With the passing of time, you notice how some insights stick with you and have an outsized influence on your thinking. For me, one of those insights came during my undergrad studies in psychology: The huge difference between a work group and a team.
I had somehow made it through childhood without team sports (or much sport of any kind) so perhaps the distinction was less intuitive to me than to others.
Unlike your average work group, I learned, a team is tightly knit. More than anything, it is marked by interdependence: All the team members depend on each other in order to get the work done. A well-functioning team must collaborate intensely.
Contrast this to the typical workgroup, where colleagues tend to work alongside each other. Tasks are divided up. You work in your swimlane. When you need to know something, you reach out to your colleague and ask. When coordination is needed, you call for a meeting. You discuss, and you go back to your swimlane.
Comfortable and predictable. Why take the trouble of constantly discussing back and forth, and generally just doing stuff together as intensely as a real team?
Because for some types of work, a team can produce way better results.
A well-functioning team, my course asserted, will often outperform a regular workgroup by a landslide if the work demands interdependence: When the problems are complex and ambiguous. When different perspectives, skills and information need to be integrated to produce the result.
It seemed obvious to me that most knowledge work fell into that bucket. Since then, I have honestly been waiting for organisations to transition to a genuine team setup. And sure; there are areas where true teamwork is common, including Product & Engineering and multidisciplinary healthcare teams. The benefits are often striking. And yet, the lion’s share of work is still performed in traditional work groups. We continue with the swimlane approach.
Apparently, we needed something to increase the value of interdependence even further. That thing might turn out to be – surprise! – AI.
Speaking to Linnea Bywall, the forward-leaning Head of People at the Swedish tech company Quinyx, made this exquisitely clear.
She told me that what’s keeping her up at night is not primarily AI upskilling, or how to handle AI-generated job applications. It’s how to organize work in the new AI reality. In the old era, she explained, each employee only had to do their part of work. She drew on her own background in athletics to explain the shift:
“Yesterday”, she said, “every employee just ran their leg of the relay, then handed the baton to the next runner. Now, everyone has to run the entire relay.”
In essence, Linnea’s message was that everyone needs to be more well-versed in the entire thing you’re producing. This is for at least three reasons:
AI expands individual reach. People can suddenly create suggestions, prototypes, or fully functioning tools outside their traditional function. In order for that to be valuable, you need to have sufficient knowledge about the area you’re entering.
Human capacity moves upstream. AI automation frees up time that can be used for more value-creating work. But only if you know how value is actually created in your particular organization – i.e., if you understand more than your individual job.
AI raises the bar for problems worth solving. Part of the things the organisation charged for yesterday can now easily be prompted or built by the customer themselves. This means you have to solve a harder problem. Those tend to cross functional boundaries.
A well-functioning team does just these things. The members engage in extensive knowledge sharing, over time making each member well-acquainted with the entire value chain the team is handling. If the team members hold various skillsets and work tightly together, they are also likely to arrive at more innovative solutions than any of them would on their own. In other words, the AI transformation might be the thing that finally makes true teamwork a must-have for organisations.
There is, of course, another possibility: AI could simply turn more of us into highly autonomous generalists. If one person can suddenly do what previously required five specialists, perhaps we need less teamwork, not more.
I suspect the opposite will happen in much high-value knowledge work. Larger, messier and more ambitious problems will require integrating perspectives rather than merely expanding individual scope.
Interestingly, organisations have long invested in making work groups feel more like teams: psychological safety, team building, retrospectives. But the big shift ahead for most organisations isn’t to schedule another team workshop. It’s to start redrawing actual ways of working.
Concretely, a true team can’t spend their days shifting between sync meetings and solitary work. Instead, effective teams spend a lot of time collaborating. Screensharing to look at each other’s current challenges, getting in front of the whiteboard to sketch out solutions to a problem, sitting together to continuously ask for feedback.
That means organisations and leaders will need to start reconsidering a whole host of things: how work days are structured, how colleagues interact, how tasks are divided, and how performance coaching and feedback gets done. For those who make that effort, there is a lot of potential for new creative heights and reaping the benefits of the new technology.
The age of AI may, somewhat surprisingly, turn out to be the age of the team.