APAC Insurers Embrace AI Despite Tech Hurdles

AI adoption in APAC insurance — stronger than expected

There is a prevailing stereotype that traditional insurers move slowly when it comes to innovation. The Moody’s survey challenges that in the APAC AI in 2026: 4 Trends You Need To Know region. Among 21 insurers (12 life and 9 P&C) across China, Hong Kong Special Administrative Region, Japan, Korea and Taiwan, more than 80 % reported using AI and realising benefits.

In short: insurers in the region are not just experimenting with AI – many are actively embedding it into operations. China, in particular, appears to be leading the pack, with insurers there reporting more diversified benefits from AI than their regional peers.

This signals a shift: not ‘if’ but ‘how’ AI is being used. For insurers in Singapore, Vietnam, Australia or Malaysia, the implication is clear: regional competitors may already be advancing into more mature phases of AI deployment.

What insurers are using AI for, and what they’re gaining

One of the most striking findings is the breadth of AI use‑cases, and the specific outcomes being reported.

Key use‑cases

1. The top use‑case cited is marketing, sales and distribution: simply put, leveraging AI to identify prospects, optimise channel strategies or personalise offers.
2. Among product lines, motor insurance and health insurance lead AI adoption. The reason: large volumes of data (vehicle telematics, claims histories, health records) gives AI rich material to work with.

Measurable benefits

1. Operational efficiency: 81 % of respondents reported increased productivity or improved efficiency.
2. Customer experience: 57 % say that their customer‑facing outcomes have improved thanks to AI.

In China, insurers appear to be further ahead: the survey suggests that Chinese firms not only deploy AI across front‑line functions but increasingly into underwriting, claims automation and product innovation.

From the vantage point of this article: for an insurer in Singapore or Thailand considering AI, these are useful benchmarks. Efficiency gains and enhanced experience are achievable, but expect those to come via well‑defined use‑cases rather than broad experimentation.

The technological and regulatory headwinds

Even as adoption is rising, the survey reveals significant friction points. These are not unique to APAC – but they are acute given the diversity of markets and legacy systems in the region.

Data quality and model transparency

A majority of respondents flagged data quality and accessibility as the main barrier to AI deployment. If the data feeding the models is fragmented, outdated or inaccessible, even the best‑designed AI system will struggle.

Linked to this is concern over the opacity of AI models and outputs. Many insurers remain uneasy about ‘black box’ decisions being made by algorithms, particularly around underwriting or claims resolutions.

Legacy IT‑infrastructure and talent shortage

For those insurers who had not yet adopted AI, the survey identifies clear blockers:

1. Lack of skilled talent capable of building or operating AI systems
2. Need to modernise IT systems, ensure data compatibility and remove obsolete technology silos

In many Asian markets, insurers still operate with decades‑old core systems, making integration of AI challenging. This points to the need for a phased approach: prioritise data infrastructure, talent build‑out, then scale AI use‑cases.

Regulation and governance

The evolving regulatory landscape adds another layer of complexity. The survey notes that regulators across APAC are actively reviewing frameworks around AI, cyber‑security, model governance and data usage.

In practice this means insurers must not only execute AI initiatives but ensure they are compliant with dynamic rules a dual challenge of transformation plus compliance. For example, governance of model explainability and audit trails is becoming increasingly important.

The message is: AI isn’t simply a technology project, it is a governance and compliance project too.

What next for APAC insurers and their peers

Given the findings, insurers in the region might consider a three‑pronged approach:

1. Prioritise high‑impact use‑cases. Build AI where data volumes are high and outcomes measurable (e.g., motor and health insurance, marketing/distribution). Use those successes to build internal momentum.

2. Invest in data and infrastructure first. AI won’t deliver unless data is clean, accessible and anchored in modern systems. Likewise, governance frameworks and internal talent need to be part of the build‑out.

3. Treat regulation as part of the strategy. Ensure that AI governance, model transparency, data ethics and cyber‑risk are built into the roadmap — not bolted on afterwards. In markets across APAC, regulatory expectations are rising.

For markets such as Singapore, Malaysia, Indonesia or even Australia, the survey's insight is instructive: peers are already embedding AI and realising benefits. Falling behind could mean losing competitive edge in efficiency, customer experience or product innovation.

Final thoughts

The survey by Moody’s demonstrates that insurers in Asia‑Pacific are not just experimenting with AI — they are deploying it and seeing returns. Yet the path is still far from smooth. Data, legacy systems and regulations remain very real obstacles.

For insurers across the region, whether in Hong Kong doing bancassurance, in Japan: Principles-Led Governance with Strong Industry Input simplifying claims, or in Korea scaling digital distribution, the message is clear: AI is already part of the game. The question now is how quickly and how well it can be scaled — not if.