Most insurance carriers have yet to embed artificial intelligence into their core operational workflows, according to Hardeep Gulati, CEO of core systems provider Duck Creek. Speaking in mid-June 2026, Gulati said there are still "very few cases" of carriers using AI for functions such as underwriting, claims processing, or policy administration.
The statement highlights a persistent gap between the industry's high-profile AI pilots and the technology's integration into systems of record. Gulati believes insurers need to embed AI into core operations without sacrificing governance or regulatory control.
Why AI in core insurance remains rare
Core insurance systems handle sensitive customer data and are subject to strict regulatory oversight. Carriers face significant hurdles in validating AI models for compliance, particularly for decisions that directly affect policyholders. The limited adoption also reflects the challenge of integrating modern AI tools with legacy infrastructure, which still underpins many insurers' critical processes.
For professionals tracking the evolution of AI for Insurance, the slow pace of core adoption serves as a reminder that operationalizing AI requires more than technical capability. Governance, explainability, and regulatory alignment must be built into the deployment from the start.
Governance shapes the path forward
Insurers operate in heavily regulated environments where decisions must often be auditable. Gulati's emphasis on preserving governance points to a central tension: AI models that cannot explain their reasoning may introduce unacceptable risk. Without clear frameworks, many carriers will continue to limit AI to non-core activities like marketing or customer service.
Why this matters for insurance professionals
Insurance professionals should expect AI to gradually move toward core workflows, but on a timeline dictated by regulatory clarity and internal governance readiness. The professionals who map those requirements now - designing audit trails, stress-testing models, and building cross-functional oversight - will position their organizations to adopt AI responsibly when the technology matures for core use.
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