And for those who’ve missed it, that’s a good thing.
In the last few years, Generative AI has been riding a wave of intense hype, with companies across industries rushing to integrate AI into their operations. From chatbots to automated marketing tools, financial institutions worldwide experimented with AI-driven solutions, often with mixed results.
Now, AI is entering what Gartner calls the “Trough of Disillusionment”, a phase where unrealistic expectations give way to a more pragmatic focus on real-world ROI.
For KiwiSaver providers, the AI hype cycle largely passed them by. Unlike banks and global asset managers, KiwiSaver firms didn’t rush into AI-driven customer engagement tools, chatbot advisors, or machine-learning-powered investment recommendations. Instead, the industry has remained focused on traditional ways of servicing members.
But skipping the hype cycle is an advantage. While others spent time and money testing AI solutions that didn’t always deliver, KiwiSaver providers can now bypass the experimental phase and move straight into AI projects that create real value.
AI in financial services: from hype to practicality
Historically, every major technology follows a predictable pattern of adoption. The Gartner Hype Cycle describes this journey in five stages:
- Innovation Trigger: A new technology emerges, sparking excitement and speculation.
- Peak of Inflated Expectations: Early adopters experiment aggressively, often with unrealistic expectations.
- Trough of Disillusionment: Many AI projects fail to deliver, leading to a market correction.
- Slope of Enlightenment: Businesses start focusing on AI applications that actually work.
- Plateau of Productivity: AI becomes a normal, widely adopted part of business operations.
Right now, Generative AI is sliding into the Trough of Disillusionment. After a frenzy of AI experimentation in banking, wealth management, and insurance, many financial firms are realizing that not all AI projects deliver real returns. As a result, companies are shifting away from experimental AI applications and investing in practical, revenue-generating AI solutions.
For KiwiSaver providers, this is the perfect entry point. Instead of spending resources on AI-powered chatbots that struggle with compliance or AI-generated financial advice that lacks regulatory clarity, KiwiSaver firms can immediately focus on AI applications that improve efficiency, reduce costs, and automate compliance-heavy processes.
Slow and steady wins the race?
While banks and fund managers worldwide have tested AI-driven solutions, KiwiSaver providers have yet to make significant moves in AI adoption.
This means they now have the opportunity to leapfrog the trial-and-error phase and focus directly on AI solutions that deliver proven business impact.
Instead of playing catch-up with AI hype, KiwiSaver firms can align AI investments with their core operational challenges:
- Regulatory Compliance: Managing strict financial regulations without adding cost and complexity
- Operational Efficiency: Reducing the manual workload of customer service and back-office teams.
- Cost Management: Keeping administrative costs under control while scaling member services.
For KiwiSaver providers, AI’s real value lies in back-end automation – the processes that cost the most in time, effort, and compliance risk.
1. AI-Driven compliance automation
Regulatory compliance is one of the biggest operational challenges for KiwiSaver providers. Every member interaction, whether an inquiry about hardship withdrawals, contribution adjustments, or fund switching, must comply with strict financial regulations.
How AI can help:
- Automate compliance checks on customer communications.
- Ensure responses to members align with KiwiSaver regulations.
- Reduce manual oversight by flagging potential compliance risks before they occur.
Why it matters:
- Reduces human error in client communication.
- Lowers compliance costs by reducing manual monitoring.
- Enhances consistency in member interactions, improving trust and service quality.
2. Process automation to reduce manual workloads
KiwiSaver providers still rely heavily on manual processing for tasks like hardship applications, fund transfers, and member onboarding. These processes are often time-consuming, repetitive, and prone to bottlenecks.
How AI can help:
- Automatically extract, process, and verify member documentation.
- Streamline fund transfers and contribution adjustments.
- Automate member queries related to account status and investment allocations.
Why it matters:
- Cuts processing times, allowing providers to scale services efficiently.
- Reduces administrative overhead, freeing up teams to focus on higher-value work.
- Improves service levels, enhancing member satisfaction and trust.
The shift in AI investment: less hype, more ROI
Across the financial industry, AI spending is shifting. Investors and executives no longer approve AI projects just to be seen as innovative. Instead, they are asking:
- Does this AI project reduce costs?
- Does it eliminate inefficient manual processes?
- Does it improve regulatory compliance?
For KiwiSaver providers, this signals the right time to invest in AI, not for innovation’s sake but for measurable business benefits. Firms that embrace AI strategically will see gains in efficiency, compliance, and cost savings, while those that delay adoption will find themselves playing catch-up in a more competitive landscape.
KiwiSaver’s AI moment: now or never
The next five years will define the KiwiSaver AI landscape. Providers who adopt AI today will be the ones leading the industry tomorrow.
- AI isn’t about hype anymore. It’s about execution.
- The winners will be those who automate, streamline, and enhance compliance.
KiwiSaver providers have the opportunity to build the AI foundation now before competitors get ahead.
The AI hype cycle is over.
The real AI revolution is just beginning, and KiwiSaver firms have the chance to be on the right side.
