Last month, we referred to the public consultation on the “European Initiative on Climate Resilience and Risk Management.”
This initiative was deemed necessary by the European Commission, as it has become increasingly clear that Europe is facing ever more severe losses, disasters, and costs due to climate-related impacts and risks.
This month, we present some interesting points highlighted in FERMA’s (Federation of European Risk Management Associations) response to this consultation.
A first observation is that FERMA’s 2024 Risk Managers Survey showed that climate change adaptation, the transition to carbon neutrality, and natural disasters are considered the three most significant risks for the next decade. Moreover, more than 50% of risk managers believe that certain risks — particularly natural catastrophes — will become uninsurable.
A second key point in FERMA’s response is the recognition of an urgent need to close the protection gaps against climate change and to strengthen risk management at the corporate level. As FERMA notes, since natural catastrophes (NatCat) are becoming more frequent and more destructive, organizations are increasingly exposed to financial uncertainty and limited insurance coverage.
Finally, FERMA stresses that bridging the insurance protection gap requires not only financial mechanisms but also robust risk management practices across all sectors. It also emphasizes the need for greater awareness and education among organizations and citizens about climate risks and insurance coverage.
Another topic we are focusing on this month concerns the MIT study “The GenAI Divide: State of AI in Business 2025.”
This study, which has received considerable attention recently, adopted a rather pessimistic tone — leading to some eye-catching headlines that, in our view, served mostly as clickbait. According to the study, 95% of organizations are not seeing meaningful returns from their investments in Generative AI (GenAI).
But is that really the case? What do the data behind these percentages actually show?
We take a closer look and conclude that the “95%” figure does not mean that AI is failing. On the contrary, it indicates that most organizations have not yet moved beyond the experimentation phase to full-scale implementation and therefore are not yet seeing direct financial returns. The technology is still in an early stage of adoption, and its most important benefits often do not appear immediately in financial statements (P&L).
We believe that pioneer organizations — the 5% — are already reaping significant benefits. This shows that the path forward exists; what is needed is strategy, patience, and proper training. Companies that adopt early and learn to leverage AI tools effectively are likely to gain a competitive advantage in the medium term.
Lastly, we also explore this month whether climate models are indeed reliable. Some people question them — not to say they question climate change itself. The answer comes from a recent analysis titled “Evaluating the Performance of Past Climate Model Projections” (Hausfather et al., 2020), published by the American Geophysical Union.
The analysis concludes that, for decades, climate models have captured the actual trajectory of global warming with impressive accuracy.
It seems, therefore, that we can trust climate models — and, in fact, it is essential that we do. The planet is changing, and this change brings challenges for people, as well as risks — and potentially opportunities — for organizations.
We hope you find this month’s articles insightful and engaging.
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