Artificial intelligence (AI) technology will play a pivotal role in shaping the new regulatory framework for iGaming in New Zealand.
AI can be used to personalise experiences, fortify security, ensure compliance and build trust. It will be a game-changer for the Kiwi betting sector.
AI is already a big Hit in the APAC region
AI tech has already made its mark in the Asia-Pacific (APAC) region. More than half of businesses have deployed chatbots, co-pilots or AI assistants, more than in Europe and North America.
For New Zealand, which is aiming for a tightly controlled and fully regulated online environment, this APAC trend supports a compliance-first approach. AI runs on real-time data, but regulation determines what data can flow and why it does.
The new framework will allow AI tools to improve harm detection and security, while constraining models that optimise engagement or spending. This follows the APAC model, where governments define boundaries so innovation can scale safely.
New Zealand’s regulatory framework must take explainability, audit logs and human oversight into account to show maturity. AI is important in this new landscape, but it must also meet set standards.
Why Safety Systems Will Dominate Early Compliance
Another APAC trend worth noting is the redefinition of AI return on investment.
Boards want to see more measurable outcomes and are now increasingly viewing security and customer operations as the clearest return on investment (ROI) lanes heading into next year. This way of thinking aligns with New Zealand’s regulatory priorities.
A new licensing regime that requires operators to show that they have harm minimisation measures in place will naturally favour AI systems that can prove outcomes, not only intent.
Practically, this means AI systems used for player risk scoring, identity verification and detecting anomalies are easier to justify to both regulators and operators.
These systems will prevent underage and multiple accounts, reduce charges and flag risky plays. From a regulatory angle, they also generate data trails that should be audited.
New Jersey’s iGaming sector offers a useful AI template for other jurisdictions to follow. The New Jersey Division of Gaming Enforcement acknowledge that regulated operators use automated, machine-learning tech to monitor transactions as part of their anti-money laundering measures.
According to FinCEN data, US casinos filed over 1.5 million Suspicious Activity Reports between 2019 and 2023. Digital monitoring tools have to be used to manage this volume.
It may not have been directly branded as AI regulation, but the US is one of the most prominent examples of advanced analytics being used to make compliance possible.
New Zealand will likely move in the same direction. Many of the reputable betting platforms listed on comparison website bettingtop10.co.nz already use AI to support their operations.
Ethics, Data Plumbing and the Limits of Personalisation
Per data from Confluent, almost half of APAC firms complain about insufficient real-time data infrastructure as a barrier to scaling AI.
Not having a proper data infrastructure in gambling creates an ethical risk as models trained on partial or soiled data can misclassify vulnerability or apply unnecessary interventions, ruining user experience.
New Zealand’s regulatory framework can establish expectations for data governance, limitations and related areas. Regulators could indirectly shape model behaviour. AI that monitors behaviour for harm prevention needs different safeguards from AI that recommends content.
The Kiwi government can take inspiration from the US. Regulators in New Jersey and Pennsylvania, had to tighten their rules after operators became overly aggressive with their marketing tactics.
AI cannot simply be allowed to operate without controls. There must be checks and balances, falling in line with APAC’s push towards more responsible AI use.
How AI Will Shape Enforcement and Trust
AI’s biggest influence on New Zealand’s iGaming framework could be cultural, not even technical, as regulators around the globe switch towards a more outcome-focused oversight model.
The technology will speed up this shift because it changes how decisions are made and how quickly harm happens. If the algorithm intervenes in seconds, regulatory bodies will demand explanations to prove that the intervention was fair and explainable.
Here again, the US shows how it is done. The American Gaming Association claims that the regulated online gaming market recorded channelisation rates of over 80 precent in mature states.
This remarkably high number stems from the trust consumers have in licensed operators. That trust comes from its enforcement capacity, which depends on automated monitoring and analytics.
New Zealand’s coming regulatory framework will be judged similarly based on how well it reduces harm, enforces compliance and inspires confidence that licensed operators are safer than offshore alternatives. The Kiwi government will regulate the outcomes and demand transparency in the systems that deliver them, while leaving AI to do what it does best behind the scenes.
AI won’t redefine gambling in NZ, but it will play a key role in how it is responsibly governed.
