Research: Workers Who Thrive Alongside AI Share One Key Trait

Whether AI Helps or Hurts at Work Comes Down to One Factor, and It’s Not the Tech

A doctoral dissertation from Finland argues that AI may be changing not just what decisions get made at work, but how humans think, feel, and build careers along the way.

For millions of workers, artificial intelligence has gone from a futuristic buzzword to a daily reality. It drafts emails, summarizes reports, and suggests strategies inside real companies, with real stakes. But one question has lingered beneath all of it: What is AI actually doing to the people who work alongside it? A doctoral dissertation from the University of Vaasa in Finland, takes a hard look at that question, and the answer might surprise even the most tech-savvy executive. The biggest factor in whether AI helps or hurts an organization isn’t how powerful the technology is. It’s whether the company has figured out how to work with it in a way that actually makes sense for the humans involved.

Researcher Zhe Zhu spent years pulling apart this puzzle from multiple angles, examining everything from how companies make big strategic calls with AI assistance to how individual employees feel about their jobs and futures when an algorithm is sitting alongside them. Rather than simply asking whether AI is good or bad for the workplace, Zhu asked a harder question: How does it actually change things, and for whom?

Four Studies, One Big Picture on AI in the Workplace

Zhu’s dissertation, titled Generative Artificial Intelligence in Organizations: Strategic Decisions and Human Adaptations, is built from four separate but connected studies, each designed to answer a different piece of the larger puzzle.

The first study reviewed existing scientific literature on how humans and AI systems interact when decisions need to be made. That review helped identify where knowledge gaps existed, and there were plenty. Most prior research had looked at either the company-level strategy side of AI or the human side, but rarely both at once.

The second study examined how real organizations are actually making the shift to AI. Rather than relying on surveys or lab experiments, Zhu analyzed podcasts aimed at business professionals, conversations where practitioners spoke openly about what was working, what wasn’t, and what they wished they had known. Companies are moving from treating AI as a shiny new toy to something far more serious, a core part of how they operate and compete. But that transition is messy and filled with strategic challenges that go well beyond simply buying new software. Zhu’s analysis produced a practical framework pointing to factors like clear decision-making roles between humans and machines, ethical guardrails, and genuine attention to the people actually using the tools.

How Workers Actually Feel About AI on the Job

The third and fourth studies shifted the spotlight from organizations to individuals, specifically to how employees experience AI at a psychological and professional level.

Using survey data and a statistical method that tests how different factors are related, Zhu examined what shapes whether a worker feels engaged and energized in an AI-assisted job.

The findings pointed to something called “dual appraisal.” A warehouse worker, for example, might see an AI scheduling tool as a chance to move into a supervisory role, and simultaneously worry it could make their current position redundant. Both reactions sit in the same person at the same time, pulling in opposite directions. When workers lean more toward the opportunity side, they tend to be more engaged and motivated. Factors like job security concerns and how easy the AI tools are to use shape which way that internal scale tips.

The fourth study took a longer view, asking how working with AI affects a person’s career over time. Focused on 361 expatriate professionals, people already navigating an especially layered mix of uncertainty and change, it found that AI collaboration alone did not directly produce better career outcomes. The effect ran through career adaptability, a person’s readiness to stay curious, plan ahead, and take ownership of their own development. Workers who brought that flexibility to the table were more likely to see lasting career benefits. Trust in the AI system and a sense of job security also shaped the picture.

What This Means for Companies and Workers

For companies, the message is clear: dropping an AI system into existing workflows and hoping for the best is not a strategy. Organizations need to rethink how decisions get made, who is responsible for what, and how employees are supported through the transition. Ethical oversight, transparency about how AI-generated information is used, and genuine attention to workers’ job security concerns all matter.

GenAI as a ‘Socio-Technical Collaborator’ in the Modern Workplace

Zhu argues that generative AI, the kind that writes, generates, and creates rather than simply predicting or sorting, is better understood as a “socio-technical collaborator.” Unlike a calculator or a search engine, it doesn’t wait to be queried; it actively shapes how options get framed, discussed, and ultimately decided. Most organizations are still treating it like software. The ones that figure out it’s something closer to a participant in decision-making are likely to be far better positioned than those that don’t.

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Disclaimer: The findings discussed in this article are based on a doctoral dissertation that had not yet undergone public examination at the time of publication. Results from the survey-based studies rely on self-reported data and should not be taken as definitive causal conclusions. The career findings specifically reflect a study of expatriate professionals and may not apply to all workers or workplace contexts.

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