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Ask what is transforming the insurance landscape in Asia today, and the answer comes without recourse to futurist abstractions or industry jargon: the sector is being fundamentally rewritten, driven not only by technological advancement, but by the specific force of generative artificial intelligence ( GenAI ).
The shift is already reshaping strategic priorities for insurers across the region, from Tokyo to Jakarta, prompting far-reaching conversations at the highest levels. One of the figures helping guide this transition is Violet Chung, senior partner at McKinsey & Company.
In a recent discussion with The Asset, Chung outlined how GenAI has progressed well beyond the stage of experimentation or novelty. Across key functions such as claims processing, underwriting, and customer engagement, it’s no longer centred around just productivity, but on reimagining operational workflows from the ground up.
What once required 20 steps across five separate departments can now, as described by Chung, be consolidated into a single, seamless transaction. In several markets, this transformation is already underway, enabled by paperless, automated processes that retain human oversight where critical judgment is required.
As Chung emphasizes, the rise of GenAI is not a tactical shift, it represents a structural transformation on the scale of an industrial revolution. “This is not a short-term play,” she notes. “You can’t just throw tools at it. You need to rethink workflows, governance, culture – and make AI part of how you think.”
For insurers, this means integrating AI not as an overlay, but as a foundational element of strategy and operations.
In Asia, where a largely underinsured population converges with some of the world’s most advanced fintech ecosystems, the implications are particularly profound. GenAI is not merely enhancing the insurance sector; it is redefining how individuals engage with the concepts of protection, risk and long-term resilience. And, as Chung underscores, this transformation is only at its inception.
Personalization at scale
In Asia’s more mature insurance markets, such as Japan, South Korea, Hong Kong and Singapore, where digital infrastructure is advanced but customer acquisition has largely plateaued, GenAI is creating value through a different lens. By transforming how insurers engage with customers, AI is enabling a shift from passive interest to active decision-making.
“If you read something 10 times,” Chung observes, “it changes you.” GenAI delivers that kind of education at scale, hyper-personalized, linguistically nuanced and tailored in tone. Increasingly, this intelligent content is not just a means of engagement, she notes, it is becoming a core component of the product itself.
A similar transformation is unfolding across emerging markets, where insurance penetration has historically been hindered by distance, cost and lack of awareness. Here, AI is breaking down those barriers through targeted content and modular products delivered via smartphones, reaching populations in rural or underserved areas where agents often have limited access.
In culturally diverse regions, such as Southeast Asia, Chung highlights the unique strength of AI in localizing both language and context, making it a critical enabler of inclusive growth across the sector.
However, the promise of GenAI extends well beyond speed and efficiency. Its true differentiator lies in contextual intelligence, Chung notes, an area where legacy systems and conventional analytics have long fallen short.
Today, when a prospective customer begins exploring insurance options, AI enables the delivery of offerings that feel highly personalized rather than generic. Agents are no longer reliant on static brochures; they are equipped with dynamically generated simulations, tailored to individual customer profiles and life stages.
This evolution naturally brings concerns around accuracy to the forefront. The potential for AI hallucinations is well documented. However, progressive insurers are responding with robust safeguards, Chung highlights, embedding human oversight within AI-enabled workflows.
Whether in risk evaluation, claims adjudication or marketing communications, AI may generate the first draft, but it is human expertise that validates and finalizes the outcome. The model’s output, in this emerging paradigm, is not a decision, but a recommendation.
Redefining risk, roles, revenue
One area where GenAI is demonstrating unexpected strength is in the prediction and pricing of risks that have historically been difficult to quantify.
In the case of climate-related perils or catastrophic events, AI models are increasingly able to extract signals from unstructured data sources, such as animal migration patterns or subtle environmental indicators, providing insurers with earlier and more accurate warning systems.
In the context of fraud detection, GenAI is evolving into a behavioural radar, capable of identifying nuanced patterns and anomalies before losses are incurred.
Despite these advances, AI is unlikely, Chung maintains, to displace agents or brokers in the near term. On the contrary, she foresees a redefinition of their roles.
With routine tasks increasingly automated, insurance professionals are positioned to shift their focus towards advisory functions and high-value engagement. This shift is particularly significant in Asia, where personal relationships and trust remain central to insurance decisions. “The integration of AI may not diminish the human element,” Chung observes, “but rather enhance it.”
Some of the most transformative applications of GenAI, Chung adds, are emerging in the realm of product design. The future she envisions includes entirely new insurance formats, dynamic, usage-based and highly personalized.
Examples include micro-crop coverage that automatically activates during adverse weather seasons, or travel insurance triggered the moment a policyholder’s phone registers in a foreign country. These offerings demand more than just AI-driven customer interaction; they require real-time capabilities in underwriting, pricing and claims adjudication.
This same intelligence is also being leveraged on the asset side of the balance sheet. Insurers, particularly those with long-duration liabilities, such as life insurance providers, are exploring AI tools to support investment decisions that align with their future obligations.
This includes identifying stable, long-horizon assets, such as green infrastructure or biodiversity-linked investments.
With environmental disclosure frameworks like the Task Force on Nature-related Financial Disclosures gaining momentum, insurers are beginning to recognize that aligning sustainability goals with capital deployment is not only responsible governance, it is also sound investment strategy.
These could prove to be critical tools as the region faces increasing environmental volatility.
