With the Executive Journey, InsurTech Hub Munich connects InsurTech Hub Munich executives from insurance, technology, and consulting—on equal footing and with a focus on implementation. QAware contributes insights on Agentic AI and data literacy. Dr. Josef Adersberger discusses the potential of Agentic AI—and why the insurance industry needs to take action when it comes to data literacy.
A conversation with Dr. Josef Adersberger, Managing Director of QAware & Advisory Board Member at InsurTech Hub Munich
Dr. Josef Adersberger
Dr. Josef Adersberger is managing partner of QAware GmbH, a leading software company based in Munich. Through his work, he has played a key role in shaping cloud migration and automation in the insurance industry in major projects. In 2021, he co-founded the venture capital fund Twip Impact Ventures. He has been a member of the supervisory board of the VHV Group since 2023. With his experience in innovation strategies and digitalization, he brings valuable impetus to the work of InsurTech Hub Munich.
Why are formats such as the Executive Masterclass needed right now?
The current climate is creating significant pressure for change—even among insurers. The key task for senior management is to keep a clear head: set an effective focus, think in terms of goals, and proceed with determination. The Executive Masterclass supports this by gathering collective knowledge through C-level interviews and presenting it in a concise format that creates space for discussion.
Why is the combination of data strategy and agentic AI so crucial for insurers?
Every insurance executive should ask themselves: How do we win? The answer lies in productivity and the ability to offer products that make a difference for customers. Agentic AI is the technological basis for both. A smart data strategy is necessary because agents need to interact with core systems and data in order to be effective.
It is no longer a question of whether AI can deliver. It is a question of when and how well—and who will be the first to get there. 44% of insurers have launched initial pilot projects, and 56% already have agents in productive operation. They see the greatest potential in claims processing, sales, and customer service. It's about the need to address the shortage of skilled workers and offer high service quality.
What are the key success factors for future-proof data literacy?
Data literacy means that a company treats its data like a strategic product. Data must be findable, interpretable, and usable. This requires a clear data strategy and culture—and it must be a top priority. In organizational terms, this means establishing central data platforms and gradually making data available as products along specific use cases. Regulatory and data protection requirements should be integrated intelligently from the outset.
How does QAware position itself in this context?
We are transformation partners and enablers. This begins with the joint development of an integrated AI and data strategy. Unlike traditional consulting firms, we always keep an eye on feasibility. Two points are particularly important: establishing a clear link to the business strategy and determining the starting point—the existing data, the AI applications that already exist, but also the business processes in place and their AI automation potential.
We act as "bloodhounds" searching for AI and data use cases with high business value and take responsibility for implementation: setting up an AI and data platform and implementing data pipelines – scalable and ready for production.
What specific lessons have been learned from the ITHM network?
From the ITHM formats, we have derived over twenty specific challenges and best practices for AI application at insurers. A key learning: Successful AI transformation is a change issue. It is about bringing together specialist departments and IT—in cross-functional teams with shared responsibility.
Second point: Many remain in experimental mode for too long. Those who make progress set clear priorities, focus on the business case with measurable ROI, and have the courage to cancel projects. "Stop starting – start finishing" is the central motto.
How important will data culture be for competitiveness?
Data culture is becoming a key competitive factor. Data is needed for AI applications, which in turn are needed to increase productivity. This is necessary in order to counteract the shortage of skilled workers, enable attractive rates with a low combined ratio, and offer high service quality. Data is also needed in underwriting and pricing in order to outperform the competition.
Those who use data in a targeted manner, automate processes, and make data-based decisions gain a significant advantage. It is about integrating data and AI expertise deep into the DNA of the organization. Companies that take this seriously will become more efficient, innovative, and customer-friendly.
