As the opening keynote of TNC26, one of Finland’s leading voices in technology, Maria Ritola brings perspective shaped at the intersection of articifial intelligence, research, and human collboration. Her current work focuses on organisational transformation particularly helping researchers navigate complexity, making sense of vast volumes of knowledge in ways that are both faster and more meaningful.
But beyond the technology itself lies the question: what does it take to build successful teams, and sustain a good work-life balance in an increasingly digital world? Drawing on her experience with exponential technologies at Singularity University in the Silicon Valley and her role as a public voice on Finnish TV, Ritola challenges us to look beyond efficiency and rethink how we define productivity, leadership, and balance. Ahead of her keynote, I spoke with Maria about the evolving nature of work, the role of AI in shaping team dynamics, and why the future of work may depend less on the tools we build, and more on the ways we choose to work together.
There’s a growing tension between productivity and wellbeing in highly digital environments. From your perspective, what distinguishes a high-performing team from a healthy one and can the two truly coexist?
I’d say that the tension is real, but I’d argue it’s a symptom of a management failure rather than an inherent trade off. When I think about what distinguishes a high-performing team from a healthy one, the honest answer is: not much, when both are functioning well. Google’s Project Aristotle found that psychological safety, the belief that you can take risks and speak up without punishment, was the single strongest predictor of team performance. That’s also the definition of a healthy team culture. The two concepts converge. Where they diverge is when organisations pursue performance through pressure. You can get short-term output by maximising hours, digital availability, and monitoring. Teresa Amabile’s research shows that when people feel they are being watched, timed, or bribed to be creative, they become less likely to take risks and more likely to take the “safest” path to a solution.
In digitally distributed teams, where presence is often virtual, what qualities matter most and what leadership habits need to be unlearned?
In digital environments specifically, I think the key variable is autonomy. When people have control over how and when they work, both wellbeing and output are likely to improve. The problem is that many digital cultures do the opposite. They create the illusion of flexibility while actually increasing surveillance and always-on expectations, which triggers chronic stress responses and kills the kind of deep, focused work where the best output happens.
So can the two coexist? Yes, but only when leadership doesn’t treat wellbeing as a perk. That means protecting focus time, setting clear norms around connectivity, and measuring outcomes instead of activity. In my view, a truly high-performing team is almost by definition a healthy one, because the conditions required to sustain high performance over time are the same conditions that protect people.
You’ve seen how culture shapes innovation. What can organisations in R&E learn from Nordic approaches to trust, autonomy, and work-life balance?
What I’d like to highlight here is trust that is treated as infrastructure, not a reward. In most organisations, trust is something you earn over time through demonstrated performance. In Nordic contexts, it often seems to be the starting point. My experience, although it comes from the technology sector and in a startup environment, is that for creative work that includes intellectual risk-taking, you have to be willing to be wrong, to pursue an idea that might not work, to challenge established thinking. Those behaviours, also required in the R&E sector, flourish in high-trust environments and get suppressed in high-surveillance ones. Some additional points to raise in this context. First, measure outcomes, not presence. Be good at separating output from performance theatre. Second, protect autonomy.
The research on self-determination theory is unambiguous: when people have genuine control over their work, quality and motivation both go up. That, again, is as true for a researcher as it is for a technology entrepreneur. And third, take recovery seriously. Recognise that sustainable performance requires genuine rest. An exhausted researcher is not a productive one. And just to make sure, the Nordic countries are not immune to the challenges raised above. Startup environments, for example, can be extremely vulnerable to short-term thinking, where wellbeing is compromised for long periods of time. And similarly, academia seems to grapple with the challenges of precarious short-term contracts, intense “publish or perish” pressures, and oversight driven by rigid funding models.
You often speak about making complex technology more human-centric. What does “good work” look like in an age where AI is increasingly embedded in how we think, collaborate, and decide? What’s one misconception about AI and the future of work that you wish we would finally move beyond?
For me personally, good work, at its core, has always meant the same things: work that is meaningful, that allows you to make genuine progress, and that uses your distinctly human capacities, judgment, empathy, ethical reasoning, creative synthesis. What changes in an AI-embedded environment is not the definition of good work, but the conditions required to achieve it.
When AI handles certain kind of cognitive tasks what remains, and what becomes more valuable, is precisely the work that resists automation. The ability to sit with ambiguity, to weigh competing values, to build trust with another person. To ask the right question rather than just answer the one given. In that sense, AI doesn’t diminish the human element of work. At the same time, however, it needs to be recognised that certain tasks will be – and have already been – automated, and it has already had a real impact on the job market. Then ‘if implemented well’ is just getting a lot of stuff done, the risk isn’t that we go after more output, faster, with less reflection. I think that’s a path toward burnout and mediocrity, not genuine performance. As for the misconception I most want us to move beyond, it’s the idea that AI and human intelligence are in competition. That framing leads organisations to ask the wrong question: ‘What can AI do that humans used to do?’ The better question is: ‘What kind of human work becomes possible when AI handles what AI is good at?’
And finally, as you open the plenary at TNC26, what is the one question you hope the audience will leave asking themselves?
Are we building infrastructure for humans, or are we slowly building humans around infrastructure?
About Maria Ritola
Maria Ritola is a Finnish entrepreneur, keynote speaker, and technology thought leader working at the forefront of AI and organisational transformation. She is also the co-founder of Iris.ai, an award-winning AI company that specialises in intelligent knowledge management. Maria has been named one of the most influential women in Nordic technology and a top AI expert in Finland. A prominent voice in the national media, Maria regularly dissects the latest trends in AI and the digital economy.
