Will Microsoft and Google Make NZ Lazy With AI?

But that mindset isn’t only premature, it's inherently dangerous to the business's long term viability. They end up mistaking convenience for capability, and comfort for progress. The very vendors giving them a leg up may also be unintentionally anchoring them down.

In tech, convenience is seductive. Copilot and Gemini can feel like magic. Auto-summaries, smart replies, instant meeting notes: who wouldn’t love that?

But here’s the philosophical challenge: ease of use naturally erodes depth of understanding and curiosity.

These tools are great for Stage 1 on the AI ladder: getting familiar, building awareness, and lowering the fear barrier. But if leaders let that be the ceiling, not the floor, they risk atrophy. They become executives who know AI exists but don’t really understand how it works and what else is out there.

Just like it's hard to decline a top salesperson who’s also your golf buddy, it’s tough to question a vendor that makes your day easier. And the risk is falling into “executive allegiance", trusting their AI stack over our own strategic needs. That’s when curiosity dies and innovation slows.

Now, let’s be clear: this isn’t anyone’s fault. It’s the natural result of our environment.

And implementing CoPilot or Gemini for most could well be the slow erosion of their business.

Microsoft often touts stats like “84% of Kiwis use AI in some capacity at work, surpassing the global average". Sounds impressive until you ask:

Most of these stats measure touchpoints, not transformation. Microsoft’s AI adoption score counts any user who interacts with Copilot at least three days a week over a 28-day period, regardless of how deep, strategic, or meaningful that interaction is.

They're based on usage, not impact. That's not a measure of workflow change or relative competitive advantage if every other business out there uses CoPilot or Gemini as part of their productivity stack (sure, adoption from organisation to organisation varies). It's not a signal that teams are gaining skills or changing how they operate.

And yet, these numbers get repeated as evidence that NZ is leading, when in reality, we’re just getting started. The gap between touchpoint and transformation is massive.

New Zealand’s geographic isolation has always shaped how we operate. It creates independence, drives creativity, and builds self-sufficiency. Kiwi businesses are known for doing more with less, solving problems with limited support, and building resilient systems without relying on global infrastructure.

That mindset is an advantage until it becomes an excuse to stay out of the loop. Because while we focus on self-reliance, the rest of the world is moving faster, collaborating more, and adapting in real time to breakthrough AI developments. We miss that exposure.

In global AI hubs like San Francisco, London, or Shenzhen, new tools are released early and adopted fast. The feedback loops are short, the pace of learning is high, and businesses evolve in real time.

In New Zealand, those same tools often arrive months later. By the time they hit our market (usually through global suite updates) the rest of the world has already moved on to the next iteration. This time lag slows our adoption curve, both at the individual and enterprise level.

The result is Kiwi businesses find it harder to compete both globally and locally. Teams that don’t look beyond NZ borders for inspiration risk falling behind those that do. Without timely access to new capabilities, the innovation gap widens, and our competitive edge diminishes.

In places like Silicon Valley or New York, the pressure to adopt AI is existential. Companies either evolve fast or fall behind.

In NZ, that sense of urgency is reduced. There are fewer challengers with AI-first mindsets, fewer boards demanding transformation, and fewer direct comparisons to businesses scaling through AI. That lack of pressure creates space for a relaxed mindset: take what the vendor gives, check the box, and assume you’re doing fine.

Especially when vendor-led stats( like Microsoft’s AI adoption score) reinforce the illusion that we’re ahead. Having seen the global standard up close, I can confidently say: we are nowhere near it.

New Zealand has a healthy instinct to question hype, especially when it comes from Silicon Valley and the tech overlords. But since returning home, I’ve noticed that skepticism often creates apathy. We stop listening. We tune out the headlines, the tools, and the stories shaping the AI future.

That intentional distance may feel grounded, even wise. But in practice, it’s leaving us uninformed. It means fewer people are watching, testing, or even curious. And when you’re not looking, you miss the shift that's taking place until is passes you by.

AI is moving too fast to be passively adopted. The idea that we can wait for it to trickle down through enterprise suites, through updates, through vendor webinars is not an adoption strategy.

Every delay is a missed opportunity to build skills, rethink workflows, and embed competitive advantage. The longer we wait, the more the gap grows between those who use AI and those who leverage it.

To stay competitive, NZ leaders must treat our isolation as a reason to actively seek out frontier thinking rather than a reason to delay.

Again, this isn’t about blame. It’s structural. It’s environmental. But unless we call it out, we won’t change it. And if we don’t change it, we’ll keep falling behind while thinking we’re ahead.

Beneath the surface of widespread AI adoption lies a less visible, but far more strategic risk: the danger of building AI strategy through a vendor's lens, not your own.

Most enterprise AI tools, especially those from Microsoft or Google, are built for broad use rather than specialised industries. Their models are often trained on general-purpose data, which creates a poor fit for regulated or domain-specific sectors like finance, healthcare, or government.

This isn’t just about model bias. It’s strategic tunnel vision. When leaders only evaluate what is already in their suite, they limit innovation to what is easy, not what is effective.

And yes, an enterprise-grade AI model like Copilot or Gemini, embedded across your productivity suite, is incredibly valuable. It accelerates everyday work, boosts adoption, and lowers friction. I’m not suggesting we walk away from these platforms.

But we cannot get locked in. Strategic advantage comes from layering in other tools, testing point solutions, and giving teams permission to experiment. That means allocating a slice of your budget for lightweight, even disposable, technology and letting people run wild with it.

Of course, not every enterprise can pivot quickly. Years of architecture, integration, and governance make experimentation complex and expensive. But that is not an excuse for inertia.

Progress requires flexibility. And curiosity.