Getting Real Value from AI in Insurance with Sam Worthington, CDO at Crux Underwriting

In this episode of Databricks Diaries, Andy Davis is joined by Sam Worthington, Chief Data Officer at Crux Underwriting, for a practical conversation on how insurance organisations can get real value from AI.Sam shares his perspective on where AI is most useful in insurance, particularly around data ingestion, extraction, underwriting augmentation, bordereaux processing, fraud detection, operational efficiency and decision support.The conversation explores why AI is not a shortcut around poor data foundations, and why insurers need to think carefully about trust, confidence scoring, conflicting data sources and when human expertise still needs to sit in the loop.Sam also explains why London Market insurance presents a different challenge to more standardised personal lines environments. When risks are complex, specialist and often difficult to compare, AI needs to support underwriting expertise rather than simply replace it.Key topics include:Why AI value in insurance often comes down to efficiency and decision supportThe role of AI in underwriting augmentationHow insurers can use AI for ingestion, extraction and cleaner data captureWhy speed to quote matters for MGAsThe importance of data foundations before applying AIHow to manage conflicting insurance data, such as slips, emails and submissionsWhy human referral and confidence scoring are critical in underwriting workflowsThe difference between top-down AI use cases and bottom-up agent adoptionWhy London Market insurance is “lumpy and bitty” compared with more standardised marketsHow to identify the right AI use cases by starting with real business pain pointsSam’s advice is clear: start with a genuine problem, embed the solution into the way people already work, build trust through controls and guardrails, and avoid trying to solve everything at once.A valuable listen for anyone working in insurance, data, underwriting, analytics or AI who is trying to separate practical opportunity from AI noise.