A Human-Centred Perspective on AI Adoption in Industrial Settings : Exploring Organizational, Emotional, and Relational Factors

Sammanfattning

This thesis investigates how industrial organizations can adopt artificial intelligence (AI) through a human-centred lens that emphasizes trust, adaptability, and employee engagement. Drawing on a real-world AI change initiative within a global industrial manufacturing organization, the study examines how employees’ perceptions of trust, organizational support, learning conditions, and acceptance shape the adoption of AI in engineering work. The study adopts a quantitative descriptive survey design based on a structured online questionnaire completed by 40 engineering professionals. The analysis uses descriptive statistics, including frequencies, percentages, and Net Promoter Score indicators, to identify patterns in employees’ perceptions of AI adoption. The results show a clear adoption gap: although 88% of respondents expected their AI use to increase over the next three years, trust in AIrecommendations was negative (NPS = −68), confidence in daily AI use was also negative (NPS = −47), and only 8% reported formal training. The main contribution of the thesis is to show that AI adoption in industrial organizations depends not only on technical availability, but also on organizational and human-centred conditions that support trust, engagement, and acceptance. By combining the Prosci ADKAR framework with Knapp’s Relationship Model, the thesis interprets AI adoption as both an organizational change process and a gradual trust-building process. The findings highlight the importance of transparent communication, explainability, role-specific training, and organizational support for realizing the practical and economic value of AI in industrial engineering work.