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Welcome to AI Insurer Brief!
Hey it’s Fabio here,
In today’s Executive Series, we’re joined by Ben Dulieu, CIO & CISO at Duck Creek.
Across insurance, AI is starting to move beyond isolated pilots and into the workflows where decisions matter most. That shift raises a bigger question for the market:
What does it take for AI transformation in insurance to move toward core decisioning?
Ben explained why insurers are looking beyond systems of record, where AI is creating value first, and why strong foundations in core systems, data, and workflows still determine whether AI delivers real enterprise value.
Let’s dive in!!
My take at the end.
1. Ben, for people who still think of Duck Creek mainly as a core systems company, how would you describe the problem you’re helping insurers solve today?
We’re not just powering insurance operations any longer - we’re powering insurance decisions.
At the foundation, we are still core-systems-based, but the problem Duck Creek is solving today has absolutely evolved.
Insurers are not just looking for systems of record anymore. They are trying to become faster, more intelligent, and more responsive in how they are making decisions across underwriting, claims, and the full policy lifecycle.
The real challenge now is how to operationalise that intelligence in a way that is scalable, governed, and embedded into everyday workflow.
What we are doing is helping insurers move from static core processing to what we call an intelligent core.
That is where data, decisioning, and execution are tightly integrated.
By embedding agentic, explainable AI directly into these core workflows, we are enabling insurers not just to process transactions, but to orchestrate decisions in real time, with full transparency and full control.
It is less about replacing what Duck Creek has already done.
It is more about elevating it.
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2. Duck Creek has recently launched its Agentic AI Platform, including use cases in underwriting and FNOL. Where do you see the strongest interest from insurers?
Underwriting and First Notice of Loss are where speed means value.
That is where AI is proving itself first.
Both of these are high-impact, high-friction points in the insurance lifecycle.
In underwriting, carriers are under pressure to improve speed and precision at the same time.
They want to make better risk decisions while reducing quote turnaround time.
In claims, and particularly at First Notice of Loss, the focus is on improving the overall customer experience while also managing leakage and fraud.
What is really resonating with insurers is the ability to move beyond isolated automation and instead orchestrate these workflows.
These areas matter most because they sit at the intersection of growth, efficiency, and customer satisfaction.
3. One of the more interesting launches was the Agentic Product Configurator - the idea of moving from requirements to deployed configuration faster. What does that change for insurers?
One of the biggest barriers in this space is the cost and the time it takes to implement - that is not just a Duck Creek problem. It is a major challenge in any digital transformation.
The Agentic Product Configurator is fundamentally compressing that cycle.
Insurers can start with business-level inputs — requirements, guidelines, even natural language — and translate that into structured configurations within the Duck Creek platform.
Those configurations can then be validated, refined, and deployed much more quickly, while still keeping human oversight built into the process.
The key benefits go back to the same themes:
speed
consistency
and delivering a level of response that is accurate
4. In your view, what do insurers get wrong when they try to scale AI too early?
The key mistake is treating AI as a layer that you can simply add on top of existing systems, or bolt on at the side, without addressing the underlying foundation.
If the core systems are fragmented, the data is not well governed, the technology is legacy, or the workflows are not clearly defined, AI is probably going to amplify those issues rather than solve them.
That is why so many pilots look promising but are hard to scale, govern, and address properly.
In a regulated industry like insurance, scaling AI is not just about performance - it is about being able to understand, audit, and stand behind the decisions it is making.
The insurers who are succeeding with AI are taking a more integrated approach: modernising the core systems, aligning the data strategy, and embedding AI directly into operational workflows from the start.
That is what enables AI to move from proof of concept and experimentation into real enterprise value.
My Take
AI is moving far beyond experimentation and toward embedded decisioning across underwriting, claims, product configuration, and core workflows.
As Ben highlighted, the real differentiator is not AI itself. It is the combination of modern core systems, trusted data, and governed workflows that allows AI to operate at enterprise scale.
See you on Friday!
Fabio Caravita
Founder, AI Insurer Brief
[email protected]
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