“You're way too aggressive on AI”

"You're way too aggressive on AI."

A few weeks ago, someone on our technical team made a comment that stopped me in my tracks. I have a lot of respect for the person who said it, and I'm fairly sure it was meant as a gentle warning. That maybe we should slow down a bit.

But I actually took it as a compliment. Not because our goal is to use as much AI as possible. It absolutely isn't. But because I think the biggest risk right now isn't necessarily experimenting too much. It might just as easily be learning too slowly.

And maybe this is really about something much bigger than AI.

This isn't my first technology shift

I've been lucky enough to be part of several major technology shifts throughout my career. I worked at Telenor when mobile telephony really started changing the world, and was there when Telenor expanded internationally. Later came the dotcom wave, digitalization, and the shift to cloud-based solutions. Now we're in the middle of the AI shift.

The technologies have been different. The pace has been different. But I find it interesting how much still stays the same. When new technology arrives, no one really knows where it will end up. The realm of possibility is enormous, expectations get inflated fast, and there's always a healthy dose of hype.

I remember the dotcom period well. At one point it almost felt like all you needed was a PowerPoint deck with ".com" written somewhere, and the funding would follow. We know how that went for a lot of those companies. That doesn't mean the internet didn't change the world, of course. And that might be exactly the point.

You don't need to believe the hype to see that the world is changing

I think I see some of the same mechanisms around AI today. There's an enormous amount of talk about AI. Some of it is fantastic. Some of it is oversold. Some of it will fundamentally change how we work, and some of it we'll probably laugh about in a few years. I don't always know what belongs in which category.

But after going through several of these shifts, there's one thing I'm fairly certain of: when a technology has the potential to change the terms of how we work and run businesses, we as leaders can't afford to sit on the sidelines waiting for the final answer. We have to learn while the development is happening.

That doesn't mean throwing ourselves at everything new. It also doesn't mean experience has suddenly become less important. On the contrary, I believe experience is one of the most valuable resources we have as leaders. Experience gives us perspective, judgment, and an understanding of patterns that take many years to build.

But experience alone isn't enough. It has to be combined with the willingness to challenge what we already know.

What worked yesterday isn't necessarily the best answer tomorrow

This might be one of the hardest things about having a lot of experience. We know what has worked before. We've built up methods, ways of working, and beliefs over many years. That's valuable. But it can also make it tempting to meet new problems with old answers.

In periods of major technological change, I think curiosity becomes especially important. Not curiosity as a nice personality trait, but as a very concrete leadership skill: the willingness to spend time understanding what's happening, testing new ways of working, and changing your mind when reality calls for it.

And right now, things are moving fast, very fast. That might be the biggest difference between the AI shift and several of the technology shifts I've been through before. The time we have to understand, learn, test, and adjust keeps getting shorter. That doesn't make experience less valuable. It makes the ability to combine experience with continuous learning more valuable.

We won't get everything right

Choosing to be on the offensive with AI doesn't mean I think we'll make all the right decisions. We definitely won't. We'll test things that don't work. We'll spend time on technology that turns out to be less interesting than we thought. And we'll change our minds along the way. That's part of learning.

But we also get things right, sometimes faster than we expected ourselves. We rebuilt the entire capassa.com website in a single week, from idea to launched site, by working closely with AI tools throughout the whole process. A few years ago, the same work would probably have taken weeks, maybe months. That doesn't prove AI solves everything. But it's a concrete example of how much faster we can move when we actually use the tools, instead of waiting for someone else to test them first.

The alternative is waiting until someone else has figured everything out first. And in a development moving as fast as it is right now, I think that alternative could end up being far more expensive.

To me, this is therefore less about being "aggressive on AI" and more about being aggressive on learning.

That's also something I believe in as a leader. I've long had a fairly simple principle for the people I work with: you should come to work, have fun, and learn something new. Ideally every single day. The day you feel you're no longer learning, I think we should talk. Because then we need to either find new challenges, change something about the role, or figure out why the development has stalled.

The same principle obviously applies to me. The day I decide that my experience means I no longer need to get familiar with new technologies, challenge my own assumptions, or learn new ways of working, I think I'd fairly quickly have a problem as a leader. AI is just the latest example. There will be something after AI too.

Are we too aggressive on AI?

Possibly.

We already live in a reality with more opportunities, more information, and more decisions than most of us can keep up with. New technology isn't going to make the need for prioritization any smaller. So this isn't about every leader now spending their time testing every single AI tool that comes along. We have to choose. But to choose well, we need to understand enough to know what we're choosing between.

If the alternative is leaning back and waiting for things to settle, I'd rather take the risk on this side. Because after going through a few technology shifts, I still believe in the value of experience. Maybe more than ever. But I also believe experience has the greatest value when it's combined with something that's actually quite simple:

The willingness to keep learning.