Season 5 - Episode 40: Too Early - or Time to Pay Attention?
How do we know whether a technology is still hype, simply too early, or beginning to become something that really matters?
In this episode of Simply Briefed, Kristine Lium speaks with Leo Rundgren Olsen, Junior Portfolio Manager at DNB Disruptive Opportunities and co-author of Postkort fra fremtiden / Postcards from the Future.
Together, they explore how we can become better at reading weak signals, understanding technological turning points and deciding what is worth observing, testing or acting on.
Key topics in this episode
Why technological change often moves slowly before it happens suddenly
How the S-curve can help us understand hype, timing and turning points
Why “we tried it and it didn’t work” can be a misleading conclusion
What happens when AI moves from answering questions to carrying out tasks
Why judgement may become more valuable as intelligence becomes more abundant
How analytical imagination can help us explore the future without losing touch with reality
Episode 40: Too Early - or Time to Pay Attention?
– With Leo Rundgren Olsen, Junior Portfolio Manager at DNB Disruptive Opportunities and co-author of Postkort fra fremtiden / Postcards from the Future
This week’s episode
Not everything new deserves immediate action. But dismissing something too early can leave us reacting too late. This episode explores how we can recognise meaningful change before it becomes obvious.
Most of us still experience AI through a screen.
We ask a question, receive an answer and perhaps complete something a little faster.
But AI is beginning to move beyond answering. Digital agents can increasingly plan and carry out tasks. Voice is becoming a more natural interface, while intelligence is being placed inside robots, vehicles and other machines that can act in the physical world.
The most interesting shift may come from what becomes possible when these technologies begin working together.
Slowly, slowly - then suddenly
A central idea in the episode is that technological change rarely follows a straight line.
Something can look promising, disappoint us and be dismissed, only to return later when the technology has improved, costs have fallen or the conditions around it have changed.
That is where the S-curve becomes useful.
It helps us ask whether a technology is still early, beginning to prove itself or approaching a point where it can start to matter.
The difficult question is knowing which situation we are actually looking at.
Is this hype? Is it a bad idea? Or is it simply too early?
When “we tried it” becomes a trap
One of the risks in fast-moving technology is that an early failure can become a permanent conclusion. We try something once. It does not work as expected. Then we decide that it does not work at all.
But the next version may be better. The cost may be lower. The infrastructure may have improved. The market may be more ready.
That does not mean every old idea deserves another chance.
But it does mean that timing matters.
In a world where capabilities can change quickly, the useful question may not be only “did this work before?”
It may be “what has changed since we last looked?”
Judgement in an age of abundance
The conversation also explores what happens when AI moves from answering questions to carrying out tasks.
Many organisations have added AI as a layer on top of existing work. But the bigger opportunity may come when work is redesigned around new capabilities, rather than simply adding AI to old processes.
As intelligence and execution become easier to access, productivity may increase.
But that also raises a more important question:
What becomes scarce?
One of the strongest ideas in the episode is that when intelligence becomes abundant, judgement becomes more valuable.
Access to AI may matter less than knowing where it actually creates value.
Analytical imagination
Leo uses the concept of analytical imagination to describe a way of thinking about the future. It is not about predicting perfectly. It is about combining imagination with evidence, pattern recognition and realism.
In simple terms: what could become possible, and what do we actually know?
That balance matters because there are two easy mistakes. One is to chase every new development because it feels exciting. The other is to wait until the change has already become obvious.
Analytical imagination gives us a more useful middle ground: staying curious, testing assumptions and looking for where real value may begin to emerge.
Your own S-curve
The episode closes with a practical way to bring this thinking closer to our own work.
We do not need to act on everything new. But we can ask where a technology or possibility sits on our own S-curve.
Is it something to observe?
Is it ready for a small experiment?
Or has it shown enough value to become part of how we work or build?
That question can help us avoid both extremes: running after everything and waiting until it is too late to respond.
Because the future may not belong simply to those with access to more intelligence.
It may belong to those able to exercise better judgement about where intelligence creates value.
🎧 Listen now on Spotify!
Host: Kristine Lium
About the guest
Name: Leo Rundgren Olsen
Title: Junior Portfolio Manager at DNB Disruptive Opportunities and co-author of Postkort fra fremtiden / Postcards from the Future
Background: Leo Rundgren Olsen is a Junior Portfolio Manager at DNB Disruptive Opportunities and co-author of the book Postkort fra fremtiden / Postcards from the Future (soon released in english). He is the youngest equity fund manager in Norway and his work sits at the intersection of investing and technological change, where he studies how emerging innovations reshape industries, competitive advantages and long-term value creation.
👉 Listen to the full episode of Simply Briefed to explore how we can recognise meaningful change, understand what is still hype or simply too early, and decide what is worth observing, testing or acting on.
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