The Workplace in the Age of AI: Why Human Curiosity Still Matters

“I’m not a robot.” For years, this simple test was enough to prove our humanity. But if robots can beat humans at chess, unfold complex proteins, and find black holes in the universe, surely they can tick a box. What can’t computers do these days?

With technology advancing at a breakneck pace, what does the widespread adoption of generative AI mean for all of us, the lives we lead, and the work that we do?

As Gen AI adoption has become widespread over the past 18 months, the first longitudinal research studies are beginning to reveal not just how AI is developing, but more critically, how AI affects people in the workplace. To delve deeper into this topic, I looked at three personas to identify the upsides and the downsides of AI adoption.

The Newbie

What’s the impact of AI adoption on new joiners to the workforce, or those with lower skill levels? For newbies, the results are mixed. On the one hand, less experienced employees working on their own can achieve higher performance levels. But these early successes bring a misplaced confidence, leading to a “phantom competence,” or confidence without mastery, while inhibiting their core learning. So, while they now enjoy enhanced autonomous performance from Day 1, newbies risk missing out on the development of core skills needed to evaluate the AI’s output, and the judgment and tacit knowledge that comes from years of acquiring them.

In response, our workplaces must be uniquely equipped to be places of lifelong learning. We already spend about 10% of our working time learning, and for the most engaged employees, this number is even higher. A 2023 study by Emanuel, Harrington & Pallais demonstrated that co-located teams exchanged 22% more feedback than teams located in separate buildings. So, the learning and training that the newbies need happen best when teams are physically together.

The Expert

For those who are highly skilled, AI can amplify their productivity and increase the quality of their work, in part by simulating input from experts in adjacent fields. However, Gen AI also exerts what Microsoft researcher Advait Sarkar calls a “mechanised convergence” on knowledge work, in which everything starts to look the same. This is a logical outcome of the statistical algorithms behind AI tools — the outputs of a predictive tool are likely to be predictable. So, while the expert benefits from enhanced productivity, increased output, and access to cross-functional expertise, they critically require exposure to diverse ideas to counter this homogenisation of ideas.

The workplace is ideally placed to connect experts to diverse ideas. In fact, if you have a relationship with someone different from you, chances are you met at work. In Gensler’s 2024 Global Workplace Survey, 77% of respondents said they formed friendships with people of other races and ethnicities in the workplace, and 88% formed friendships with people of other ages. Our workplaces can and should be environments that foster the exchange of these diverse perspectives.

The Team

The greatest benefits of AI appear to be at the team level. Dell’Acqua et al. indicated in “The Cybernetic Teammate” that, in addition to saving time, collaborating with an AI teammate is a more positive experience than working alone. What’s more, a team with AI is three times more likely to produce top-quality solutions than an individual without it. However, the most original ideas happen when teams ideate on their own first, unassisted by AI, before turning to the LLM’s. What teams need in the age of AI is a strong human team to frame problems, paint the art of the possible, and direct their cybernetic teammates.

Workplaces are a powerful tool to provide this human connection. According to Gensler’s 2025 Global Workplace Survey, people in high-performing workplaces are more than twice as likely to have positive relationships with their colleagues. And while AI can elicit positive emotions, it does not seem to allay loneliness or support engagement and belonging. Indeed, Chris Fussell, president of McChrystal Group, wrote in his book, “One Mission: How Leaders Build a Team of Teams,” that “face-to-face interaction with others is closely correlated with trust and quality of relationship formation.”

So, if ticking the little box isn’t what makes us human, then what is? What kind of roles will cybernetic teams rely on humans for?

From the What to the Why

Throughout human history, the pursuit of knowledge and the pursuit of understanding have been interlinked. Now, AI gives us knowledge on tap — but without the understanding that we usually gain along the way.

Anyone who has ever had a conversation with a 3-year-old knows that it’s not enough to tell them that no, they can’t drive the car. They want to know why. Is there something inherently human about wanting to understand how the world works, not just that it does? Is there something about humans that wants to know why things are impossible, so we can wonder if, just maybe, those things could be possible after all?

Even when we hold the collected knowledge of humanity at our fingertips, I believe we will still wonder why. And to answer this question, we need the perspectives of people who share our curiosity about the world. We need people who approach the same question from a different perspective and people who teach us new things and new methods. In an AI-powered world, we need human-centric workplaces more than ever.