AI Monday is more than just a regular event – it’s a platform for open exchange among those shaping the future of artificial intelligence. Co-organised by Ray Sono and DAIN Studios, this format fosters discussions around the pressing issues of AI adoption.
AI Monday offers deep insights from various perspectives, valuable networking opportunities and inspiration for those who want to do more than just understand AI – but actively use it. On Monday 3 February 2025, Dirk Hofmann, co-founder and CEO at DAIN Studios Germany, and Johann Bayerl, Division Lead Digital Communications at Ray Sono, moderated an AI Monday discussion on how AI is becoming an essential part of corporate infrastructure.
From FOMO to FOBLB: the new AI realism
Just two years ago, the hype surrounding generative AI, fuelled by ChatGPT, dominated the corporate world. Curiosity, enthusiasm and FOMO (fear of missing out) drove its rapid development. But over the past year, the narrative has shifted and FOBLB (fear of being left behind) has taken over.
Companies now recognise that they need AI – but many are not yet prepared to scale it. Poor data quality, rigid corporate structures and a lack of workflows and skilled professionals are major obstacles to seamless implementation. While China is advancing disruptively and the US is pouring massive capital into AI, Europe often seems stuck in regulatory debates. The pressing question is: How do we keep up?
AI in practice: a reality, not just vision
Artificial intelligence (AI) is transforming the insurance industry - fundamentally. Julia Krezdorn, Head of Artificial Intelligence at Munich Re, showcased compelling examples of how AI is optimizing both internal processes and external products.
Munich Re’s AI team develops practical solutions to make internal workflows more efficient - such as automating contract review and data processing. But AI isn’t just streamlining internal operations. Across industries, various AI-powered solutions are already helping insurance companies assess risks more accurately and accelerate processes.
One of the most transformative examples is the evolving role of underwriters in reinsurance. Until now, their work has been heavily shaped by preparatory tasks like research and data entry. AI has the potential to significantly reduce these tasks in the future, freeing up experts to focus on strategic core activities like risk assessment and customer advisory - a shift that is already becoming reality.
These developments make one thing clear: AI is not just a technological advancement - it’s a key driver of transformation in the insurance industry.
AI governance and the EU AI Act: a regulatory roadblock?
Paloma Laye (AI Quality Advocacy Manager, TÜV SÜD) addressed a major regulatory milestone - the EU AI Act, the world’s first comprehensive AI legal framework. This legislation classifies AI systems into four risk levels, ranging from prohibited and high risk to low and minimal risk.
Highly regulated industries, such as healthcare and law enforcement, must meet strict transparency and compliance requirements. While these measures uphold ethical standards and accountability, the ongoing debate around their implementation feeds concerns about potential challenges for innovation - particularly for start-ups navigating compliance complexities.
The balance between self-regulation and legal oversight remains intricate. Large companies can and do develop in-house AI governance policies, while smaller firms often lack the resources to do so. However, companies that proactively integrate AI into their strategy can gain a competitive advantage rather than merely reacting to legal constraints.
Investments and trends: where is capital flowing?
Jessica Lieber (Principal, 10x Founders) provided compelling insights into the AI investment market. In Q4 2024, half of global venture capital was invested in AI, with a significant portion flowing into foundation models with general-purpose applications.
In her trend forecast for 2025, she anticipates a rapid surge in funding rounds for industry-specific AI solutions – spanning both horizontal and vertical models. At the same time, embodied AI is on the rise, as AI advancements increasingly extend into the physical world.
The reality of AI in enterprises
Patrick Simon (Program Manager, New Digital Tech/GenAI, ZEISS) highlighted the five biggest challenges companies face when implementing new digital technologies such as generative AI. Central to this is the balance between technological innovation and corporate responsibility. While companies seek to harness the potential of AI, they must simultaneously uphold high standards in data security and compliance.
Moreover, successfully implementing AI systems requires more than just technical expertise. What truly matters are measurable business value, well-thought-out processes, and the systematic integration of employees. He particularly emphasized the importance of a well-balanced strategy: On the one hand, companies must be able to respond quickly to new technological developments; on the other hand, it takes time to embed lasting change within the organization.
Another key focus of his analysis was the role of employees in the transformation process. Instead of introducing AI solely from the top down, he advocates for a combined approach: Strategic initiatives from leadership should be complemented by bottom-up innovation, empowering employees across all departments to identify and leverage AI potential.
Is the ‘iPhone moment’ for AI agents still a long way off?
The panel discussion made it clear that AI agents are not yet indispensable in daily life – as noted by Jessica Lieber, the much-anticipated ‘iPhone moment’ has yet to arrive. However, as AI agents become capable of independently managing complex tasks like scheduling and decision-making, this will change. Adoption is expected to start at the individual level before spreading into business applications, as people who integrate AI into their daily routines will naturally seek similar support in the workplace.
2025 AI predictions: what’s next?
Models like DeepSeek are emerging as challengers to OpenAI, signalling a shift in the competitive landscape. AI development is moving beyond pure research, with a growing emphasis on real-world applications. AI agents will continue expanding into more industries, accelerating their role in various sectors. The ability to distinguish real from AI-generated content will become increasingly crucial, as synthetic media continues to rise. At the same time, the risks associated with AI-powered chatbots – especially ethical concerns – will become more apparent. AI workflows are also evolving, steadily progressing towards full automation.
Conclusion: perfection is not the goal
Julia Krezdorn (Head of Artificial Intelligence, Munich Re) brought the discussion to a close with a thought-provoking insight: ‘We expect 100% accuracy from machines – something no human has ever achieved.’
AI doesn’t need to be flawless to be valuable. The key lies in its responsible use and scalable implementation. 2025 may mark the shift from an experimental phase to AI becoming an indispensable core infrastructure for businesses.
Join our AI Monday Munich Meetup group – don’t miss your next chance to network and be part of the conversation!
https://www.meetup.com/ai-monday-munich/
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