Insurers are currently facing the challenge on AI budget, as nearly half of it go to operational and back-office efficiency, compared with only 5-10% for new products and revenue models.
This is the findings of a recent survey by KPMG, revealing that just 11% have a very clear view of AI return on investment.
Only 11% report strong data foundations and governance to scale AI, while just 8% rate their workforce as highly proficient in AI tools.
The study found that 45% of insurance executives polled place themselves in the top quartile for AI transformation, yet functional redesign and reimagining remain rare across core insurance services.
Seventy-seven percent believe failing to redesign their enterprise architecture for AI will undermine competitiveness within five years, but 71 percent still use AI mainly for content generation or routine task automation.
For corporate CFOs and finance leaders across Asia-Pacific, KPMG’s findings highlight a growing gap between AI investment and the ability to demonstrate measurable business value.
The relatively small percentage claiming to have a very clear view of its return on investment raises a critical question for finance leaders: are AI investments delivering sustainable financial returns, or are organisations relying too heavily on adoption rates and efficiency gains as indicators of success?
CFOs have a key role in establishing performance measures that link AI spending to tangible outcomes, including lower operating costs, shorter processing cycles, improved risk management and new revenue opportunities.
The findings also underscore the importance of strengthening data governance, workforce capabilities and enterprise architecture before scaling AI across the business.
For APAC CFOs, this presents both a financial and strategic challenge: balancing near-term efficiency gains with longer-term investment in data infrastructure, employee training and business-model innovation.
As AI adoption accelerates across industries, finance leaders will need to work closely with technology and operational teams to prioritize investments, clarify accountability and ensure that AI initiatives generate measurable returns while supporting the organisation’s long-term competitiveness.
Additionally, according to KPMG, while much of today’s AI activity is focused on productivity gains and targeted use cases, their report suggests the next phase is likely to center on redesigning customer journeys, operating models and decision-making processes around AI.
Over the longer term, KPMG says AI could enable new approaches to insurance, helping insurers move beyond risk transfer towards more proactive forms of risk management and prevention.
