The Business of Tech

The Opportunity Party is attracting growing support from young tech professionals, scientists, and startup founders, demanding bolder, more evidence‑based leadership.
That’s according to Opportunity party leader Qiulae Wong, the businesswoman, climate leader and mother who will lead the party into the election in a bid to crest the 5% popular vote threshold needed to see the party in a position to support a coalition government.
On this week’s episode of The Business of Tech, I sit down with Wong to discuss her party’s plan to lift New Zealand out of its low‑productivity rut by putting innovation at the centre of economic policy.
You’ll hear how the Opportunity Party wants to double R&D investment from around 1.5% of GDP to 3% – finally putting us in the same league as other advanced economies – and pair that with much stronger support for commercialisation so ideas don’t just die in the lab.
We also dig into how greater competition in highly concentrated sectors like supermarkets, banking and energy could free up capital and lower barriers for new, tech‑driven challengers.
Gold standard AI rules
A big focus of the episode is artificial intelligence and the weightless tech economy. Wong explains why New Zealand needs “gold standard” AI rules that are tight on outcomes but open for innovation, so founders can build globally competitive AI products here rather than in London or San Francisco. We talk skills, education, and the critical thinking needed to make sure AI boosts productivity instead of hollowing out jobs.
We also unpack how the Opportunity Party plans to pay for its policy agenda. Its newly released tax policy includes a 1.75% land value tax, a universal citizens’ income and compulsory “KiwiSaver 2.0” savings. Qiulae argues this package is designed to shift money out of speculative property and into productive investment, while helping fund a serious uplift in R&D and a faster clean‑energy transition.
Rounding out the episode, we explore a 25‑year energy strategy, ways to bring Kiwi tech talent home, and how citizens’ assemblies and digital voting could revitalise our democracy for a generation that lives online.
Has Opportunity got a chance? Recent polls have the party hovering around 3% of the popular vote, shy of the level needed to get its candidates into Parliament. But these are unprecedented times, with younger voters in particular looking for bold leadership. The momentum may be on this minor party’s side.
Listen to the full conversation with Qiulae Wong on this week’s episode of The Business of Tech, streaming on iHeartRadio, Apple, Spotify, or wherever you get your podcasts.
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Market research has long been a privilege of the big end of town. Got $50,000 and six weeks to spare? Great, you can know what your customers think. Everyone else? Good luck.
That model is being dismantled, and a New Zealand startup is doing some of the dismantling. In the latest episode of The Business of Tech, I sat down with James Donald, CEO of Auckland-based Ideally, fresh from closing a $16 million Series A that values the company at $100 million.
Ideally is one of three AI-centric New Zealand startups to hit that psychological valuation milestone in the past month – a sign that our fledgling AI start-up ecosystem is gaining momentum.
James is a former Shell engineer turned serial founder whose previous company, Yonder, was acquired by a US travel tech firm. Now he's turned his sights on a $40 billion slice of the global market research industry – one where 90% of spend still flows to people-heavy agencies like Kantar and Nielsen.
His pitch: AI can do what took those agencies weeks to do, in hours, at a fraction of the cost, and with results in the hands of the people inside a company who actually know what questions to ask.
The pros and cons of synthetic data
In our chat, we get into the heart of what Ideally is doing differently. One of the most interesting debates in AI right now is the rise of synthetic data – building artificial personas to simulate how real people would respond. James makes a pointed argument: when the stakes are high, and you need genuine nuance, synthetic just isn't good enough.
We also dig into what James calls "living data" – the idea that consumer insight shouldn't die in a PDF buried in SharePoint, but should be a continuously growing, queryable understanding of your customer base.
And we talk about the SaaSpocalypse – that February moment when hundreds of billions were wiped off the value of software companies worldwide. Ideally sits squarely in that story: an AI-native challenger gunning for the market share of legacy research platforms and expensive agencies alike, with a usage-based pricing model designed to turn in-house marketers into researchers, rather than leave it to outside consultants.
This is a great example of how AI is being used to shake up long-established industries.
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New Zealand is quietly dismantling the productive base that built its prosperity – and we’re doing it without anything resembling a plan.
Over the past decade, the country has shed around 20,000 manufacturing jobs while the sector’s share of GDP has steadily eroded. Factories producing everything from pulp and paper to frozen foods and wood products have scaled back or shut down entirely, including household names such as Wattie’s and McCain.
For regional centres like Westport and Kaitāia, each closure is an economic shock that ripples through the whole community. The blow would be blunted somewhat if we had a plan B to revive manufacturing and offer employment prospects in the regions. But we don’t.
Some economists and industry leaders now openly talk about the “deindustrialisation” of New Zealand. Manufacturing is responsible for roughly 60% of our exports and employs close to one in ten workers, yet it has slipped down the priority list in Wellington.
Other countries – Australia, Singapore, the UK and the US among them – have modern industrial strategies and long-term Industry 4.0 programmes. New Zealand, by contrast, shelved its industry transformation plans and has yet to articulate what kind of manufacturing base it wants to have in 10 or 20 years.
Energy costs sit at the heart of the problem. For many manufacturers, electricity and gas now rank among their top 2 - 3 operating costs. The rapid push to electrify process heat, combined with volatile spot prices and an uncertain gas transition, has left some plants badly exposed. At the same time, manufacturers face chronic skills shortages, conservative lenders demanding personal guarantees for capital upgrades, and resource consent processes that add cost and delay to even straightforward investments.
In the latest episode of The Business of Tech podcast, I’m joined by Christchurch-based manufacturing expert Sean Doherty to delve into what’s gone wrong – and what can still be salvaged.
Beyond plug-in AI fixes
After a 30‑year career that includes a long stint at Rockwell Automation and leading the advanced manufacturing programme at Callaghan Innovation, Doherty has had a front‑row seat to thousands of technology and productivity projects. He’s blunt about the structural issues and the policy vacuum, but he also insists manufacturers are not powerless.
Rather than chasing silver bullets or “plug‑in AI” fixes, Doherty argues for a disciplined focus on small, practical productivity and efficiency initiatives: getting real‑time data off the factory floor, tightening basic management practices, and investing in people alongside machines.
In a tough, high-cost environment, those incremental gains can spell the difference between slow decline and a credible growth story you can take to the bank – and, collectively, between a country that drifts into deindustrialisation and one that chooses to rebuild its industrial backbone.
Listen to the entire episode of The Business of Tech, streaming on iHeartRadio, Spotify, Apple, or wherever you get your podcasts.
Show notes
Factories in retreat: inside NZ’s deindustrialisation crisis - The Post
Sean Doherty on LinkedIn
Aotearoa’s Industry 4.0 Journey - Callaghan Innovation report
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Artificial intelligence isn’t coming to the New Zealand public sector – it’s already here.
AI is shaping everything from your tax bill to how quickly police process crime reports. And right now, it’s happening in a way that’s fast, fragmented and largely hidden from public view.
On the latest episode of The Business of Tech, I talk to BusinessDesk journalist Cécile Meier about her multi‑part investigation into the use of AI across government – an investigation built on a trove of Official Information Act responses from major agencies. What she found is both encouraging and unsettling.
Real efficiency gains and cost savings
There are genuine wins. Police have slashed processing times for lower‑severity crime cases from eight to ten minutes per file to as little as one to three minutes using an AI‑powered workflow tool – a saving estimated at 18,000 hours and around $1 million a year. Inland Revenue is using AI in its debt collection models, helping secure tens of millions of dollars in payment arrangements in just weeks. ACC and others report large productivity gains from Microsoft’s Copilot baked into everyday tools.
But scratch the surface, as Meier has, and the story gets a lot more complicated. There is a public‑service‑wide AI framework governing how these tools should be deployed, but it is not binding. Agencies have guidlines for adoption but are largely left to design their own pilots, measure their own “time saved”, and often rely on the very vendors selling them AI to prove the return on investment. Quality, error rates and real‑world impacts on citizens barely get a look‑in.
The AI deployment divide
Her reporting also exposes a stark divide. Some agencies – IRD, ACC, Police and DOC – are forging ahead, training thousands of staff and embedding AI deep into decision‑support systems. Others, like Oranga Tamariki and Corrections, are so wary of the risks that they’ve blocked external AI tools and confined usage to tightly constrained, low‑stakes tasks. All of this is happening under the same loose, non‑binding guidance.
AI tools are stumbling over te reo Māori and Māori legal concepts, raising obvious concerns about bias and fairness. There's growing reliance on a handful of US tech giants to supply and measure government AI, and a rising wave of “shadow AI”, as public servants quietly use banned tools on personal devices because they’re simply too useful to ignore.
Listen to The Business of Tech for the full interview, and hear how AI is quietly rewiring the state, often without the scrutiny it deserves. Streaming on iHeartRadio, Spotify, Apple, or wherever you get your podcasts.
Show notes
'Slippery slope': Concerns millions spent on AI may not be delivering for public - BusinessDesk
Light rules, high stakes: Agencies push AI into frontline work - BusinessDesk
Government AI spending hits $20.2m with real cost likely far higher - BusinessDesk
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Big organisations love to talk about innovation. They set up labs, hire “transformation” teams, and run hackathons.
Yet inside many companies, the best ideas still die in PowerPoint decks or get buried in cautious business cases.
In this week’s episode of The Business of Tech, I talk to Gravity cofounder James Boult, an innovation specialist who has spent years inside large New Zealand organisations, watching this play out in real time.
Boult’s verdict is that most corporates are structurally set up to smother genuinely new ideas, even when the will – and the talent – is there.
Boult’s core advice is to treat every significant new idea as if it were a venture‑backed startup inside your organisation. That means giving it a dedicated budget, a finite runway, clear deliverables, and hard stage gates where the project must “earn” the right to continue. No more quietly funding side projects from the core P&L. No more open‑ended experiments that drift for years without real customers.
The gatekeepers and the fear factor
Instead, project owners should be forced to pitch for the next tranche of funding just like founders fronting up to investors. That shift, says Boult, changes behaviour overnight. Teams become sharper on the problem they’re solving and far less likely to hide behind internal politics or legacy metrics.
The episode also digs into the human side of corporate innovation – the “gatekeepers” who can make or break new ideas. These people aren’t cartoon villains. They’re often acting out of fear about budgets, risk, or their own roles. Boult explains how to identify them early, understand their motivations, and design an innovation process that works with – rather than around – those emotional realities.
For frustrated “intrapreneurs” who feel like they’re “going mad” inside a big company, Boult offers a practical playbook for testing startup thinking without immediately quitting the day job. And for senior leaders, he lays out why outsourcing innovation, spinning up venture arms, or re‑branding old projects as “agile” won’t work unless the underlying incentives and governance change.
If you work in a large organisation that talks a big game on innovation but struggles to ship anything truly new, this episode is required listening. Listen to The Business of Tech wherever you get your podcasts.

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