Why the AI Debate Often Misses the Point
Best-selling author Dan Goleman argues that important technical questions should take a back seat to some very human quandaries.
Daniel Goleman is author of the international best-seller Emotional Intelligence and Optimal: How to Sustain Personal and Organizational Excellence Every Day. He is a regular contributor to Korn Ferry.
In recent months, the conversation about artificial intelligence has centered on urgent questions of policy, ownership, and ethics. Should powerful AI models be open or closed? How much regulation is enough? Who should have access to world-changing technologies?
While these are important questions, they may not be the most important ones.
Beneath the debate over AI governance lies a series of assumptions about what humans are—and are not—capable of. As AI grows more capable, leaders are finding themselves making decisions for which there are not objectively "right" answers. Every path forward involves competing values, uncertain consequences, and tradeoffs that cannot be easily predicted. AI is stretching leaders to sit in more discomfort—not just their own, but the unnamed discomfort of everyone they lead.
For decades, leaders have been tasked with reducing uncertainty. The goal has been to gather more information, get better at analyzing data, and choose a course of action based on a thoughtful balancing of risk and reward. The underlying assumption has always been that with enough intelligence and enough information; decisions would be naturally better.
In many ways, AI supports that model. It can synthesize vast amounts of information, instantly recognize less obvious patterns, and generate options at extraordinary speed.
Yet many of the decisions leaders face today are becoming less—not more—suited to this approach.
Should an organization move quickly to adopt AI, knowing it may disrupt jobs? Should it slow adoption to protect employees, even if competitors gain an advantage? Should powerful models be made widely available to accelerate innovation, or restricted to reduce the risk of misuse? Should AI be seen as the road to a utopia of purposeful work for all? Or the demise of human beings and the beginning of a new dark age?
These are not technical questions waiting for technical answers. Each requires human judgment informed by values and ever-evolving human needs.
The distinction matters because AI is not just changing what leaders do – it is changing the conditions under which leadership happens. Many of the assumptions that guided decision-making for decades don’t continue to hold in the same way. Meanwhile, new norms and capabilities have yet to fully emerge. This is the equivalent of standing between two worlds: one whose rules and operating assumptions are fading and another whose guidelines and norms are still taking shape.
For human beings wired to seek certainty, resolve ambiguity, and regain a sense of control, the in-between can be profoundly uncomfortable. Yet leadership doesn’t cease to be needed. Navigating the middle terrain of change—the phases of change that can feel totally disorganized and overwhelming—takes a set of competencies that many leadership models still treat as secondary.
More and more, emotional intelligence is one of leadership's most indispensable skill sets. When many people think about emotional intelligence, they think about empathy or communication or calmness. While that's true, emotional intelligence also shapes something even more fundamental: our ability to make sound judgments when there is no clear map.
This is precisely what Korn Ferry's recent research on AI readiness suggests. The research identified six common warning signs that leaders are unprepared for AI, arguing that the greatest barriers to AI readiness are rarely technical. They are leadership challenges: helping people navigate ambiguity, redesigning work, fostering experimentation, and leading through profound change. In other words, AI readiness depends as much on developing human capabilities as it does on adopting new technologies.
Take managing ambiguity as one example. In many circles, managing ambiguity is often misunderstood as simply tolerating uncertainty with a calm demeanor and, in best cases, a hopeful outlook. But increasingly, it means helping others navigate uncertainty without rushing to fix, solve or offer false promises to relieve tension. It requires leaders to regulate their own emotional responses, remain curious in the face of competing viewpoints, and create enough psychological safety for thoughtful disagreement to emerge.
To do this, leaders need self-awareness to recognize when fear, excitement, or overconfidence are impacting their thinking. They need empathy to understand why people arrive at different conclusions about the same issue. They need organizational awareness to consider the ripple effects of any decision across employees, customers, communities, and society. They need adaptability to revise assumptions at the pace at which technology is evolving.
The debate over open versus closed AI illustrates this well. Both perspectives are motivated by legitimate concerns. Whereas advocates of open models argue that transparency fuels innovation, scientific discovery, and accountability, those calling for greater restrictions worry that increasingly capable systems could amplify cyberattacks, misinformation, or other forms of harm.
Notice what is happening beneath the surface.
Neither side is arguing primarily about technology; they are wrestling with trust.
Can we trust individuals with increasingly powerful tools? Can we trust organizations to deploy them responsibly? Can we trust governments to regulate wisely? Can we trust markets to balance innovation with the public good?
These are not engineering questions; they are big and profound human ones.
One practical way to bring emotional intelligence into AI decision-making is to resist the urge to solve before fully understanding the tension you're trying to navigate. Before asking, What's the right answer?, ask instead: What do we know? What assumptions are we making? What values are in tension? And what hopes or fears might be shaping our thinking?
The goal isn't to eliminate uncertainty. It's to help people move through it with greater clarity, wisdom, and trust. Perhaps that's the real leadership challenge AI presents: not mastering a technology, but developing the capacity to remain present with uncertainty long enough for wiser decisions to emerge – not only for us, but for everyone looking to us for direction.
The conversation about AI often focuses on what the technology is becoming. The more enduring question is what it is asking us to become.
Co-written by Elizabeth Solomon
Click here to learn more about Daniel Goleman's Building Blocks of Emotional Intelligence.
