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Welcome to AI Insurer Brief!
Hey it’s Fabio here,
In today’s Executive Series, we’re joined by Alex Harari from Governance AI 360.
Many insurers now have formal AI governance frameworks or policies in place.
The harder part is managing those frameworks in real time, especially as AI use becomes more transformational and regulation becomes more demanding. That creates a clear need to capture AI events with an immutable log, mapped back to inventory, policies, and regulations.
So we focused on a practical question:
What does it take to move from a static governance pack to live AI governance that boards, regulators, and compliance teams can actually rely on?
Alex explained what problem Governance AI 360 is solving, what evidence firms are still struggling to produce quickly, and what “live governance in eight weeks” actually looks like in practice.
1. Alex, for people hearing about Governance AI 360 for the first time, what problem are you solving?
Many insurers now have AI governance policies on paper. The harder part is showing live, attributable evidence of how AI is actually being used, monitored, and overseen in practice.
That is the gap Governance AI 360 is designed to close.
It helps firms move from a static governance pack to a live operating platform that inventories AI assets, classifies them by risk, captures human oversight in workflow, and makes it much easier to produce audit-ready evidence across clouds and vendors.
2) What evidence do boards and regulators now expect that many organisations still cannot produce quickly?
Boards and regulators have moved beyond asking, “Do you have a policy?”
They now want evidence that AI is visible, owned, monitored, and governed in practice.
In most firms, five areas are still hard to produce quickly:
a live inventory of AI use cases, models, and third-party tools in production
named approval and oversight records, with clear accountability
ongoing monitoring for bias, drift, and performance issues
end-to-end lineage showing where outputs came from
audit-ready logs that can be reconstructed without weeks of manual effort
For many insurers, that evidence is still spread across spreadsheets, tickets, and email threads.
That is the gap the platform is built to address.
3) What does “live governance in eight weeks” actually look like - and what does success look like at that stage?
“Live” means the governance layer is running in the client’s own environment, connected to a real LLM use case rather than sitting in a sandbox.
By that stage, the firm should be able to see AI interactions being logged, flagged where needed, reviewed by the right teams, and tied back to an inventory, governance workflow, and audit trail.
Success at that point is not theoretical.
It means compliance can review a real flagged interaction, the business owner can see how the use case has been classified, technology can confirm data remains in the firm’s own environment, and the executive sponsor can see a clear evidence pack showing how governance is operating in practice.
From there, the next phase is about extending that working foundation across the broader AI estate.
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