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AI and the future of leadership: Rethinking talent, work and governance

By Fu Xiaoya | chinadaily.com.cn | Updated: 2026-04-15 19:20
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Q2 You have long challenged the notion that confidence equates to leadership. As AI enables more objective judgment and even replaces certain decision-making functions, do overconfident leaders face greater risks? At the same time, which leadership traits remain indispensable, and which capabilities are being weakened?

I have long argued that confidence is a poor proxy for competence. In the age of AI, this becomes even more problematic. When machines can generate plausible answers instantly, the marginal value of confidence declines, and the cost of misplaced confidence rises. Overconfident leaders are more likely to accept AI outputs uncritically, mistaking fluency for accuracy. Overconfidence also leads to people feeling "artificial certainty" or thinking that they know just because they read the outputs of AI without having the deep expertise to vet it, edit it, or question it.

To be sure, what remains indispensable are qualities that AI cannot replicate easily: judgment, curiosity, learning agility, and the ability to influence others. Leadership becomes less about knowing and more about thinking, especially when the world feels it is no longer important to think, because we can outsource or delegate thinking to machines! This elevates what I would call "cognitive leadership": the ability to structure ambiguity, prioritize effectively, and make trade-offs. It also reinforces the importance of social and ethical judgment, which remains stubbornly human.

Emotional intelligence also matters, not as authenticity, but as the ability to manage impressions and mobilize others effectively. The more emotionally intelligent you are, the more authentic you will seem to otherseven when you fake it.

Meanwhile, traditional signals of expertise are being eroded. Domain knowledge, technical skills, and even strategic analysis are increasingly augmented or commoditized by AI. The premium shifts to meta-skills: asking the right questions, validating outputs, and persuading others to act on them.

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