Rather than an obligatory “what I am grateful for” post over the New Year period, I took some inspiration from the topics discussed at the various family events I attended over the holiday. Overwhelmingly, I have had family and friends ask me about AI. This has also been a recurring theme all year. These questions are expected in my work, where I advise founders, executives, and boards. What surprised me was how often the same questions came from friends and family who do not work in technology.

They were not asking about tools or models. They were asking what this means for their work, their kids, and their sense of stability. As the year closes, it feels like the right moment to write this down. Not as a prediction or as hype. Just as a reflection shaped by the changes I have seen across my own life.

Growing Up With Change

I was born in New Zealand in the early 1970s. It was a small country, far from everything, and slow by design. Change still arrived. It just arrived quietly. I grew up without computers in the home. Phones stayed on the walls. Music lived on vinyl. Learning took effort. If you wanted answers, you asked someone or went looking for them. Knowledge had friction, and time sat between curiosity and understanding.

That friction mattered. It shaped patience. It taught respect for process. Learning felt earned rather than instant.

A Habit of Learning

My grandfather shaped how I learned more than any classroom ever could. He believed learning was a habit, not an event. Every few years, he bought a full set of encyclopedias and treated them as working tools, not decoration.

We shared a love of tennis. I played every week at the local tennis club. At the end of each session, the coach gave us history questions to take home. Names, matches, rule changes, rivalries. We had a week to find the answers. My grandfather and I sat at the table together. We pulled volumes from the shelf and worked page by page. We checked dates. We debated details. We talked about why the game changed and what stayed the same. Learning was slow, deliberate, and shared.

That routine taught me something I did not recognize at the time. The tool mattered far less than the posture. Curiosity came first. The encyclopedia simply supported it.

Watching Tools Appear and Disappear

Years later, encyclopedias vanished. Search engines replaced shelves of books. Answers arrived in seconds. Some people felt unsettled by that shift. My grandfather would not have. He was never loyal to encyclopedias. He was loyal to learning.

I watched the same pattern repeat across my life. I remember the first time we connected to the internet through a modem. The sound filled the room. Pages loaded line by line. It felt fragile and exciting at the same time. I remember sending my first text message. It felt awkward and unnecessary. Why type when you could just call? That question did not last long. I remember microwave ovens arriving in kitchens. People worried about safety and quality. Today, they barely register as technology.

I remember being the only kid in the family who could program the VCR. Blinking clocks everywhere. Instructions taped to the side. That small skill carried real value for a brief moment. Each change followed the same arc. Confusion came first. Resistance followed. Then quiet adoption. Then normal life.

Personal computers arrived. Fax machines appeared and disappeared. Mobile phones spread fast. Email replaced letters. The consumer internet collapsed distance. Each step felt unsettling at first. Each one became ordinary sooner than expected. Fear always showed up early. It never stopped progress. It only slowed acceptance.

Why AI Feels Different

AI fits into that same pattern, but with one important difference. The speed is much faster. Change that once took decades now takes months. Anxiety fills the space where experience has not yet formed. Denial appears here, too. Some hope this will pass. Some treat AI as a fad. Some refuse to engage at all. That posture has never worked.

AI is not going away. It is not a feature. It is not a phase. It already sits at the heart of how work gets done. Denial only delays learning, and delay carries a cost. Many people try to make AI feel smaller by calling it a search engine. That framing feels safe, but it misses the point. Search retrieves existing answers. AI participates in thinking itself. It drafts, critiques, compares, and refines ideas as they form.

I think of AI as a sparring partner for thought. It pushes back without ego. It forces precision. It exposes weak logic quickly. Used well, it raises the standard of thinking rather than lowering it.

What the Dotcom Boom Actually Taught Us

The internet did not fail in the late 1990s because it was a bad idea. It failed because most people misunderstood what it was good for. Almost every company called itself a dotcom. Few could explain how customers were better off. Fewer understood economics, distribution, or trust. Many confuse presence with value.

The companies that survived respected fundamentals. Amazon made buying easier and broader. eBay created trust between strangers at scale. They applied new tools to old truths. Most others added “.com” to old thinking. That thinking collapsed under pressure.

AI sits at a similar inflection point. Many teams say they are doing AI. Few can explain what improves for the user. Even fewer can measure it. Adding AI to old workflows without rethinking the work itself will fail for the same reasons. AI does not change what matters. It accelerates consequences.

What Social Media Should Have Taught Us

Social media offers a more recent lesson, and many of us lived through it in real time. It arrived with optimism and speed. The promise centered on connection. Distance would shrink. Voices would multiply. Information would move freely. Some of that promise landed.

What we did not do was pause long enough to ask how these systems would behave at scale. We did not debate incentives early. We did not think deeply about responsibility. Adoption ran far ahead of reflection. By the time harder questions surfaced, habits were already set. Business models hardened. Behavior shifted. Changing course became far harder than shaping it would have been.

If we could reset that moment, the debate would not be about stopping social media. It would be about boundaries. What behavior systems reward? Where does trust belong? What parts of life should resist optimization? Those debates came too late. The cost of that delay is now visible.

What That Means for AI

AI gives us another chance, but the window is smaller. AI will move faster than social media ever did. It already touches work, education, creativity, and decision-making. The question is not whether it should exist. That question is already answered. The real question is how deliberately we shape its role.

Rules will matter, but they will lag behind behavior. Transparency matters. Provenance matters. Accountability matters. When AI systems influence decisions that affect livelihoods, health, or freedom, responsibility cannot disappear. Culture matters just as much. Norms matter. Education matters. Shared expectations matter.

We should debate where AI assists and where it leads. We should debate which decisions remain human-owned. We should debate what skills still deserve practice, even when machines perform faster. None of this requires predicting the future. It requires humility about incentives and honesty about tradeoffs.

Parenting in an Age of Uncertainty

This uncertainty is most evident in parenting. Some of the most challenging questions I get come from parents. How do we guide our kids now? What should they study? Is college still worth it? What careers make sense in a world shaped by AI? There are no clean answers. No one can predict the future. Many of the jobs our kids will hold do not exist yet. Many of the skills we value today will look different. That makes it tempting to search for certainty. To hunt for the right major or the safe path. That instinct is understandable, but it misleads.

Education was never about locking in a job. It was about learning how to learn. That mattered before AI. It matters more now. Specific tools will age quickly. Durable skills will not. Writing clearly. Reasoning well. Asking good questions. Understanding tradeoffs. Taking responsibility. Working with people who think differently. Those skills travel. They are not owned by any single career or degree. College still has value, but not as a guarantee of success. Its value lies in exposure, discipline, and growth. The same is true for alternatives. None comes with protection.

The mistake would be coaching our kids toward certainty. Certainty is disappearing. The better posture is curiosity and resilience. As parents, we cannot map the road. We can help our kids build instincts for walking it.

Learning as the Only Real Response

The response to AI cannot be denial or distance. It has to be engagement. Learning AI does not start with theory. It begins with use. Write with it. Think with it. Ask it to challenge work you already understand well. Familiar ground reveals limits quickly, and limits build confidence rather than fear. Every major shift creates people who shape outcomes and people who react to them. The difference rarely comes down to intelligence. It comes down to posture.

Closing the Year

As the year ends, I think back to that table in New Zealand. Two people. A stack of books. A shared belief that learning mattered. The tools have changed. The posture has not. Sit down. Ask better questions. Stay curious. Fear fades once understanding grows. That has always been true.