Careers in AI: The New Zealand Landscape

When people think about AI careers, they usually think Silicon Valley. But Aotearoa has a growing AI ecosystem that's worth paying attention to — especially if you want to build technology that serves a small, diverse, and community-minded country.

We surveyed the landscape. Here's what we found.

Wellington: Government and public sector

Wellington is the centre of New Zealand's public sector, and government agencies are increasingly adopting AI. Stats NZ, the Ministry of Social Development, ACC, and the Department of Internal Affairs are all exploring or deploying machine learning tools.

Roles in this space often combine technical skills with policy understanding. If you're interested in AI governance, algorithmic accountability, or responsible AI deployment, Wellington is arguably the most interesting place in the country to work.

Key organisations:

• Stats NZ — data science and statistical modelling
• NZQA — exploring AI for credential assessment
• MBIE — innovation policy and AI strategy
• Various Crown Research Institutes — applied AI research

Auckland: Startups and scale-ups

Auckland has the largest concentration of AI startups in New Zealand. Companies like Soul Machines (autonomous animation), Imagr (computer vision for retail), and Xtended AI are building products for global markets.

The startup ecosystem is smaller than overseas, but that's not necessarily a disadvantage. In a small company, you're closer to the problem, you ship faster, and you learn across the stack.

Christchurch and beyond

Don't overlook the regions. The University of Canterbury has strong AI research programmes. AgriTech companies across Canterbury and the Waikato are using ML for precision agriculture. And remote work means geography matters less than it used to.

What employers want

Based on conversations with hiring managers at our Industry Night events, here's what NZ employers look for in AI roles:

1. Python proficiency — still the lingua franca of ML
2. Understanding of ML fundamentals — not just library calls, but understanding why algorithms work
3. Communication skills — can you explain your model to a non-technical stakeholder?
4. Domain knowledge — understanding the problem space matters as much as the algorithms
5. Ethics awareness — increasingly, companies want people who can think about the societal impact of what they're building

What you can do now

If you're a VUW student thinking about AI careers:

• Join VicAI — our events connect you directly with industry professionals
• Do a summer research project — VUW's School of ECS runs summer scholarships
• Build a portfolio — GitHub projects, blog posts, and workshop contributions all count
• Learn the fundamentals — COMP309 (Machine Learning) and SWEN432 (Advanced Data Engineering) are solid starting points
• Think broadly — AI careers aren't just for CS graduates. Data analysts, policy advisors, UX designers, and ethicists are all needed

The AI job market in NZ is small but growing fast. The students who start building skills and connections now will be well positioned.