The Business of Tech

The National Party is aiming to introduce legislation for its proposed social media ban for under‑16s before November’s election.
The move, replicating a ban already in place across the Tasman, might look like a neat political fix – but it is far more likely to fail, backfire and leave our kids and critical infrastructure less safe.
That’s the stark warning from veteran tech consultant and internet governance expert Daniel Spector, my guest on this week’s episode of The Business of Tech. Spector, a long‑time KiwiFoo stalwart and current Internet New Zealand board member standing for re‑election, argues that prohibition‑style policies are the wrong tool for the job.
We don’t stop teenagers drinking by banning alcohol. We won’t stop them using TikTok and Instagram by declaring them off‑limits either.
Wait for the VPN boom
Instead, Spector says Australia’s under‑16s ban is already doing something unintended but entirely predictable – upskilling teenagers in VPNs, masking tools and hacking techniques, as they learn how to route around clumsy age‑verification systems and facial recognition.
In his view, New Zealand is on track to copy a model that not only won’t protect children, but will produce a more technically adept generation of young hackers while entrenching a surveillance architecture dressed up as “child safety”.
We examine the deeper question politicians are mostly dodging: why are we attacking the demand side – who can log on – rather than the supply side of harm, like infinite scrolling, rage‑bait design and hyper‑targeted advertising?
Spector highlights recent US court moves that treat addictive features such as endless scroll as “defective by design”, putting liability squarely on Meta and Google, and argues this is the direction New Zealand should be watching - and even replicating.
A golden age of hacking
Spector also lays out why Anthropic’s Mythos and similar cutting‑edge models are likely to usher in a “golden age of attack hacking”, systematically hunting for vulnerabilities in decades‑old code. Criminal groups will get them eventually, and board directors – with the potential to soon face personal and even criminal liability for cyber breaches – are nowhere near ready.
We talk zero‑knowledge proofs, digital identity, data sovereignty, and why outsourcing our safety to offshore tech giants and hurried bans is a dangerous illusion.
You can hear the full discussion with Daniel Spector on The Business of Tech wherever you get your podcasts.
Show notes
A Modest Proposal for the Orderly Dissolution of New Zealand. - Daniel Spector, LinkedIn
The verification layer did say 'yes'. Well... once. - Daniel Spector, LinkedIn
#DigitalSovereignty: A personal professional crisis. And a national one, too. - Daniel Spector, LinkedIn
NCSC got nation-state grade AI. Now what? - Daniel Spector, LinkedIn
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Australian startup Heidi Health has become one of the most visible examples of AI actually shifting the dial on healthcare productivity – and New Zealand is at the forefront of that story.
In this week’s episode of The Business of Tech, I talk to Heidi co‑founder Yu Liu about the company’s journey from student training tool to AI “care partner” for clinicians, and its audacious goal of doubling global healthcare capacity.
Heidi didn’t start life in the emergency department. Yu and his co‑founders first built Oscar, a chatbot that helped medical students practise exam skills – essentially simulated patients for training bedside manner and clinical questioning.
Oscar was useful, but the startup team struggled to find students willing to pay for it. In 2019, Liu and his co-founders, Dr Tom Kelly and Waleed Mussa, pivoted to tackling one of the biggest bottlenecks in healthcare – the hours clinicians lose every day to documentation and administration.
Widespread use in emergency departments
That created Heidi Scribe, an ambient AI scribe that sits in on consultations, listening to the conversation and producing high‑quality clinical notes tuned to each hospital’s templates and workflows. Clinicians were quick to adopt it. Liu describes doctors using Heidi in every consult and calling the founders directly when it went down, because they no longer wanted to go back to typing everything themselves.
In New Zealand, that enthusiasm has translated into national‑scale deployment. Health New Zealand is rolling Heidi out across all emergency departments, with clinicians in places like Hawke’s Bay cutting documentation time per patient from roughly 17 minutes to around four minutes.
Heidi, which has now raised around US$100 million across several VC-backed fundraising rounds, blends frontier large language models with specialised, region‑local models trained on clinical language and medication names, hosted in‑region to satisfy data sovereignty requirements. That’s how it pushes accuracy toward the near‑99 per cent threshold clinicians need to trust AI‑generated notes, says Liu. Heidi wants to transform assistive AI into something closer to infrastructure.
From scribe to evidence-gatherer
Heidi doesn’t retain recordings of conversations, and while many doctors create transcriptions on their smartphones or laptops, the Heidi Remote is also available – a mobile recorder doctors and nurses can carry around clinics and hospitals for easy recording that doesn’t rely on an internet connection.
The company is already moving beyond transcription. Heidi Evidence surfaces relevant clinical research and guidelines at the point of care, while Heidi is expanding into pre‑chart summaries, referrals and spoken commands that trigger real actions in electronic health record systems. The aim, says Liu, is to let doctors focus on diagnosis and human connection, and let AI handle everything else.
In the episode, we dig into Heidi’s founding story, its rapid uptake in New Zealand’s public health system, and the governance and privacy questions that come with putting AI in the consult room.
Tune in to the full conversation with Heidi Health co-founder Yu Liu on The Business of Tech, available wherever you get your podcasts.
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Another New Zealander has joined the global AI big league.
Auckland-raised engineer Jeff Hawke is now co‑founder and chief technology officer of Odyssey, a Palo Alto‑ and London‑based frontier lab that has just raised an eye‑watering US$310 million at a US$1.45 (NZ$2.55 billion) valuation – making it one of the world’s hottest AI “world model” startups.
On this week’s episode of The Business of Tech podcast, I talk to Hawke about how he went from tinkering with autonomous forklifts in New Zealand to helping shape the next era of artificial intelligence from Silicon Valley and Shoreditch.
Odyssey isn’t building another large language model. The company is focused on “world models” – AI systems that learn from sight and sound to understand how the real world works and then simulate it. Instead of spitting out text, these models simulate the real world, allowing robots that learn like humans, and games that feel like living worlds.
Amazon to power Odyssey’s models
Global investors are piling in. Odyssey’s Series B is led by US fund Natural Capital, with Amazon, AMD, GV, EQT, IQT and other heavy hitters on the cap table, plus a who’s who of Silicon Valley angels. Amazon Web Services has also signed on as Odyssey’s preferred cloud provider, betting that its Trainium AI chips can give the lab an edge in what is rapidly becoming an arms race for compute.
For Hawke, it’s the latest step in a deep‑tech odyssey. After studying mechatronics and computer science at the University of Auckland, he cut his teeth at a local autonomous forklift startup before heading offshore. Stints in the US and at the Oxford Robotics Institute led to him becoming the first technical hire at UK autonomous‑vehicle company Wayve, working alongside Kiwi founder Alex Kendall as they grew the company to a multibillion‑dollar valuation.
In our conversation, Hawke explains why he thinks world models are the missing piece of the AI puzzle, how Odyssey plans to move from a “GPT‑2 era” of world simulation to its own ChatGPT‑style breakout moment, and what this means for robots, jobs and the balance of power between tech companies and governments.
We also look at what his success says about New Zealand’s tech ecosystem – and why a new generation of Kiwi founders is quietly wiring itself into the very top tier of global AI.
You can listen to the full interview with Jeff Hawke on The Business of Tech, available now on Apple, Spotify, iHeartRadio or wherever you get your podcasts.
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China is racing ahead in artificial intelligence and robotics – and New Zealand risks being left on the sidelines if it doesn’t pay close attention.
In this week’s episode of The Business of Tech, I talk to two Kiwis who’ve just had a rare front‑row seat on China’s AI boom – Auckland-based ElementX co‑founder and chief technology officer Ming Cheuk, and Christchurch AI engineer and consultant Blake Harkness.
They’ve returned from an AI discovery tour organised by the AI Forum and the New Zealand China Council that took them inside some of China’s most advanced AI labs, hyperscale cloud providers, hospitals, banks, councils and robotics manufacturers. What they describe is a country where AI has moved well beyond pilots and proofs of concept and is now deeply embedded in everyday life and industrial processes.
The AI hospital
In healthcare, they visited a single hospital serving around five million patients a year, where AI chatbots handle initial triage in multiple languages, imaging tools cut the time to analyse scans by 80%, and robots in the pharmacy automatically pick and dispense prescriptions. Everything is done with the scan of a QR code. For a country like New Zealand, grappling with an ageing population and over‑stretched health services, it’s a glimpse of what fully scaled AI-enabled care could look like.
They also met with frontier large language model labs and firms building China’s own AI tech stack, often with a strong open-source ethos. Models that can be deployed on customers’ own infrastructure – even as part of sovereign AI arrangements – are central to China’s strategy, allowing overseas organisations to adopt Chinese AI without sending data back to Beijing. It’s a clever way to sidestep geopolitical mistrust while still extending technological influence.
On the robotics front, Ming and Blake toured factories producing humanoid robots and agile robotic “dogs” that are already off‑the‑shelf tools for search and rescue, asset inspection and industrial maintenance. The sheer number of robotics companies, and the pace at which they’re iterating on hardware and control systems, underscore how serious China is about becoming a global robotics powerhouse.
The tech divide
Yet geopolitics is never far from the surface. Export controls, national security concerns and shifting alliances mean much of this technology may never be directly available to Western buyers. Even so, Ming and Blake see real opportunities for New Zealand in partnering around open-source models, sovereign AI builds and targeted robotics deployments in sectors like infrastructure, manufacturing and agriculture.
If you want to understand where AI and robotics are really heading – and what that means for New Zealand’s economy, workforce and policy choices – this is an episode you won’t want to miss.
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The Government’s plan to cut 8,700 public sector jobs and save $2.4 billion has been framed largely as a brutal cost‑cutting exercise.
In this week’s episode of The Business of Tech podcast, Hamilton‑based technologist Brandon Hutcheson argues it could instead be the catalyst for a once‑in‑a‑generation redesign of how government works – if we get the AI strategy right. He admits, that's a big "if".
Hutcheson, head of quantum at Netherlands-based IT services firm HSO and co‑founder of AI specialist Aware Group, has published a detailed catalogue of 160 ways artificial intelligence could transform the public sector. The ideas range from obvious efficiency wins – such as shared AI‑enabled contact centres and common cloud HR and payroll platforms – through to more ambitious proposals like synthetic populations for policy testing and real‑time legislation impact simulators.
Rather than starting with “who can we cut?”, Hutcheson wants agencies to map their processes into four buckets: fully automatable, automatable with a transition plan, partially automatable with permanent human oversight, and human‑only functions. That discipline, he argues, is missing today, with agencies scrambling to bolt on AI tools in isolation, baking in the next wave of technical debt and eroding public trust.
The next wave of computing
He’s particularly critical of the way the cuts have been communicated – telling public servants their jobs are on the line while expecting them to lead the automation of their own roles. In his view, the smarter play is to frame AI as a way to improve citizen experience, reduce low‑value manual work, and spin out new export‑focused ventures built on New Zealand’s deep public‑sector expertise.
The episode also looks ahead to the next wave of computing that will sit behind many of these changes. Hutcheson has just returned from Microsoft’s quantum labs in Redmond, where the company is racing to build fault‑tolerant quantum machines. He explains what he saw on the ground, why quantum should already be on the radar of boards and CIOs, and how it could combine with AI to reshape industries that rely on complex simulations – from materials and manufacturing to agriculture and finance.
For business leaders, technologists and policy makers, this conversation is a roadmap to what’s possible – and a warning about the architectural decisions we make now.
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