At the recent ITI USA Roundtable, Insurants convened a dynamic group of senior insurance executives and technologists to explore how firms were unlocking insight using (Gen)AI to create competitive edge. The discussion revealed both the opportunities and imperatives facing carriers as they modernize in an increasingly complex, AI-enabled environment.
Commercial Lines: Still Evolving, Still Expanding
Participants agreed: despite being a mature segment, commercial lines are far from static. Demand for bespoke, highly tailored risk protection is driving continued evolution of traditional products—while entirely new lines are emerging to address risks in areas such as cyber, climate, supply chain, and gig economy workforces. Meeting these needs requires faster insight, better data, and more adaptable systems.
“Clients don’t want off-the-shelf coverage—they want risk protection tailored to their risk appetite.”
GenAI: Augmenting the Specialist
AI (and GenAI) is supercharging the insurance workflow across a breadth of use cases ranging from high volume industrialised processes to one off complex analysis and summarisation. If (Gen)AI is to scale without creating duplication and overhead it needs to support this breadth and augment the specialist.
Insight that Informs Decisions and Integrates with Existing Platforms
The group emphasized that GenAI must also inform decisions. Embedding insight into existing systems, decision logic, and workflows is critical. Wholesale replacement of core platforms is expensive and time consuming, so firms need to be clear on the edge of these emerging capabilities.
Decision Control and Accountability
As AI takes on more analytical work, decision control remains non-negotiable. Carriers must maintain governance over AI-informed decisions to align with internal risk appetite frameworks and to comply with increasing regulatory expectations.
This includes:
- Transparent decision flows
- Human oversight of critical outcomes
- Explainability of model reasoning
“You can use the model—but you still own the decision.”
Avoiding Lock-In, Owning the Outcome
Participants also cautioned against relying on a single LLM or proprietary AI model. In a rapidly evolving landscape, model agility is a strategic advantage. Firms should invest in modular, model-agnostic platforms that allow them to select and switch between LLMs, tune models with proprietary data, and remain compliant across jurisdictions.
Regulators are watching closely. Emerging guidance makes it clear that firms must be able to explain, audit, and stand behind any AI-supported decisions. Accountability cannot be outsourced to a black box.
The Path Forward: Embedded, Accountable AI
As one participant summarized:
“GenAI can’t just be a lab experiment. It has to be part of how we operate—and it has to be something we can own and defend.”
At Insurants, we’re committed to helping carriers unlock the value of GenAI with confidence—transforming insight into action, embedding AI into the heart of the operating model, and ensuring firms stay in control of their decisions.
Because in commercial insurance, speed matters. But trust and accountability matter more.
