Imagine waking up on a Saturday morning with a perfect plan. Breakfast is set, taking a walk with the same route as usual, the restaurant has been booked for a long time, and the evening ends with the movie you’ve already read the reviews about. Everything goes exactly as you imagined. It’s a good day, but when someone asks you a few weeks later what you remember from it, you have a hard time coming up with anything in particular.
Compare that to another day. You take a different route home from work because the street is closed. You happen to end up buying a meal in a small café you’ve never seen before. There you start talking to someone you would never have met otherwise. The conversation leads to an idea, a new collaboration, or maybe just a new way of looking at the world. When you later tell the story of the day, almost the entire story is about the unexpected, and easy to remember.
It’s no coincidence that our strongest memories often contain coincidences.
We humans often feel most alive when something breaks our expectations. And if it’s positively unexpected, there’s a sense of discovery that few planned activities can replace. At the same time, more and more parts of our modern society are built on the opposite. Algorithms want to predict our choices. AI wants to help us make the right choices. Recommendation systems want to reduce uncertainty. The calendar plans our time and the navigation system chooses the fastest route. Slowly but surely, we are building a society where the unexpected is seen as a problem rather than an opportunity. The question is whether we are also making ourselves less creative.
AI is making the world smarter but also more predictable
Generative AI is undoubtedly one of the most powerful tools of our time. It helps us write, analyze, summarize, program, and create images in seconds. It gives us access to knowledge that previously took days or weeks to find. For many tasks, this is a huge development. The problem arises when AI no longer just helps us solve problems but also begins to replace our own exploration.
We quickly get used to asking AI about everything. What should I write? How should I formulate myself? Which strategy is best? Which solution seems most plausible? Which book should I read? Which destination is best for me?
Each question seems reasonable. But together they change the way we think. Instead of investigating, we start optimizing. Instead of discovering, we start choosing the most likely option. Instead of letting the world surprise us, we let algorithms reduce the likelihood of surprises.
It’s efficient. But it’s not necessarily creative.
The greatest value often lies outside the predictable
Almost all great innovations have one thing in common. They were unexpected.
Not because they lacked logic, but because they were outside what the models of the time could predict. If the future had simply been a linear continuation of history, the internet would never have changed the world the way it did. Social media would never have gained the cultural significance it did. Nor could anyone have predicted that billions of images, texts, and films would one day be used to train artificial intelligence.
The most valuable things in the future are almost always precisely the things that today’s models have the most difficulty describing. This means that the better our tools become at predicting the “normal”, the more important the human ability to detect the abnormal becomes. Creativity is therefore not just about thinking smartly. It is about being able to discover the value in things that do not yet fit into any model.
Serendipity is the ability to recognize the gifts of randomness
The concept of serendipity describes a phenomenon that has long fascinated researchers in innovation and science. Many people think that serendipity means luck, but it is actually about something else. Serendipity occurs when a person discovers the value in something unexpected. Two people can encounter exactly the same random event. One moves on without reacting. The other stops because something seems interesting. The difference lies not in chance but in attention.
There is a risk with too extensive AI dependence. If AI always presents the most likely answers, the number of occasions where we ourselves need to explore the world decreases. We no longer train our own ability to detect unexpected connections. Slowly but surely, our ability to sense serendipity is at risk of weakening. We are getting better at finding the right answers. But worse at finding the questions that no one has yet asked.
Flow requires both skill and surprises
Flow is often described as the state in which we are completely absorbed in an activity. Psychologist Mihaly Csikszentmihalyi showed that flow occurs when the challenge is at the limit of our ability. If the task is too easy, we get bored. If it is too difficult, we get stressed. But there is another dimension that is rarely discussed.
Flow almost always contains an element of uncertainty. We do not know exactly what will happen next. We improvise, discover and adapt in the moment. The musician does not know exactly how the improvisation will develop. The researcher does not know exactly what the experiment will show. The designer does not know which idea will suddenly feel obvious.
When everything is already predetermined, some of the energy on which flow is based disappears. That is why randomness and flow are not opposites. They are often the prerequisites for each other.
The Dice Man is not really about dice
When Luke Rhinehart wrote the novel The Dice Man, he created a story that on the surface is about a man who lets a dice make decisions about his life. Many read the book as absurd humor or psychological provocation. But behind the story there is a much deeper message.
The book’s main character is not primarily trying to replace his own judgment with chance. He is trying to break free from his own habitual patterns.
We humans like to think that we choose freely, but we often repeat the same behaviors year after year. We choose the same restaurants, meet the same people, read the same types of books and attack problems in the same way. Our lives are gradually becoming more optimized but also more predictable. The dice therefore become a symbol of something bigger. It represents the courage to sometimes leave the usual traces.
This does not mean that we should leave important decisions to chance. But we can let randomness open doors that our habit would otherwise never have allowed us to discover.
Randomness can be trained
The beauty of random is that it does not require advanced technology. It requires above all a willingness to sometimes leave the usual.
Sometimes choose a book because the cover feels strange instead of because the algorithm recommends it. Get off the bus one stop earlier. Let someone else choose the restaurant. Start a meeting with the youngest person instead of the most senior. Read a scientific article from a field you know nothing about. Attend a conference where you don’t really belong.
Most such experiments do not lead to any major breakthroughs. But a few change the way you see the world. Just as evolution relies on many mutations to make a few decisive, creativity relies on many small deviations where a few lead to completely new perspectives.
The most interesting examples of randomness are often the ones we don’t notice
We like to think of randomness as dramatic coincidences. But many of the most important effects are much more subtle. An architect overhears a conversation between two children and suddenly realizes how people actually use a city square instead of how they assumed they would use it. A doctor becomes interested in music and discovers new ways to communicate with patients. A programmer starts growing vegetables and suddenly sees similarities between biological ecosystems and distributed computer systems. A city planner gets lost on vacation and discovers how small alleys create encounters between people in a way that wide thoroughfares never do.
None of these insights could have been ordered. They arise because people happen to be exposed to something they are not looking for.
Innovation needs more variety than standardization
In recent years, innovation management has become increasingly professionalized. There are frameworks, processes, and ISO standards that help organizations work more systematically with innovation. This is fundamentally positive. Common languages, clearer processes, and better follow-up can increase the quality of innovation work. But there is also a paradox here.
The more detailed we try to standardize innovation, the greater the risk that we will simultaneously standardize away the very unexpected that innovation thrives on.
ISO standards for innovation management are valuable when they help organizations create structure, learning, and a long-term perspective. But if the standards start to be interpreted as detailed recipes for how innovation should be done, they can defeat their own purpose. Innovation takes place in an environment that changes faster than any standard can ever be updated. What worked yesterday is not necessarily the right approach tomorrow.
A truly innovative organization therefore needs to use standards as support, not as a given. The structure should help people discover the unexpected, not make it impossible.
Randomness is a strategic resource
When we talk about strategy, the conversation often revolves around analysis, planning, and risk management. All of these are important. But the future is also shaped by things that no one could have predicted. That is why randomness also needs to have a place in our strategic thinking.
It is not about replacing knowledge with luck.
It is about understanding that complex systems develop through the interplay of planning and surprises. The organization that only optimizes what is known risks missing what is becoming important. The person who always chooses the safest path risks never discovering the opportunities that were a few steps away.
Make random your friend
Perhaps the biggest change we need to make is not technological but mental. Instead of asking how we can eliminate randomness, we should start asking how we can collaborate with it.
AI will become increasingly better at predicting, analyzing, and recommending. That is precisely why the human ability to detect the unexpected is becoming increasingly important. The most creative people of the future will likely not be those who compete with AI to find the most likely answer. They will be those who use AI where it is strong and at the same time consciously create space for what no algorithm can yet predict.
Randomness is not the opposite of intelligence. Randomness is the most interesting raw material that intelligence works with.
Just as evolution could never have created the diversity of life without mutations, tomorrow’s innovations will need people who dare to leave the predictable path sometimes. Perhaps the most important question, therefore, is not how to avoid randomness, but how we can become better at recognizing its possibilities when it unexpectedly knocks on the door.
