Build or Buy AI in Insurance?

With GenAI tools becoming more accessible, building internal solutions has never looked more achievable. And for a lot of carriers and brokers, that’s prompted a fair question, why wouldn’t we just build this ourselves?

In this InsTech podcast episode, Scrub AI co-founders Nicola Turner and Alex Ley sit down with Matthew Grant to unpack what the build vs buy decision actually involves when the workflows are complex, the data is messy, and the tolerance for error is low, as it is across catastrophe modelling, exposure management, and pricing.

In this conversation, Nicola and Alex explore:

• Why the conversation has intensified as AI moves into formal strategy
• Why generative AI can accelerate development but does not remove the complexity of insurance data
• The danger of plausible but wrong outputs in exposure management and catastrophe modelling
• Why deterministic AI still plays a critical role in delivering consistent, renewal-ready data
• The hidden cost of technical debt when insurers attempt to build internally
• Why maintaining and iterating AI tools is often harder than building the first version

This is a useful listen for anyone who’s being asked to define an AI strategy, build a business case for partnering, or simply make sense of what’s realistic and what isn’t. It won’t tell you what to do but it will give you a sharper framework for thinking it through.

You can listen to the full episode on the InsTech podcast or below. And if the topic’s on your agenda at the moment, we’re always happy to chat.