The following article feature is an original publication from Sean Hogan, a HumanCulture Fellow. The article first appeared in his LinkedIn Newsletter, May 2026.

Leaders are asking "how do we use AI?" But the question that will define your organization is "who are you becoming while you do?"

There is a version of AI adoption happening right now in organizations everywhere that looks like progress on paper. New tools are being deployed. Efficiency metrics are improving. Dashboards are reporting productivity gains.

And underneath all of it, something quieter is happening: people are scared, disoriented, and watching their leaders for signals about whether they are safe.

That's the part the implementation roadmaps don't address.

The question leaders keep asking, and the one they should

The dominant leadership conversation about AI in 2026 is operational: How fast can we deploy? Which workflows do we automate first? How do we measure ROI? These are legitimate questions. They are also insufficient.

The more consequential leadership question is one of identity: Who are you as a leader when the pressure to optimize is relentless, your team is anxious, and the technology is moving faster than your culture can absorb?

Research from organizational psychology has long established that people don't resist change. They resist loss. Loss of competence. Loss of significance. Loss of certainty about their place in the story. AI triggers all three at once.

Nearly seven in ten employees believe AI will lead to layoffs at their company within three years. The psychological impact is already measurable: 24% say AI is negatively affecting their mental health today. Not in some hypothetical future. Today. (Source: Modern Health, May 2026)

Leaders focused solely on implementation speed are missing the crisis unfolding at the human layer.

Two failure modes, and what they have in common

In the organizations I've worked inside and alongside, AI transformation tends to surface two distinct leadership failure modes.

The first is over-automation: the leader who becomes so focused on efficiency that they lose sight of why the organization exists. Culture erodes quietly. Accountability becomes algorithmic. The people in the organization start to feel like variables in an optimization problem rather than people with purpose.

The second is paralysis: the leader who is so risk-averse, or so overwhelmed by the pace of change, that they fail to provide direction. Their teams absorb the ambiguity and fill it with anxiety.

What both failure modes share is a loss of leadership identity. The leader has become reactive to the technology rather than staying anchored in something the technology can't touch.

What grounded leadership actually looks like

The leaders handling AI transformation most effectively right now are not necessarily the most technically fluent. They are the most self-aware.

They have done the internal work of knowing what they value, why they lead, and what they will not compromise. That clarity becomes a stabilizing force for their organizations during disruption.

In practice, this shows up in a few distinct ways.

They name the anxiety directly. Rather than projecting confidence as a performance, they create space for honest conversation about what is uncertain. Psychological safety is not a soft concept. It is the organizational infrastructure that allows teams to adapt rather than contract.

They define what AI is and isn't for. The most dangerous leadership posture right now is ambiguity about values. When people don't know what the leader believes about the role of AI in the organization's mission, they write their own story. And it is usually worse than the truth.

They lead the human architecture, not just the technical one. AI governance is not primarily a technology problem. It is a values and trust problem. It requires leaders to make explicit what would otherwise be assumed: how data is used, who is protected, and what decisions will always remain human.

The work that remains irreducibly human

McKinsey's 2025 State of AI data found that nearly two-thirds of organizations have not yet begun scaling AI across the enterprise. Most are still experimenting. Still in pilots. (Source: McKinsey State of AI, 2025)

Most are watching and waiting. That window, uncomfortable as it is, is actually an invitation.

It is an invitation to decide, before the technology makes the decision for you, what kind of leader you intend to be in the middle of this. What you will protect. Who you will remain.

The technology will accelerate. The implementations will expand. The pressure to optimize will intensify.

Your organization needs you to have already answered the question of who you are before all of that arrives.

That's the leadership work AI cannot do for you.

What's one commitment you've made as a leader that AI adoption won't change? I'd love to hear it in the comments.

Sources

Modern Health workforce survey, reported by Fair Play Talks, May 2026. https://www.fairplaytalks.com/2026/05/08/seven-in-10-workers-fear-ai-layoffs-as-burnout-political-stress-and-workplace-distrust-surge/

McKinsey and Company, The State of AI in 2025: Agents, Innovation, and Transformation, November 2025. https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai