The growing pressure inside the AI boom is raising questions about how leadership must evolve, a shift highlighting the need for emotional intelligence in high-stakes decision-making.
Intelligence alone does not help leaders adapt unless it is paired with emotional understanding, Microsoft (NASDAQ:MSFT) CEO Satya Nadella said on the "MD Meets" podcast, hosted by Axel Springer CEO Mathias Döpfner.
"I mean, intelligence quotient has a place, but it's not the only thing that is needed in the world," Nadella said. "And I've always felt at least as leaders, if you just have IQ without emotional intelligence, it's just a waste of IQ."
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Why EQ Matters To Nadella
He added that collaboration strengthens when people interact directly. Nadella called the workplace "the best collaboration tool," saying humans learn from one another through cues remote setups often miss. He viewed those abilities as especially important when product, science, and infrastructure teams work together.
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How AI Is Changing Leadership
Nadella told Döpfner leaders must remain curious and willing to relearn as AI reshapes how companies operate. He described Microsoft's culture as focused on being "learn-it-alls," not "know-it-alls," and said staying relevant often requires unlearning habits that once worked.
Nadella added that he studies how smaller companies build products because their tight coordination across product, science, and infrastructure allows them to move faster than a large organization.
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He said this approach helps companies maintain control by developing systems grounded in their data rather than relying entirely on outside models.
EQ's Role In The AI Workplace
Nadella said AI will take on more tasks but will still rely on people to guide progress. He described a workflow in which autonomous agents complete assignments and then return when they encounter limits or need direction. Nadella told Döpfner, these agents will report what they finished, where they stalled, and what requires human input, creating a new type of inbox for reviewing updates and determining next steps.
He added that this pattern keeps people involved because the agents return whenever they reach limits or need further direction.
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