AI adoption is planned as a technical project in most companies. Tools are selected, licenses purchased, rollout plans written. What is systematically underestimated: The decisive bottleneck lies not in the technology, but in three fundamental psychological needs of the people who are supposed to work with it.
A thesis at FOM, which I recently supervised, empirically tested what I have observed for years in workshops and consulting mandates: The acceptance of AI depends less on the tool than on whether employees feel competent, autonomous, and socially integrated.
The Key Insight: Three Needs Determine Acceptance
Deci and Ryan’s Self-Determination Theory describes three fundamental psychological needs that drive intrinsic motivation: autonomy, competence, and relatedness. If these are met, engagement arises. If they are violated, resistance arises.
The empirical study with 78 respondents shows: All three needs have a significantly positive effect on the perception of AI as an opportunity. The strongest lever is competence. The model with competence as a predictor explains about 43 percent of the variance in the perception of AI as an opportunity, and thus the highest proportion of the three needs examined.
With 78 predominantly younger participants recruited through personal and professional networks, the sample is not representative; the effects indicate a direction, not a magnitude transferable to the general population.
These findings are not an isolated observation. A global KPMG study with over 48,000 participants in 47 countries confirms the pattern: Only 39 percent have ever received formal AI training. Almost half rate their own knowledge as limited. The competence gap is measurable.
3 Levers for Your Employees’ AI Acceptance
Those who take AI transformation seriously as a leadership task plan along these three levers:
- Systematically build a sense of competence. A McKinsey study shows that about 20 percent of employees receive little support in building competence. Practical training with real success experiences is not a mere formality, but a prerequisite for acceptance.
- Do not stifle autonomy with regulations. If AI tools are mandated from above, without room for choice or participation, the sense of autonomy decreases. Well-thought-out AI governance allows employees to decide for themselves, within defined corridors, when and how they use AI. This is not a weakness of control, but control that works. If this leeway is missing, it is likely that employees will resort to their own, unapproved tools – the entry into Shadow AI.
- Actively maintain social spaces. 36 percent of respondents in the Workday Report 2025 fear that AI will reduce meaningful human interactions. This concern is not irrational. Those who design AI transformation without actively fostering social bonds risk reserved employees.
Conclusion: AI Transformation is a Leadership Task
AI transformation is not an IT task supported by HR development. It is a leadership task that uses IT as a tool. Those who take their employees’ fundamental psychological needs seriously create the conditions for AI to be adopted within the organization.
This insight costs no tool budget. It costs attention from leadership.
Scientific background
This article draws on findings from the following work:
Gegaj, A. (2026): Perception and Evaluation of Artificial Intelligence – The Influence of Leadership and Motivation. Thesis, FOM University. Empirical online survey with 78 participants, October 2025.
Study Sources: KPMG/University of Melbourne (Gillespie et al. 2025), McKinsey (Meyer et al. 2025), Workday (2025).
