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Artificial Intelligence is rapidly moving from experimentation to infrastructure in actuarial work. AI systems are beginning to influence decisions that were historically driven by statistical models, expert judgment, and regulatory constraints. This session focuses on understanding what is happening under the hood of modern Generative AI systems, particularly large language models and AI agents. What does “attention” mean in technical terms, and why is it foundational to how these systems process information? How do agentic systems differ from classical predictive models? And critically for actuarial practice: where does predictability break down?
We will examine both the capabilities and the limitations of AI. In domains characterized by uncertainty, feedback loops, and human behavior, no system, human or machine, offers perfect foresight. Understanding these boundaries is essential for responsible adoption. The objective is not to replace actuarial judgment, but to augment it, while ensuring that humans remain accountable for decisions in high-stakes contexts.
In this web session, we aim to deepen the understanding of how GenAI models work and why and how they understand digital context in the way humans understand broader context. We also want to shed light on the limitations of GenAI capabilities, as well as human limitations, when it comes to predictability of systems of complex and dynamic nature, which occur in nature, societies and finance and why humans therefore need to stay in the loop when AI work results are used for that matter.
Early-bird discount is available for bookings made by 28 August 2026. |
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Coming soon... |
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Solvency II Update | 16 June 2026
Causal AI for Actuarial Models | 17 June 2026
How to Read the IFRS Balance Sheet for Insurers | 24 June 2026
Explore our website for more information and discover all our upcoming events. For more insights, updates, and a bit of actuarial fun, feel free to follow us on LinkedIn! |