For younger people entering the workforce, capability matters more than ever: the ability to adapt and keep adapting.
That is not a new idea, but the pace and scale of change now feels amplified compared with earlier shifts such as the digital revolution, when work moved from manual systems to computers, or even the industrial revolution, when machinery transformed how goods were made.
I still personally remember when digitalisation in NZ started becoming mainstream in the late 1970s. There was plenty of doom and gloom: one word processor replacing a whole room of typists, and genuine concern about what technology might do to our thinking. Even allowing calculators into exams sparked debate.
And yet, here we are. If history tells us anything, it is that fear usually arrives early, but over time, people adjust. Technology reshapes work, sometimes dramatically, but it also creates new possibilities and opportunities that are hard to see at the beginning.
The Real Skill Isn’t Tech — It’s Adaptability
The conversation right now is heavily focused on AI tools — which ones to use, how they work, what they replace.
But the more important shift is happening at a human level.
Research continues to show that one of the most important capabilities in this environment is adaptability - the ability to learn, unlearn and keep moving. Reports such as the World Economic Forum’s 2025 Future of Jobs analysis highlight resilience, flexibility, agility and technological literacy among the skills rising fastest in importance.
And sitting right at the centre of that?
Curiosity.
Curiosity is what prompts people to test, explore, question and engage with change rather than resist it. In the context of AI, that makes it more than a personality trait, it becomes a practical capability.
The broader workforce conversation is increasingly pointing in the same direction - curiosity, lifelong learning and technological literacy are becoming essential companions to analytical thinking and judgement.
So while the tools themselves are evolving rapidly, the people who thrive will be the ones willing to stay curious.
AI Is Not a Human Brain
There is also a common misconception that AI is just like a human brain.
It’s not, and it’s important we understand that.
AI systems do not “know” things in the way humans do. They work by identifying patterns in large datasets and producing outputs based on probability, rather than understanding, lived experience or independent reasoning.
That’s why different AI tools behave differently. They’ve been built by humans, trained on different data, and designed for different purposes.
And it’s also why they can go wrong.
One well-known limitation is hallucination - the model can produce an answer that sounds polished and confident, yet are wrong or entirely fabricated. That is one reason human review remains essential.
So the goal isn’t to trust AI blindly but to use it well.
This Is Where Human Thinking Becomes More Valuable — Not Less
When you understand what AI is, and what it is not it actually reinforces the value of human thinking.
Your ability to reason, question, sense-check, interpret context, and apply judgement.
These human capabilities become more important, not less.
AI can accelerate tasks but it still needs direction, interpretation, and oversight.
That is why curiosity is not just about learning how to use the tools. It is about asking better questions, exploring what is possible, and recognising where AI adds value and where it still needs careful human oversight.
Curiosity Is the Bridge Between Fear and Capability
One of the biggest barriers I see is hesitation and a feeling people need to “understand AI” before they start using it. But both research and practical experience suggest the opposite. Curiosity drives engagement - Engagement drives learning - Learning builds confidence.
Organisations that encourage curiosity are usually far better placed to adopt AI successfully, because their people are more willing to experiment, test, question and iterate rather than wait for certainty.
Practical Reality
This isn’t about becoming an AI expert overnight but it is about mindset.
This isn’t about becoming an AI expert overnight, but it is about mindset - being willing to try the feature, ask the question, test the output, and form your own view.
That might be something as simple as turning on a feature like Xero’s automatic reconciliation, asking a tool like Xero’s Jax a question, and reviewing what comes back.
Sometimes it will work brilliantly. Sometimes it will not. Both outcomes teach you something.
Final Thought
If history shows us anything, it is that technology will keep changing. That part is inevitable.
What isn’t fixed is how we respond to it and the people who get the most value from this next phase will not necessarily be the most technical.
They might be the most curious.
Because in an AI-enabled world, curiosity is not just a nice-to-have. It is the skill that helps people keep learning, keep questioning and keep finding value as the landscape changes.