New Zealand brokers wanting to know how far AI is changing the insurers they place with have a new reference point, although it comes with caveats. A KPMG survey of insurance leaders found that insurers are directing nearly half their AI budgets to operational and back-office efficiency, against 5% to 10% for new products and revenue models, and that only 11% say they have the data foundation and governance needed to scale.
The findings come from a discussion board of 44 insurance leaders across 20 countries, held in May, supplemented by a separate KPMG survey of 53 insurance transformation leaders. Most participants were in Europe and North America, base sizes on individual questions range from 35 to 44, and New Zealand is not broken out. KPMG describes the results as directional. Insurance Business reported the global findings when the survey was released.
For New Zealand brokers, the survey is more useful as a set of questions than as a benchmark.
Activity is concentrated in efficiency. Some 71% of respondents mainly use AI for content generation or automating routine tasks, 57% have built agents or decision-support engines for underwriting, and 29% run front-to-back processes through agents or automation. While 92% say AI is driving cost and efficiency transformation, only 25% say it is driving growth.
Just 3% are functionally redesigning claims management, even though claims is where many insurers report AI-driven change is most visible.
That gap matters for brokers. Claims turnaround and the quality of claims decisions are what clients judge their insurers on, and what brokers defend at renewal. If AI investment is going mainly into back-office efficiency, brokers are entitled to ask insurers what it has changed in claims and underwriting turnaround, beyond content generation.
Executives see urgency but differ on how far to go. Some 77% agree that insurers which fail to redesign their enterprise architecture for AI will lose competitiveness within five years, yet 63% agree most insurers can stay competitive by adding AI incrementally to existing systems.
About 45% place themselves in the top quartile of AI transformation, and none say they are significantly lagging, which KPMG reads as a sign that some may be overestimating their progress. Matthew Smith, KPMG UK’s global lead for insurance strategy and transformation, said the data points to “a notable gap between AI vision and reality.”
The report also points to gaps in accountability. Only 18% say they have a clear AI vision with aligned leadership, 45% place AI ownership with the technology function alone, and 15% have AI governance fully integrated into strategic planning. Just 11% describe their view of AI’s return on investment as very clear, and 8% rate their workforce as highly proficient with AI tools, although 54% say they provide effective training.
Brokers appear in the survey only in small numbers. The report says 71% of brokers in its sample reported limited clarity on AI’s return, and 86% were using external solutions. But with seven brokers among the participants, those figures represent roughly five and six people, so they say little about brokers generally.
The reliance on external tools is still worth noting. Many New Zealand brokerages use AI through vendor products rather than building their own, which raises the question of who is responsible when those tools get something wrong.
That question is already on the regulator’s agenda. The Financial Markets Authority (FMA) has been examining the use of AI in financial advice, and IB’s coverage of that work has highlighted the risk that AI advice tools may fall outside existing rules, and that professional indemnity cover may not respond to losses arising from them.
For brokers, that brings the KPMG findings closer to home. The same questions they might put to insurers (what AI is being used for, who is accountable for it and how its value is measured) apply equally to their own businesses, particularly where AI tools are bought from third parties.
KPMG also warns that the biggest disruption may come from outside traditional insurance. Smith said well-capitalised organisations, such as pension funds and large corporates with good data, may no longer need a traditional policy to take on risk, which bypasses the industry’s business model rather than competing within it.
For brokers, the survey suggests three lines of questioning. With insurers: what AI has changed in claims and underwriting turnaround, beyond content generation and routine tasks. On accountability: who within the insurer owns AI decisions, and how it measures their return. And internally: which AI tools the brokerage itself relies on, who supplies them, and whether the firm’s professional indemnity cover would respond if those tools produced poor advice or errors.
