Insurance firms across the Asia-Pacific region are significantly increasing their financial exposure to alternative private markets and artificial intelligence (AI). However, pervasive legacy computer systems and outdated data infrastructures are severely hindering their capacity to manage these increasingly complex investment portfolios. Industry data indicates a widening gap between the strategic ambitions of these financial institutions and the technical limitations of their operational frameworks, raising critical questions about institutional readiness across the regional sector.
The convergence of aggressive asset diversification and rapid digital transformation has laid bare structural inefficiencies within these organisations. As market dynamics grow more intricate, the reliance on decades-old computing architectures threatens to undermine the precise execution of sophisticated investment mandates and the seamless deployment of automated tools.
Rising Allocation to Alternative Private Markets
A comprehensive regional survey conducted by Clearwater Analytics Holdings, Inc., which gathered insights from 150 senior insurance executives, revealed a major shift in asset allocation strategies. The findings show that Asia-Pacific insurers collectively oversee an estimated $3.8 trillion in total assets. Within the next five years, these organisations project to allocate approximately one-third (33%) of their combined investment portfolios to alternative assets, including private debt, private equity, infrastructure projects, and other non-traditional instruments.
This projected allocation marks a significant increase from the current level of 20%. Despite this aggressive investment trajectory, an overwhelming 93% of the surveyed senior executives explicitly stated that their legacy technology infrastructure is already actively limiting and restricting their daily business operations. Shane Akeroyd, the Chief Strategy Officer and Asia-Pacific President at Clearwater Analytics Holdings, Inc., highlighted the structural challenges in an industry report published in April.
“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 stated.
The statistical data compiled by Clearwater Analytics further underscored specific institutional weaknesses regarding data management. Only 42% of the surveyed insurers rated their existing internal data integration systems as excellent. Furthermore, technological support for highly complex financial assets scored the lowest across the study, with a mere 23% of respondents expressing confidence that their current systems can adequately process and handle the intricate alternative portfolios they are actively building.
Artificial Intelligence Ambitions Face Infrastructure Barriers
Simultaneously, a separate market survey published in April by credit rating and research agency A.M. Best Company, Inc. detailed the sector’s outlook on emerging technologies. The research, which was originally conducted in November 2025, indicated that nearly 60% of insurance industry respondents expect artificial intelligence to completely reshape their fundamental business models within the next one to three years.
Financial commitment to this technology remains strong, with 66% of the executives surveyed stating that their organisations intend to increase their dedicated AI spending over the next 12 to 24 months. However, a significant implementation gap exists, as only about 20% of the participating organisations described themselves as being at an advanced stage of actual AI adoption. Sridhar Manyem, the Senior Director for Industry Research and Analytics at AM Best, pointed out the operational risks of deploying advanced technology on unstable digital foundations within the published report.
“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 explained.
He further noted that insurance firms possessing robust data governance frameworks and modernised computing platforms would encounter significantly fewer difficulties when attempting to integrate AI capabilities into their core operations.
Drivers and Deterrents of Technological Integration
According to the analytical data provided by AM Best, the primary catalyst driving corporate investment into artificial intelligence remains institutional productivity. Approximately 68% of the survey respondents identified improving overall employee productivity as a top organisational goal. This was followed by 47% who cited the lowering of operational costs as a primary objective, and 37% who pointed toward achieving superior underwriting and risk pricing accuracy through automated systems.
Conversely, the research agency identified three definitive roadblocks preventing successful institutional adoption of AI across the region:
-
Data Readiness: The widespread prevalence of poor-quality or uncontextualised corporate data.
-
Security and Privacy: Concerns regarding data protection and regulatory compliance.
-
Legacy System Integration: The technical friction caused by attempting to overlay modern AI applications on top of decades-old computing architectures.
The collective findings from both industry reports demonstrate that while Asia-Pacific insurers possess clear investment and technological objectives, their underlying core systems remain fundamentally unequipped to manage the heightened complexities of alternative markets and advanced analytics without substantial infrastructure upgrades. The inability to seamlessly process multi-variable alternative assets alongside modern analytical programs underscores the urgent necessity for a comprehensive overhaul of core operational technologies within the regional marketplace.