Beyond the Algorithm: AI as a Business and Organizational Challenge
Artificial Intelligence (AI) is often framed as a technical phenomenon—a matter of algorithms, data pipelines, and computing power. But this framing tells only part of the story.
Master's Study: AI sparks both unrest and excitement among knowledge Workers
Are you a pioneer or a skeptic? Four factors are essential for succeeding with AI as an effective workplace tool, according to a new master’s study.
AI is advancing rapidly, with new tools like ChatGPT, Eppi-Reviewer, and Copilot being introduced at an incredible pace. But employees in a Norwegian healthcare organization revealed mixed feelings about this fast-moving AI train.
Some see AI as a creative sparring partner that boosts efficiency and engagement, while others worry about errors, ethical dilemmas, and the loss of professional identity, according to a new Master’s study by Tordis Dybvik Jensen and Live Innvær Ljones.
Through interviews with employees and leaders, the study uncovered a gap between management's ambitions for AI adoption and employees’ actual experiences. Many employees also expressed uncertainty about leadership’s expectations for AI use. The presentation was held at a breakfast meeting AT DIG last week.
So, what does it take to make AI work in practice? The students identified four key success factors:
- Clear AI strategies to provide structure and build confidence.
- Competence development to give employees the time, tools, and training they need.
- Cross-functional collaboration to break down silos and foster knowledge-sharing.
- Active leadership to guide employees without undermining their autonomy.
-Leadership is essential for driving the AI train forward, says Jensen and Ljones. They highlight how important it is for leaders to balance support with professional freedom, especially for knowledge workers who value intellectual expertise.
This study, conducted in affiliation with Copenhagen Business School, is one of the first to explore how AI affects the professional identity of knowledge workers in Norway.
A Real-Life Example: AI and Computational Problems
A bonus highlight from the seminar: Lars Jaffke, Associate Professor at NHH’s Department of Business and Management Science, delivered an inspiring talk on how algorithmic modeling can solve real-world problems. Using air traffic congestion as an illustration, he demonstrated how data-driven tools can address complex challenges with speed and precision.
AI: The latest step in a long quest
Hear Professors Tor Wallin Andreassen of NHH and Mohamed Zaki from the Cambridge Service Alliance in conversation on what the newest AI-agents are all about. The same quest as the early robots – mimicking humans.