Designing AI for underwriters 2026
In this IIL seminar, hosted by Convex, Waswate Ayana and Amil Malik explore the practical realities of building and embedding AI for underwriting in a human-centric way.
Artificial Intelligence promises to revolutionise the business of underwriting, but the ‘Field of Dreams’ approach: ‘If you build it, they will come’, is not a model for success!
In this session, the speakers talk about the investment case for AI-augmented underwriting workbenches. Moving beyond the hype, the panel explore how to design for uncertainty (surfacing imperfect data rather than hiding it) and how to manage the distinct demands of different stakeholders. They also discuss the nature of product adoption and the factors that lead to success.
Learning objectives:
- The Investment Case: explore the motivations behind investing in AI capabilities and how different personas within an insurance company perceive value in different ways, making investment decisions more complex
- De-risking the Investment Case: understand how a human-centric design philosophy directly reduces commercial and regulatory risk, satisfying the competing demands of CFOs, CTOs, and CUOs
- Navigating the Human-AI Spectrum: reflect on the spectrum of AI intervention (from supportive augmentation to full automation) and learn why “designing for uncertainty” is more effective for adoption than striving for a “black box” of perfect answers
- The Reality of Adoption: gain an appreciation of the partnerships and organisational heavy lifting required to drive the use of AI solutions, learning why flexibility in underwriting working practices is just as critical as the technology itself
- Finding clarity in chaos: methodologies to create time and space for high-value decision-making in a noisy world
- Designing for decisions: How to design AI-enabled products that truly reduce cognitive load
Speakers
- Waswate Ayana, Head of Product Management, Convex
- Amil Malik, UX and Design Strategy Lead, Convex
- Chair: Greg Butera, Wordings Counsel & Legal Technology Manager, Convex
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