Preparing for the AI of tomorrow: A call to KiwiSaver providers
Preparing for the AI of Tomorrow: A Call to KiwiSaver Providers

Preparing for the AI of tomorrow: A call to KiwiSaver providers

Clive Fernandes
Clive Fenandes
- CEO | Co-Founder
As a financial adviser and founder of National Capital, New Zealand’s largest KiwiSaver advice fintech, Clive has direct experience with the challenges faced by superannuation providers and advisers.

KiwiSaver providers must prepare today for the AI of tomorrow to stay competitive in a rapidly evolving financial landscape. Declining inference costs, stronger security, and the rise of small language models are reshaping the industry. Those who adapt early will be the leaders of the future.

With inference costs dropping, deploying advanced AI solutions will soon become more affordable and scalable.

Enhanced security features address critical risks, ensuring trust and compliance in sensitive financial ecosystems.

Meanwhile, the shift towards small, efficient language models opens doors for customisable, cost-effective AI deployments tailored to specific business needs.

To fully leverage these advancements, KiwiSaver providers must start preparing today, laying the groundwork to thrive in a smarter, faster, and more accessible AI-driven future.

The declining costs of AI inference and the impact of DeepSeek

The cost of AI inference, the process of using AI models to deliver results, is steadily declining, and innovations like DeepSeek show this may continue.

This trend aligns with Jevons Paradox. Microsoft CEO Satya Nadella noted: “As AI gets more efficient and accessible, we will see its use skyrocket, turning it into a commodity we just can’t get enough of.”

As AI inference costs fall, the demand for AI applications will rise exponentially, leading to accelerated adoption across industries.

DeepSeek’s novel training and post-training techniques will make the development of models more efficient and pave the way for enhanced inference efficiency. Enterprises can deploy more innovative AI solutions at a lower cost, enabling broader adoption and scalability.

For KiwiSaver providers, this shift offers immense potential. Reduced inference costs make deploying advanced AI for customer service, personalisation, and compliance far more feasible.

Preparing now for these advancements ensures that providers can harness smarter, cheaper AI solutions to remain competitive and deliver enhanced value to their clients in the future.

The rise of small language models

The shift towards small language models (SLMs) and open-source AI is transforming how businesses approach artificial intelligence, and KiwiSaver providers stand to benefit significantly from this change. Unlike large, resource-intensive AI systems, SLMs are designed to be cost-effective, scalable, and adaptable, making them an ideal choice for providers aiming to enhance operational efficiency and client engagement.

From an enterprise perspective, SLMs offer numerous advantages. They allow businesses to scale their AI deployments cost-effectively. For KiwiSaver providers, this means deploying AI solutions that enhance customer service, personalise financial advice, and streamline compliance without the significant running costs typically associated with larger AI systems.

SLMs also bring enhanced agility to the table. Their shorter deployment times and easier customisation align AI capabilities more closely with evolving business needs, enabling KiwiSaver providers to remain competitive in a dynamic financial landscape.

Additionally, SLMs better address perennial concerns such as data privacy and sovereignty. When hosted on-premises or within private clouds, SLMs allow organisations to meet stringent regulatory requirements while maintaining robust security—an essential consideration in the financial services industry.

Another overlooked advantage of SLMs is their reduced energy consumption compared to larger models. For KiwiSaver providers, this supports corporate sustainability initiatives and aligns with the growing demand for environmentally responsible business practices.

Security in AI is becoming mainstream

As AI grows more sophisticated, so do the security measures around it.

AI security is becoming mainstream as practitioners and organisations actively address vulnerabilities and threats inherent in AI systems. Efforts to mitigate risks such as misuse, exploitation, and adversarial attacks are advancing rapidly, as evidenced by initiatives like the Generative Red Team Challenge at DEF CON 2023, which tested models from major players like OpenAI, Google, and Meta.

Organisations like MITRE have introduced frameworks like ATLAS, which apply systematic approaches to AI threat characterisation, complementing tools like ATT&CK for broader cybersecurity.

The development of the AI Vulnerability Database further enhances the ability to catalogue and address failure modes across AI systems. Techniques from software supply chain security and safety assurance practices are being adapted to secure AI, focusing on auditability, governance, and proactive risk mitigation.

These efforts pave the way for standards, norms, and regulations enabling organisations to integrate AI responsibly and securely in an increasingly AI future.

For KiwiSaver providers, this is critical. The sensitive nature of client data and regulatory obligations in the financial sector requires robust security features to ensure trust and compliance.

Providers need to think ahead about how to incorporate AI securely and responsibly into their operations, creating a framework that is resilient to future risks. Starting this work now will save significant headaches when AI adoption becomes non-negotiable.

The mindset shift: Preparing for tomorrow’s AI

The fundamental message is clear: AI will keep getting better, faster, and more capable. However, unlocking its full potential requires starting now. This preparation involves,

  1. Investing in Infrastructure: Ensure your systems are AI-ready, with scalable architecture and robust data governance.
  2. Upskilling Teams: Equip your teams with the skills to understand, deploy, and manage AI solutions.
  3. Strategic Planning: Begin aligning your business strategy to take advantage of tomorrow’s AI capabilities rather than being constrained by today’s limitations.

AI developers and companies also need to adopt this mindset. It’s not enough to build solutions that work within the constraints of current AI. Developers should anticipate the exponential improvements in AI capabilities and build with those advancements in mind, ensuring their solutions remain relevant and competitive.

The future is now. Start preparing.

KiwiSaver providers have a tremendous opportunity to lead the financial services industry into the AI-driven future. By preparing today, you’ll position your business to benefit from tomorrow’s advancements and create a foundation for sustained innovation and growth.

The AI of tomorrow will be smarter, faster, and more accessible than we can imagine.

The question is: will you be ready to make full use of it?

In this article...

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