In a recent development that merits attention from technology leaders across New Zealand, the Reserve Bank of New Zealand (RBNZ) has expressed concerns about artificial intelligence's expansion and its potential impact on financial stability. This highlights a critical juncture for technology executives navigating the AI revolution within regulated industries.
The RBNZ's May 2025 Financial Stability Report provides a nuanced view of AI's role in the financial sector. While acknowledging substantial efficiency gains across data modelling, fraud detection, and cyber defence capabilities, the central bank has flagged how technological complexity and increasing dependency on third-party AI service providers might amplify systemic vulnerabilities.
This cautionary stance reflects a broader realisation within regulatory circles: as AI becomes more deeply woven into critical financial infrastructure, its influence extends beyond operational efficiencies to potentially reshape fundamental risk frameworks.
"There is still considerable uncertainty around how AI will shape the financial system," notes the RBNZ report. "While its impact could be positive, especially in enhancing resilience, it could also introduce or amplify vulnerabilities."
Despite these regulatory concerns, organisations across New Zealand and Australia are demonstrating remarkable confidence in AI technologies, particularly generative AI (GenAI) platforms. Current investments are yielding an impressive 44% return on investment—slightly outpacing the global average of 41%.
The business case for AI adoption appears increasingly compelling, with 91% of local organisations reporting improvements in decision-making speed compared to 84% globally. This performance delta suggests New Zealand businesses may be implementing AI solutions with greater effectiveness than many of their international counterparts.
What's particularly noteworthy for technology leaders is the strategic shift in AI application focus. While early AI deployments often targeted back-office efficiency, organisations are increasingly directing these technologies toward customer-facing functions.
This pivot recognises that AI's true value proposition extends beyond cost-cutting to enhancing customer relationships through personalised communications and elevated engagement models. For technology executives, this represents both an opportunity and a challenge: how to harness AI's transformative potential while maintaining the human elements that build genuine trust.
Despite the promising returns, the path to successful AI implementation remains fraught with challenges that technology leaders must navigate:
The report highlights that 63% of ANZ businesses encountered higher-than-anticipated staffing expenses—significantly above the global rate of 48%. This disparity reflects the unique challenges within our regional talent market as organisations expand AI teams and accelerate onboarding efforts.
Technology executives must recognise that successful AI deployment isn't merely a technology challenge but fundamentally a people challenge. The war for AI talent remains particularly intense in New Zealand, where the specialised skill pool is more constrained than in larger markets.
Companies in our region report more frequent difficulties with fragmented data systems and time-consuming preparation tasks, creating implementation delays that can undermine AI initiatives before they begin delivering value.
This finding underscores a critical truth: AI capabilities are only as good as the data foundations upon which they're built. For many New Zealand organisations, legacy systems and siloed data repositories represent significant barriers to AI maturity.
While AI promises to transform customer interactions, industry analysts maintain that certain engagements still require human oversight. Beatriz Benito, lead insurance analyst at GlobalData, notes: "While all in all, AI has the potential of considerably improving satisfaction rates in insurance, the need for the human touch and empathy in engagements continue to limit its full potential."
This perspective highlights the delicate balance technology leaders must strike: leveraging AI to enhance efficiency while preserving the human relationships that ultimately build customer trust.
The RBNZ's stance reflects an evolving regulatory landscape that technology executives ignore at their peril. The central bank emphasises that regulated financial entities must assess and address AI-related exposures within their existing risk management protocols.
This directive signals that AI governance is rapidly moving from a theoretical exercise to a practical requirement. Technology leaders must ensure their AI deployments incorporate robust risk assessment frameworks that satisfy not only operational requirements but also emerging regulatory expectations.
For technology executives navigating this complex landscape, several strategic imperatives emerge:
As regulatory scrutiny intensifies, organisations need governance structures that can demonstrate responsible AI use. This includes:
Before rushing to deploy advanced AI capabilities, organisations must invest in strengthening their data infrastructure:
Successful AI strategies recognise that automation and human intervention aren't competing approaches but complementary forces:
While external vendors can accelerate AI deployment, developing internal competencies remains crucial:
Different sectors face unique challenges and opportunities in AI deployment:
Banks are leveraging AI for credit decisioning, fraud detection, and personalised financial advice. However, algorithmic bias in lending decisions remains a significant risk that requires robust testing and monitoring frameworks.
Insurers are applying AI to claims processing, underwriting, and customer service. As Beatriz Benito notes, the challenge lies in determining which customer interactions benefit from automation versus those requiring human empathy.
Portfolio optimisation, market analysis, and client reporting are prime AI applications in this sector. However, the "black box" nature of some AI algorithms creates transparency challenges that may concern both regulators and clients.
Fraud detection, transaction monitoring, and customer authentication represent high-value AI use cases. Yet dependence on third-party AI providers could create concentration risks across the payments ecosystem.
For New Zealand technology leaders, several factors create a unique operating environment:
Our market size means AI investments must be carefully calibrated—solutions developed for larger markets may not yield equivalent returns in New Zealand without thoughtful adaptation.
With a smaller specialist talent pool, organisations must develop creative strategies to attract and retain AI professionals in an increasingly competitive global market.
New Zealand regulators are likely to follow international precedents while adapting oversight to local market conditions, requiring technology executives to monitor developments across multiple jurisdictions.
Ethical AI deployment in New Zealand must respectfully address Māori data sovereignty principles, which may require specialised approaches not necessary in other markets.
The RBNZ's concerns about AI's impact on financial stability represent an important signal for technology leaders across New Zealand. While AI promises significant efficiency gains and improved customer experiences, its implementation must be guided by robust governance frameworks and a clear-eyed assessment of associated risks.
For technology executives, particularly those in regulated industries, the message is clear: AI adoption should neither be recklessly accelerated nor overly cautious. Instead, organisations need thoughtful strategies that balance innovation with stability, automation with human oversight, and efficiency with trust.
As we navigate this complex landscape, technology leaders who can articulate a vision for responsible AI deployment—one that satisfies regulatory requirements while delivering business value—will position their organisations for sustainable success in an increasingly AI-driven future.
The path forward requires not just technical expertise but strategic wisdom: knowing not only what AI can do, but what it should do within the unique context of New Zealand's financial and business environment.
