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There was a time when machines did not feel dangerous to me.
In the early 2000s, I played Go at 1 dan level. At that time, Go programs were still weak. Most of them played around middle kyu level, and for me they were easy to beat.
Chess had already been shaken by computers, but Go felt different. The game was too open, too subtle, too human. The number of possibilities was enormous. Strong Go players still believed that this was a place where human intuition, experience, and feeling had a special advantage.
Then came 2016.
AlphaGo beat Lee Sedol.
For many Go players, it felt like the world had cracked. Not because a machine had won a game, but because it had entered one of the deepest spaces of human strategic thinking and shown that it could see things we could not see.
Google had reached something that felt like the holy grail of AI research.
I remember my own reaction clearly. I was not angry. I was not trying to resist it.
I was amazed.
Part of me thought: welcome, new AI overlord.
But behind the joke, there was a serious feeling. If AI could see new possibilities in a game that humans had studied for thousands of years, then maybe many of our “best practices” were not final truths. Maybe some of the moves we thought were bad were simply misunderstood. Maybe our way of learning, teaching, and improving had to change.
And that is exactly what happened.
AI did not only make Go players weaker or obsolete. It gave them a new mirror. It showed new moves, new shapes, new ideas, and new ways to study. The strongest players did not become strong by rejecting AI. They became stronger by learning how to work with it.
Almost ten years later, AI is everywhere.
It is no longer only about Go. It is in writing, research, design, coding, customer service, analysis, planning, administration, and decision-making. Every organisation is now facing the same question Go players faced after AlphaGo:
Do we resist the change, or do we learn how to become stronger with it?
For me, the answer is clear.
I did not resist AI then, and I do not resist it now.
I use it in my work. I learn with it. I build with it. I challenge it. I also stay careful with it, because powerful tools need responsible use.
This is where digital strategy begins.
Not with buying every new tool.
Not with adding AI everywhere.
Not with following the hype.
A good digitalisation plan starts by asking better questions:
Where does your organisation lose time? Where is knowledge stuck in people’s heads? Where are teams repeating the same manual work? Where could AI help people think, write, analyse, decide, or serve clients better? Where must human judgement stay in control? What should be automated, and what should remain human?
The lesson from AlphaGo is not that machines replace strategy.
The lesson is that strategy itself changes when a new intelligence enters the room.
The organisations that win will not be the ones using the most AI tools. They will be the ones that understand how to combine human experience, business context, and AI capability into a better way of working.
That is what digital strategy means now.
Not doing everything.
Choosing the right moves.