How can insurers keep up as private market bets grow?

Only 23% are confident systems can handle complex portfolios.

Asia-Pacific insurers are raising exposure to private markets and artificial intelligence (AI), but outdated systems are slowing their ability to manage more complex portfolios.

“The firms that will lead the next phase of growth in the Asia-Pacific are already asking the right questions: ‘Does our infrastructure match our ambition, and does our scale allow us to compete as this market becomes more complex?’” Shane Akeroyd, chief strategy officer and Asia-Pacific president at Clearwater Analytics Holdings, Inc., said in an April report.

Clearwater surveyed 150 senior executives across the region and found insurers expect to allocate a third of their combined $3.8t in assets to private debt, private equity, infrastructure, and other alternative investments within five years, up from 20% now. At the same time, 93% said legacy technology is already limiting their business.

The findings raise questions about whether insurers can expand into more complex investments without first upgrading core systems and data infrastructure.

A separate survey by A.M. Best Company, Inc. published in April showed nearly 60% of respondents expect AI to reshape their business models within one to three years.
Yet only about 20% said their organisations are at an advanced stage of AI adoption.

The survey, conducted in November 2025, also found that 66% expect to increase AI spending over the next 12 to 24 months.

“AI systems can produce unreliable outputs when underlying data is of poor quality, fragmented across legacy systems, insufficiently governed or lacking appropriate context,” Sridhar Manyem, senior director for industry research and analytics at AM Best, said in the report.

He added that insurers with stronger data governance and modern systems would find it easier to integrate AI into operations.

The biggest driver for AI investment remains productivity. About 68% of respondents said improving employee productivity was a top goal, whilst 47% cited lower operating costs and 37% pointed to better underwriting and pricing.

AM Best identified data readiness, security and privacy, and legacy system integration as the main barriers to AI adoption.

Clearwater reported similar weaknesses. Only 42% of insurers rated their data integration systems as excellent.

Support for complex assets ranked lowest, with just 23% confident their systems can handle the portfolios they are building.

Questions to ponder:

• Can insurers scale private market exposure without rebuilding legacy systems?
• Will AI investment widen the gap between large insurers and smaller players?