EditorialPeople View Teams Managed by AI as Less Creative

'Focus on benefits rather than features' has long been a marketing mantra. The logic being that it's not what a product does that matters, but how it benefits the end user. The same should be the case with the deployment of technologies, such as AI, in the workplace. Alas, a study from Northeastern University reminds us that it seldom is.

When managers focus on features over benefits, they strip out the people side of the equation and fall into the trap of simply installing a new technology and hoping for the best. This approach is destined for failure, as workflows and processes around a technology need to change for it to be effective. We've known this for decades now, at least since Michael Hammer's famous essay on the reengineering required to get the most out of the computer revolution in the late '80s.

When Deploying Technology, People Matter

Business process reengineering is sufficiently well developed that most people understand its benefits whenever we think of new technology. What is perhaps less well understood is how technology changes how we think about ourselves.

The Northeastern researchers remind us that any new technology has the potential to improve employees, teams and organizations, but we need to view them through a lens of their impact on people. For instance, if AI makes us think we need to invest less in our people or makes us view our colleagues as less creative, that's not a positive outcome.

The researchers conducted a handful of experiments where they asked volunteers to compare the creativity of two groups of employees, one of whom was managed by a human boss, and another that was managed by an algorithm. The results suggest that people universally view those teams managed by algorithms as less creative than those managed by a human.

Does AI Make Us More or Less Creative?

Of course, this is a matter of perception, but is AI making us more or less creative? Researchers from the University of South Australia posed that question in a study. The results found that while AI can produce creative-looking work, it still depends on human input. 

That human input and oversight might in many cases come by way of our managers, so it's understandable that we worry about the impact on our creativity when we have an algorithm for a boss.

The Northeastern study also suggests that human managers may be better at spotting skills in people that an algorithm might overlook. This not only reduces the creative capabilities of the team but might even contribute to lower employee engagement, higher absenteeism and staff turnover.

There have also been longstanding concerns that by outsourcing so much of our cognitive work to AI, we're dulling our capabilities. This is especially so when it comes to creativity. Although we assume creativity is some kind of Eureka moment, it's largely a cumulative process of our past experience that allows us to recombine ideas in novel ways.

“One of the big benefits talked about with AI is its ability to increase efficiency, which directly connects to creativity. Let the AI take care of the mundane stuff, and then your workers can be freed up to work on the more creative stuff,” the Northeastern researchers write. “But what our work shows is that even if that’s true, there might be consequences that haven’t been considered yet — that if AI actually allows people to be more creative, they might be viewed as less creative regardless. And what our work shows is managers might choose to invest less in those people on those AI-managed teams.”

Why the Perception Gap?

What’s behind that perception? What is making us view people as less creative when they work with, or under, AI? The researchers believe it has a lot to do with our understanding of the technology, which they posit is far lower than AI's actual capabilities. If we view AI as not being creative, then it's easy to assume that AI-managed teams won't be creative either.

This perception gap doesn’t just affect how work is evaluated — it could also shape career trajectories. It’s entirely possible that employees under algorithmic management could be overlooked for promotions or high-profile assignments, regardless of their actual performance. Even in hiring scenarios, two candidates with identical résumés might be judged differently based on whether they were previously supervised by a human or an algorithm.

The study highlights a deeper issue: a structural disconnect. “There’s a disconnect between this fancy new thing and how it affects people. A big difference between the idea of AI in the abstract and when the rubber meets the road," the researchers explain. "There’s also a disconnect between top management who make the choice to implement AI and middle managers who actually have to oversee it.”

A Renewed Call for More Humane Workplaces

The researchers are clear that the successful implementation of AI-driven systems will require more than just technical integration. It demands a cultural shift.

“Acceptance of algorithmic management may therefore require more than merely implementing it; instead, it may require substantive change of organizational norms and culture,” the Northeastern researchers explain.

For years, people like Gary Hamel have advocated for more humane workplaces, and with the march of AI, this has never been more pertinent. Too often, organizations look at AI in terms of replacing humans rather than augmenting them, but even that isn't enough if it strips employees of the very things that make them human. For companies to remain creative, we need to ensure that human capabilities remain respected and celebrated.

In other words, if we want AI to enhance our creativity and not diminish it, we must remain intentional about how it’s deployed — and never lose sight of the people using it.

Editor's Note: Read more thoughts on how to best introduce AI into the workplace below:

• Why HR and IT Must Join Forces for AI to Succeed — The overlooked partnership at the center of real AI adoption.
• Leadership at a Crossroads: Thriving Through Change in 2025 — The pressure to invest in technological innovations might lead you to believe it should come at the expense of workforce investments. That's a false dichotomy.
• An AI Roadmap for the Next 5 Years — Developing an AI business plan with clear, practical goals for the one, three and five-year horizons is the key to delivering real-world business results.