As we approach the end of what's been a particularly challenging year for many Wellington organisations, I've been reflecting on the conversations I've had with leaders throughout 2025. One stands out from just last week, a CEO who summed up what I'm hearing across the board. "I know we need to do something with AI," she said, "but I feel like I'm standing at the edge of a cliff, and everyone's telling me to jump without showing me where I'll land."

If this sounds familiar, you're not alone. Right now we're living in the ‘liminal space’ — no longer in the old digital world we understood, but not yet confidently established in the new one emerging around us. Add to this the economic pressures many of us have faced this year, and it's no wonder leaders feel caught between a rock and a hard place.

And the pace is overwhelming. AI capabilities that took years to develop are advancing in months. New tools launch daily, each promising to revolutionise how we work. Meanwhile, customer expectations and behaviours are shifting faster than strategic planning cycles can keep up with.

There's huge appetite for progress, but also real hesitation. Leaders know they need to move forward and embrace emerging tech, but they're uncertain about where to start or how to do it well while keeping the lights on and managing costs — particularly after a year where many have had to be more cautious with budgets.

This is made even harder by the noise. I'm regularly hearing stories of clients being pitched fancy solutions with no understanding of the business context or existing digital infrastructure. The snake oil touts are talking miracle cures, but that's not what we're seeing in practice.

Us Kiwis are naturally a bit sceptical and prefer to see evidence before investing. To be honest, I think that instinct is serving us well right now.

Instead of trying to leap across the entire chasm in one go, we've been working with clients on what I call #lilypadding. Imagine you’re crossing a body of water by stepping carefully from one lily pad to the next. Making steady progress without needing to clearly see the entire path ahead.

What this looks like in practice is starting with small experiments using existing platforms. Rather than complete system overhauls, we're exploring how new technologies can make digital products and experiences more effective. Why throw the baby out with the bathwater when you can optimise for AI instead?

We're running proof-of-concepts that test specific use cases: AI-powered chatbots for customer service, automated content generation for marketing teams, or machine learning to understand customer behaviour patterns. These don't require enormous budgets, but they generate real learnings about what works in each specific context.

The beauty of this approach is that each small step builds organisational confidence and capability. Clients aren't just implementing technology, they're developing internal expertise and governance structures to use AI responsibly long-term.

One client recently told me, "These small experiments have given us something we didn't expect — not just new capabilities, but confidence that we can navigate this change thoughtfully."

The experimental mindset allows you to fail small and learn fast. Not every test succeeds, and that's the point. Better to discover what doesn't work through a small pilot than after a major implementation.

As I reflect on this year’s challenges and conversations, I think that the organisations thriving in this new digital world won't necessarily be those with the biggest AI budgets or flashiest technology stacks. They'll be the ones that learned to navigate change thoughtfully, building capabilities through careful experimentation, even when resources are tight.

If you're feeling overwhelmed by technological change, maybe start by taking inventory of your existing digital assets. What's already working well? Where are the friction points that new technologies might address?

The approach we've found most effective is picking one small, specific experiment for the next quarter. Something measurable and relatively low-risk: testing an AI tool for one customer touchpoint, or exploring automation for a time-consuming internal process.

Getting moving with AI doesn't mean rushing into massive transformation projects. It means taking that first deliberate step, learning from what happens, and planning the next move based on real evidence.

As we head into 2026, I reckon the future belongs to those who balance bold vision with practical wisdom, which sounds exactly like the kind of leadership New Zealand does well.

If you want to get moving with AI but need independent advice and a human-led perspective, give us a call. Sometimes the most powerful step forward is having a chat with people you can trust.