Giving people better tools is one thing. Creating the conditions to use them differently is another. We're giving employees increasingly powerful AI tools. Tools that can generate ideas, analyse information, write code, create images and help people solve problems faster. So, it would be easy to assume that better tools will naturally lead to more innovation. But will they?
AI won't make your organisation innovative
At Arendalsuka, Norway's annual gathering for public debate and discussion on issues shaping business and society, the session “KI, psykologi og hysteri – 5 Ingredients for Workplace Innovation”, one comment offered a refreshingly simple perspective.
When the discussion turned to tools for creativity, one participant talked about experimenting with AI and coding tools. But when asked what her best tools were, she came back to something much more familiar:
Coffee and conversations.
It was a small moment, but it captured something important. AI can give people extraordinary new capabilities. But innovation doesn't happen simply because people have access to powerful technology. They also need the right conditions to do something new with it.
Giving people AI is the easy part
Much of the workplace AI conversation currently focuses on tools. Which AI should employees have access to? What can they use it for? What skills do they need? How can we encourage adoption? Those are important questions. But access to a tool and changing how work gets done are two different things.
An employee might have access to the best AI tools available and still spend every day moving from meeting to meeting, answering messages and working through a long list of existing tasks. Where does experimentation fit? One of the themes running through the Arendalsuka discussion was time. Creativity can't always be something employees are expected to squeeze in when everything else is finished. If organisations genuinely want people to explore new ways of working, they need to make room for it.
That doesn't necessarily mean launching a major innovation programme. It could simply mean giving people permission to spend time asking: Could we do this differently now?
Innovation starts with the people who understand the work
Another interesting point raised during the session was the danger of making innovation sound like a specialist activity. It can be tempting to create innovation teams, appoint innovation leads and hand responsibility for finding new ways of working to a small group of people. Specialist expertise certainly has a role. But many of the best opportunities to improve work are visible to the people already doing it. They know where processes are frustrating. They know which tasks take too long. They know which information is difficult to find.
And they know which seemingly small problems happen again and again. As one participant argued during the session, the people with the domain knowledge are often also the people best placed to ask the right questions. That becomes particularly interesting with AI. Instead of asking only, “What can this AI do?”, organisations can start with a different question: “What problems do our people already know we need to solve?” The technology then becomes a tool for exploring the answer, rather than the starting point.
Experimentation requires permission to get things wrong
There is another problem with asking employees to innovate. Innovation involves producing things that don't work. Bad ideas. Failed experiments. Strange first attempts. Questions that turn out to lead nowhere. That's not a flaw in the process. It's part of it. The session connected this with psychological safety. When people are worried about getting something wrong, looking foolish or being judged, experimentation becomes much harder. The discussion highlighted how stress and fear can narrow our attention when creative problem-solving requires us to explore more possibilities.
And AI creates an interesting tension here. Organisations want employees to experiment with a new technology whose possibilities are still emerging. At the same time, there may be considerable uncertainty around what employees should do with it, what is acceptable and what happens if something goes wrong. So, giving people an AI tool isn't enough. They also need boundaries they understand – and enough freedom within those boundaries to experiment. For HR and leaders, that means creating an environment where people can say: “I tried this. It didn't work. Here's what I learned.”
Sometimes serious problems need less serious thinking
One of the more unexpected themes of the session was humour. When organisations face difficult problems, our instinct is often to become more serious. We need an answer. There are budgets involved. There are deadlines. There may be customers, employees or citizens depending on the outcome. But the discussion explored how becoming intensely focused on solving a problem can also narrow the way we think about it. Humour and playfulness can help interrupt that. Ask an absurd question. Look at the problem from an entirely different perspective. Suggest an idea you know won't work just to see where it takes the conversation.
The objective isn't to make serious work trivial. It's to create enough space for people to think differently. That becomes particularly relevant with AI because the technology makes experimentation cheap and fast. You can explore an idea, challenge it, create alternatives and discard them within minutes. But people still need to feel comfortable doing that.
AI is a tool, not an innovation strategy
At one point during the session, AI was compared to a brush or a hammer: a tool that helps you create something, rather than something inherently creative in itself. It's a useful distinction. AI can make it dramatically easier to test ideas. It can help someone with no coding experience build a prototype. It can give an employee a starting point when they're staring at a blank page. It can help teams explore possibilities that previously would have taken far more time or specialist expertise.
But none of that tells an organisation what is worth improving. That still requires people who understand the work. People who notice problems. People who ask questions. People who talk to each other. And people who have enough time and trust to try something different.
This is where HR has a role
AI adoption is often discussed as a technology transformation. But if organisations genuinely want employees to use AI to improve how work gets done, there is a significant people dimension too. Do employees have time to experiment? Do they understand where the boundaries are? Can they share half-formed ideas without worrying about looking foolish? Are managers comfortable with experiments that don't immediately produce results? Are the people closest to the work being asked what could be improved? And do teams have opportunities to learn from each other's experiments rather than everyone discovering AI alone? Those are questions about culture, leadership, and ways of working. In other words, they're also questions for HR.
Better tools need the right environment
The five ingredients discussed during the Arendalsuka session were place, time, tools, trust and humour. They were presented as ingredients for creativity and innovation rather than as an AI framework. But there's something useful in applying that thinking to the current rush towards workplace AI. We have never had more powerful tools for creating, experimenting, and solving problems. That doesn't mean innovation will automatically follow.
Organisations still need to give people space to think. Time to explore. Trust to experiment. Opportunities to work with other people. And permission to occasionally come up with something that doesn't work. Because ultimately, AI won't make an organisation innovative. People will. AI might just give them some remarkable new tools to do it with.
About this article
This article is part of our The human side of AI series ,inspired by sessions at Arendalsuke, Norways annual gathering for public debate and discussion on issues shaping business and society. It draws on the session “KI, psykologi og hysteri”, with Kjell-Vidar Åhman Teig, Innovation Lead at Yulieta by Innocode, and Vidar Ulset, Associate Professor of Psychology and Clinical Psychologist. The session explored what psychology, innovation and practical experience can teach us about creating a healthy culture for innovation and technological change.
Source: Arendalsuka – KI, psykologi og hysteri
