Tackling Disruption Playfully

Purposeful play is a critical behavior for executives facing disruptive change. In good old-fashioned play, the goal isn’t to win or lose. It isn’t to achieve against an objective standard. It’s to have fun. To experiment with different approaches. To see what feels good and what doesn’t. And in so doing, to learn and begin to build new capabilities that help turn disruption from a threat into an opportunity.

In my interview with Harvard Business School professor Amy Edmondson exploring the intersection between her research on psychological safety and disruption, she contrasted learning environments and performance environments. “If you’re on stage on Broadway each night, you hope that the performance is absolutely as good as it could be,” she said. “You want it to be close to perfect. If you’re in a classroom environment and things seem perfect, it’s not learning.”

Contrast the difference between performing, practicing, and playing.

When you are performing, you’re trying to achieve excellence against a given standard. Your goal is to do as well as you possibly can. Perhaps a judge is assessing your performance. If you fail to deliver against your standards, it’s disappointing. You seek to understand why and do better next time.

When you are practicing, you’re trying to consciously improve your skills so that you can deliver against a given standard in the future. Your goal is to improve. Ideally, you have a skilled coach who can provide real-time feedback to help you do that.

When you are playing, there’s no judge or coach. There might be someone who creates the context or sets the parameters for play, but the goal is simply to … play. Play is fun. But it is more than that. It creates the space for low-risk experimentation, capability development, and innovation. It can be awkward and uncomfortable, but that’s when we learn the most.

Playing With AI

In the early stages of disruptive change, there is always a period in which the right strategy is unknown and people are consciously experimenting with different approaches. Consider artificial intelligence. It’s clear that AI is going to have a big impact on a range of different tasks, roles, professions, and even industries. Exactly what that impact will be, who will win and who will lose, and what human capabilities are needed is still very much to be determined. It reminds me of being an MBA student in 1999, when the internet was entering the mainstream. We each built a website because, of course, everyone had to know Hypertext Markup Language — which, it turned out, was useless for the vast majority of us. But playing around with an emerging technology gave all of us greater fluency in and intuition about how the web functioned. And it was fun!

This is one reason why, in spring 2024, I ran a short-format pass-fail course on generative AI. Because about half of the graduates of the Tuck School of Business at Dartmouth College go into consulting, the course specifically focused on how consultants could use GenAI to better serve their clients. I am far from an AI expert, so I enlisted a couple of friends with AI experience to help provide pointers to the students. We sourced real companies with real problems that small teams of students sought to address with generative AI.

And then we got out of the way. We let the students play.

Without the pressure of a grade but with the constraint of a short time frame, students rolled up their sleeves and learned by doing. And GenAI’s natural language interface made experimentation and play incredibly easy. Students needed only to express their ideas, questions, and problems in the same way they would if they were chatting with a colleague to start getting useful insights.

One team that was helping Godiva Japan develop ways to expand its retail cafes used chain-of-thought prompting to develop an idea for a kiosk that could be placed inside office buildings. In this approach, the initial prompt incorporates logical examples so that the generative AI tool can apply the same type of reasoning to the problem at hand and iterate its answers. Another team had GenAI take on the persona of the CEO of a vehicle manufacturer to pressure-test their idea for a disruptive subscription model. A third used a half-dozen tools to develop a 30-second animated video clip with a voiceover to explain their idea for a home-based robot to an appliance manufacturer.

The No. 1 lesson students learned is that the biggest barrier to using generative AI was their own perception that it would be complicated to use. Once they got in and started playing, they quickly learned what worked and what didn’t, developing their skills through applied experimentation. “I didn’t fully expect to play so thoroughly in the course,” one student wrote in a post-class reflection note, “and now it has put me in the mindset of play with GenAI to see where it works for me personally and professionally.”

From Playground to C-Suite

In his recent book, The Anxious Generation, Jon Haidt opines that today’s youth don’t get enough opportunities for free play. One memorable example contrasts three different playgrounds. The first, from the 1960s, has children dangling from a beam that appears to be about 30 feet in the air with no protection. Yikes! Too much freedom. The second is a modern playground with gentle slides, small ladders, and plastic equipment. I’ve spent many an hour watching kids on similar structures. They are fine but boring. There’s no risk. It’s not that fun. Time passes, but there isn’t space for kids to experiment and learn.

Then there’s the playground spinner. Seeing a picture of one whooshed me back to my childhood. Haidt calls the simple wheel with eight handlebars on it the “greatest piece of playground equipment ever invented.” Why? It requires cooperation. The more kids, the better. The centrifugal forces make it uniquely thrilling. Lying in the center leads to “consciousness alteration,” he asserts. You can experiment with additional risk-taking by leaning off the side or playing catch while spinning.

“You can get hurt if you’re not careful, but not badly hurt, which means you get direct feedback from your own skillful and unskillful moves,” Haidt writes. “You learn how to handle your body and how to keep yourself and others safe. Researchers who study children at play have concluded that the risk of minor injuries should be a feature, not a bug, in playground design.”

Many executives, sadly, are out of practice with playing at work. After all, it’s called work. Play leads to learning, and the smartest, most successful people are the ones who often find it hardest to learn. As Chris Argyris observed in a 1991 Harvard Business Review article, “Because many professionals are almost always successful at what they do, they rarely experience failure. And because they have rarely failed, they have never learned how to learn from failure. … Their ability to learn shuts down precisely at the moment they need it the most.”

Play, I believe, creates the conditions where smart, successful executives can relearn how to learn. If you have kids — and I can attest that one of the many benefits of having four children is countless opportunities to play — look beyond playing Monopoly or catch with them and seek out opportunities to consciously join them in playing around with new technologies. If you don’t have kids, create your own virtual sandbox — dedicated time with the right equipment — and start mucking around.

Inside your organization, make it safe for your teams to play around with new technologies. Give them time, the tools, and maybe some rough guidelines. But don’t set specific objectives or demand specific outcomes. Let them explore and have fun. Do it with them. Screw up. Smile. Share. You’ll be surprised by what you learn — and how it makes you hungry to learn more. It will serve you well as you navigate today’s disruptive times.

“The MIT Sloan Management Review is a research-based magazine and digital platform for business executives published at the MIT Sloan School of Management.”

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