AI is transforming industries worldwide, yet finance and accounting remain surprisingly hesitant adopters. New research from Haaga-Helia reveals the real barriers holding the sector back—and the human-centred solutions that could unlock AI’s potential.
In our first article, we showed that AI’s impact will be felt most acutely in office work, not just tech jobs. But awareness alone won’t protect your organisation. The companies and regions that thrive in the years ahead won’t be those with the lowest AI exposure — they’ll be the ones that prepare now. Here’s how to start.
The AI disruption everyone’s talking about? You’re probably looking in the wrong place. New research from MIT shows the real impact won’t hit tech jobs first—it’s already reshaping the office and administrative work that exists in nearly every organisation. This article reveals where AI’s hidden risk zone really is. Our next article shows you how to prepare before it’s too late.
What if young people’s phone phobia isn’t a problem at all, but rather a sign that the workplace is changing? When a third of Gen Z avoid phone calls and half trust AI more than their own manager, perhaps algorithmic management isn’t a threat anymore — but a solution to workplace transformation.
The future of work may not be about replacing humans with machines, but multiplying human capacity through digital twins that work simultaneously across multiple tasks. This transformation promises unprecedented productivity gains, but raises profound questions about compensation, ownership, and labour rights when one worker can do the work of five.
Despite tremendous advancements in AI, most organizations still struggle to turn it into real, repeatable value. Many companies experiment with tools like ChatGPT or Microsoft Copilot, run a few pilots, then hit a wall when they try to connect AI to their actual processes and data.
Only 26 per cent of Finns feel they possess sufficient skills to utilise AI – at the same time as the EU AI Act makes AI literacy mandatory. The question is no longer whether personnel should be trained, but how to do it effectively before supervision intensifies in August 2026.
AI was supposed to make knowledge work easier and more efficient. Instead, three-quarters of employees report increased workloads, and nearly half admit they have no idea how to extract the promised productivity gains. What went wrong – and more importantly, how can we fix it?
Enlightenment philosophers believed that knowledge liberates. The EU AI Act relies on the same conviction, imagining that an enlightened citizen can identify deepfakes. In the third and final part of this blog series, we examine the transparency paradox and three alternative paths forward.
Algorithmic management raises fears, but at its best it can make leadership more equitable than traditional human management. As routine tasks become automated, managers gain time for what truly matters: leading people and thinking strategically.
