-making.