AI makes performance differences visible in new ways. The question is not who runs fastest but how leadership handles the fact that not everyone does.
As AI becomes a powerful support in daily work, performance gaps quickly widen. A person who masters the tools may suddenly deliver at a level others perceive as unrealistic. This dynamic is not new,but its speed and visibility are.
If leadership fails to address this actively, the risk of stress, comparison culture, and feelings of inadequacy increases. Over time, this can lead to quiet resistance, cynicism, or disengagement, Carl Heath says.
– Fair leadership in this context does not mean slowing down those who are ahead. It means investing in those who need more time. Above all, it means making AI learning an organizational responsibility rather than an individual side project.
Be explicit about what is valued
When AI competence is something you are expected to “figure out on your own,” inequality grows. When learning is built collectively within teams, with time allocated during work hours, it becomes part of the organization’s shared capability.
– Leaders must also be explicit about what is truly valued. If high output is rewarded regardless of how it is achieved, unhealthy performance norms emerge. When learning, sharing, and quality are valued just as highly, a different dynamic takes shape.
AI does not change the need for fair leadership. It simply makes the absence of it more costly.
Three questions for the executive team:
- How do we ensure AI capability is built collectively, not individually?
- What are we rewarding today—output only, or also learning and collaboration?
- How do we identify and support those falling behind early in an AIaugmented workplace?
Carl Heath is a senior researcher at RISE and a doctoral researcher at the University of Gothenburg, focusing on leadership, AI and digital resilience. His work explores how organisations can navigate technological change while strengthening human judgement, trust and agency. He approaches AI not as a technical issue, but as a leadership and organisational challenge rooted in learning and everyday practice.