SEA’s insurers face a new question: what happens when customers have agents?
Insurance has spent the past year experimenting with generative AI in the most obvious corners of the enterprise: summarising emails, extracting details from claims forms, drafting responses for call-centre agents, and speeding up document-heavy back-office work. Those are useful gains. But a new whitepaper by Google Cloud and CoverGo argues that they may also be […] The post SEA’s insurers face…
Insurance firms in Southeast Asia are grappling with a growing concern as they integrate generative AI into their operations. While automation has improved efficiency, the whitepaper published by Google Cloud and CoverGo warns that treating AI as isolated productivity projects may be a distraction. The authors suggest that this approach is akin to the "Kodak moment" – an industry optimizing an existing business model while the market shifts elsewhere.
For insurers, this means that enhanced workflow automation alone will not suffice if the fundamentals of claims, underwriting, and distribution are being redefined by autonomous software agents. The paper highlights studies from MIT and BCG, which indicate that 95% of organizations struggle to derive tangible returns from agentic AI.
It argues that many institutions still view AI as a series of isolated productivity projects rather than a new operating layer for the business. In Southeast Asia, where customers are mobile-first and digital wallets, embedded finance, and platform ecosystems are transforming financial services, this distinction is crucial. If insurance becomes a machine-speed negotiation between multiple software actors, with customers using AI agents to optimize claims submissions and various stakeholders leveraging agents to submit, verify, or challenge information in real-time, insurers will need to adopt a new operating model.
The paper proposes the concept of an "Agentic Core Operating System," emphasizing the need for a technology foundation where human experts and AI agents collaborate as coordinated teams. This approach involves moving away from monolithic, hardcoded systems towards modular architecture, standardized protocols for agent-to-agent communication, and protocols that enable safe transactions.
While insurers should not replace humans with autonomous machines, they must create a foundation that enables seamless coordination between human experts and AI agents to navigate the evolving landscape of insurance.
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