AI could improve public services and help Finland respond to labour shortages and pressure on public finances. But replacing employees should not become the goal before the country defines the public value it expects AI to create.
If your competitive edge depends entirely on a model someone else owns, do you actually have a competitive edge at all? A look at what a century of technology history says about who really wins.
The prevailing assumption in AI discourse is that the biggest winners will be the companies that integrate AI most deeply into their products. The more agents, the stronger the competitive advantage. This assumption may well prove wrong, if we look at the broader history of technology.
A third of Finnish leaders believe AI could eventually outperform humans at strategic planning. But the same research reveals that accuracy alone isn’t enough. Leaders would rather work with a transparent, less accurate algorithm than a highly accurate black box they don’t understand.
Brussels has finally given digital sovereignty a legal definition. The European Commission’s Technology Sovereignty Package, published on 3 June 2026 after three delays, covers cloud infrastructure, semiconductors, artificial intelligence, and open-source software.
Let’s state the fact. Finland is using AI. It just isn’t profiting from it yet. Across the Nordic region, 79% of organisations report efficiency gains from AI — but only 18% report revenue growth. That gap is not a technology problem. It is an organisational one.
Finnish companies are adopting AI at a faster pace than ever. But adoption and impact are not the same thing. Drawing on four primary data sources — including FAIR’s own consultancy findings — this article examines why the gap between AI activity and measurable business value persists, and what it will actually take to close it.
We are living through an exceptional era. The most expensive technology in human history has been handed to us for almost nothing — and that is becoming a problem. When the price tag is invisible, learning doesn’t happen. When it becomes visible, being too late will cost you.
Cold but Fair? Algorithmic Management in the Workplace Algorithmic management promises efficiency, scalability, and data-driven decisions. It often delivers on that promise. The problem is not what algorithms do, but what they typically don’t do.…
Four in five active users adopted artificial intelligence within the past three years, yet fewer than one in four can identify the EU’s main AI law — a gap that researchers warn could expose businesses to unforeseen legal risk.
