The Business of Tech

Everyone wants an AI-powered economy. But who takes responsibility when the technology gets things wrong, and how do we make sure everyone shares the long-promised productivity gains?
That’s at the heart of this week’s episode of The Business of Tech, recorded as the US absorbs its midterm election results and New Zealand waits for special votes to help determine the next government.
My guest, Victoria University of Wellington AI researcher Dr Andrew Lensen, argues that getting value from AI requires more than buying software, building data centres and telling staff to embrace AI. It needs leadership, accountability and evidence that the investment actually delivers.
For the next government, Lensen’s starting point is to have someone in charge. A senior minister responsible for AI would give the issue political weight. An independent body, the equivalent of the Privacy Commissioner, could help turn broad promises about responsible technology into practical oversight.
Explainability and an appeal process
Lensen sees merit in an AI commissioner, with powers to investigate complaints and scrutinise automated decisions. If a government agency uses AI to make a consequential decision about you, there should be an explanation and a way to challenge it.
But rules are only part of the equation. Leaders also need their people on board.
Selling AI primarily as a vehicle for job cuts, as the coalition Government did earlier this year, risks sabotaging its introduction. The employees who understand an organisation’s processes are often best placed to identify where the technology could help. Give them a reason to fear it, and that knowledge becomes harder to unlock.
“As soon as you say, hey, by the way, we're going to get you to do this, and then we'll fire you. I mean, you're really not going to get much progress being made,” Lensen says.
Then there’s the productivity question. Are organisations measuring improvements, or simply assuming that more AI means better performance?
“Because there's so much where at the moment it feels like it's on vibes.”
Better metrics on AI's impact
Lensen wants proper comparisons between existing processes and AI-assisted alternatives, with success measures set upfront. Time saved, fewer complaints and better outcomes matter more than enthusiastic anecdotes.
We also tackle the data-centre boom. What should New Zealand expect in return for supplying land, electricity and infrastructure? Could access to computing capacity help local researchers and startups, rather than simply serving offshore demand?
This isn’t a call to stop experimenting. It’s a challenge to get more focused about what success looks like, articulate who benefits and who answers when things go wrong.
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New Zealand runs on American technology. But what happens when the country behind those platforms starts looking like a less dependable partner?
That question hangs over the latest episode of The Business of Tech, as Microsoft faces growing pressure to give governments and businesses more control over the systems they rely on.
My guests are Lewis Mills, Microsoft New Zealand’s Corporate Affairs Director and Special Counsel for National Security, and Blake Herzinger, Microsoft Asia’s Defence and National Security Government Affairs Lead.
Both recently participated in the Aspen Institute’s national security forum in Queenstown, where cybersecurity and public-private cooperation featured prominently.
The sovereignty debate is no longer just about where data sits. It’s about who can access it, which laws apply, and whether essential services can keep running when a supplier, network or international relationship comes under strain.
Microsoft is adapting. Its Sovereign Private Cloud offering, built on Azure Local, brings selected cloud capabilities onto customer-controlled infrastructure. Disconnected deployments can operate without a connection to Microsoft’s public cloud, moving the management layer inside the customer’s own environment.
Control, security and resilience
That offers more control. It doesn’t necessarily mean less dependence on Microsoft.
That distinction is drawing more attention as organisations weigh the benefits of global platforms against concerns about foreign jurisdiction, supplier concentration and geopolitical disruption.
Mills defines digital sovereignty around control, security and resilience. But those priorities can compete. Keeping infrastructure close may strengthen direct oversight, while using geographically dispersed cloud services can help organisations recover when disaster strikes locally. In an earthquake-prone nation, having offshore options could represent a digital lifeline.
Herzinger likens the choices to the sliders on a DJ’s mixing desk: turning one setting up can force compromises elsewhere.
Rebuilding everything locally carries a formidable price tag.
“If you want to spend, you know, two per cent of GDP, you could build a completely domestic AI technology stack, but very few governments are going to be able to achieve that,” Herzinger told me.
It underlines the scale of the challenge.
In the episode, I press the pair on US government access to data, the risks of relying on hyperscalers, and what sovereign AI could realistically mean for a small economy.
The answer isn’t simply to bring everything home or to double down on public cloud platforms.
It’s deciding which dependencies we can live with, which controls we need, and whether we have credible options when circumstances change.
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Two days into the job, Roman Reyhani was confronting a $231 million question: how does New Zealand turn clever science into businesses that deliver lasting value here?
The founding chief executive of the New Zealand Institute for Advanced Technology joins this week’s episode of The Business of Tech to explain his approach.
The institute represents a pivot towards high-tech research and commercialisation. But its funding has largely been redirected from other parts of the science system, rather than added to the pot.
That increases the pressure to deliver. Can a stronger commercial focus succeed without weakening the research pipeline feeding it?
From genocide prosecutions to Silicon Valley startups
Reyhani’s route to the role is unusually varied. Raised in Auckland, he began in international law, including an internship with the prosecution team at the United Nations tribunal investigating Rwanda’s genocide.
California offered a different way to make an impact. He established a legal practice and worked with technology startups, gradually moving beyond legal advice into strategy and business development.
Six years at Boston Consulting Group’s venture-building arm, now BCG X, followed. His teams helped major companies create products and businesses, recruiting people and taking technology to market rather than leaving clients with presentation slides.
Now back in New Zealand after more than two decades overseas, he wants the institute to bring an investor’s discipline to research funding.
“It’s not just here’s a chunk of money and a handshake and good luck to you,” he says.
Instead, funding would follow “stage gates” milestones with money shifted away from projects that aren’t progressing.
The institute’s territory sits between promising laboratory research and technologies mature enough to attract private investment. Bringing companies and investors alongside earlier could help bridge that expensive gap.
Applied AI is a big opportunity.
Then there’s the question of who benefits. Reyhani wants New Zealand to retain more value when taxpayer-backed technologies succeed, whether through financial returns, research facilities, skilled people or new businesses.
On artificial intelligence, he sees opportunities in applying existing models to New Zealand datasets, including agriculture and health, rather than competing head-on with the world’s biggest model developers.
It’s an ambitious brief for a modest budget by international standards. The challenge is choosing where New Zealand has a genuine edge, then backing it without confusing commercial discipline with impatience.
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Andfoods isn’t trying to win the plant-based food battle in the supermarket aisle. It wants raving fans in Asia’s busiest kitchens.
The New Zealand startup is turning black gram, also known as black mung bean, into whipping cream. Its pitch to chefs is that dairy-free shouldn’t mean settling for second best.
On this week’s episode of The Business of Tech, co-founder Alex Devereux explains why winning over the person holding the whisk could be a smarter business than chasing shoppers.
Devereux learned the food service trade at Fonterra, supplying ingredients to businesses where taste, consistency and price determine whether a product earns its place in the fridge.
After leaving dairy for technology roles, an invitation from Icehouse brought him to Massey University’s Riddet Institute. There, he and fellow Fonterra alumnus Leon Clement tasted a plant-based whipping cream that stood out.
“We knew the markets, we knew the dynamics and what customers were looking for in that kind of product,” he says.
The science tackles an awkward problem: beans taste like beans.
Replicating the taste and texture of dairy
Riddet researchers developed a fermentation process that strips out those sharp flavours while retaining black gram’s natural creaminess and ability to foam. Combined with coconut oil and other ingredients, it becomes a cream that, Devereux says, delivers dairy-like taste and texture.
There’s a practical selling point, too. He says the whipped cream holds its shape longer in hot conditions, a useful attribute for cakes and desserts in tropical markets.
But clever science doesn’t automatically win kitchen space.
Andfoods employs a chef in Singapore to demonstrate the product alongside its distributor. The aim is to talk chef to chef, showing how it performs rather than delivering a sales pitch.
“Chef-led sales is the most effective way to win this type of business,” Devereux says.
Get the product right and customers tend to stick around, without the marketing bill needed to build a supermarket brand.
Andfoods has secured Singapore’s Marina Bay Sands as a customer, with Malaysia, Vietnam and Thailand on its expansion list.
Its model also departs from the familiar Kiwi export recipe: retain research and intellectual property here, but manufacture in China, closer to customers.
Having raised $4 million, Andfoods is seeking another $7m to fund growth, with culinary cream and cold foam products in development.
The ambition isn’t simply to replace dairy. It’s to become the cream chefs choose.
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The people building the world’s most powerful artificial intelligence systems promise extraordinary gains. They also warn those systems could escape our control.
That is the ethical fault line running through this week’s episode of The Business of Tech.
My guest, New Zealander Peter Barnett, works at the Machine Intelligence Research Institute in Berkeley, California. The University of Otago physics graduate develops governance plans aimed at preventing catastrophic outcomes from advanced AI. He previously worked on technical AI alignment, the difficult job of making powerful systems act in line with human intentions.
This conversation is a topical one.
OpenAI is facing fresh turmoil over its approach to safety. Three recently fired safety and alignment researchers claim they were punished for challenging the company and working with outside evaluators. OpenAI rejects that account, saying they mishandled sensitive information and breached its trust.
David Robinson, one of OpenAI’s senior safety figures, has also resigned. The former author of safety reports accompanying major model launches says the company’s culture is “broken” and the industry is not being nearly careful enough. He just sat down for a podcast interview with Ezra Klein of the New York Times, which makes for fascinating viewing.
These departures expose the moral dilemma at the centre of the AI boom.
Worrying emergent traits in AI
The companies racing towards more capable models say the technology could cure disease, lift productivity and create enormous wealth. But they face fierce competition, huge investor expectations and a geopolitical contest framed around beating China.
Every incentive rewards speed. Caution risks handing the advantage to a rival.
So who decides when the danger is too great?
Barnett argues it cannot be the companies themselves. He says frontier AI developers are effectively writing their own rules and can loosen them when safety commitments obstruct progress. Independent audits, government oversight and limits on training more powerful models may all be needed.
His concern is not simply that people will misuse AI. It is that increasingly autonomous systems could learn to game evaluations, work around safeguards and pursue goals their creators did not intend. Safety researchers still cannot reliably predict everything a frontier model will be capable of before it is trained.
Barnett believes New Zealand can play a role. We do not build frontier models, but our nuclear-free history shows a small country can challenge powerful nations on an issue carrying global risk.
When insiders abandon lucrative careers to raise the alarm, maybe it's worth listening to them.
Listen to the full conversation with Peter Barnett on The Business of Tech, streaming on iHeartRadio, Apple, Spotify or your podcast app of choice.
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