Every major technology shift generates a wave of “leadership for the [technology] era” thought pieces. AI is no exception. My LinkedIn feed is full of articles claiming that AI requires fundamentally new leadership approaches.

I’m sceptical of most of these claims. Leadership has always required vision, communication, decision-making, and developing others. AI doesn’t change those fundamentals.

But some things are different. Let me separate the signal from the noise.

What Hasn’t Changed

Most leadership fundamentals remain constant regardless of technology.

Setting direction still matters. Leaders still need to articulate where the organisation is going and why. AI is a tool that can help get there, but it doesn’t set the destination.

Communication still matters. People still need to understand what’s expected of them and why their work matters. AI can help draft communications, but leaders still need to deliver messages that resonate.

Developing people still matters. Leaders are still responsible for building their team’s capabilities. The specific skills may evolve, but the responsibility remains.

Making difficult decisions still matters. AI can provide analysis and options, but someone still has to make the call on ambiguous, high-stakes choices.

Building relationships still matters. Trust, respect, and connection aren’t automated. They’re built through human interaction over time.

If you were an effective leader before AI, you have the foundation to lead through AI. The core skills transfer.

What’s Genuinely New

That said, AI does introduce some genuine leadership challenges that didn’t exist before.

Leading Through Uncertainty About the Technology Itself

Previous technology changes were more predictable. You could see where computing or the internet were heading with reasonable accuracy. AI development is faster and harder to predict.

This means leaders need to make decisions with less certainty about what capabilities will exist in 2-3 years. That requires:

• Greater comfort with ambiguity
• Ability to make reversible bets rather than all-in commitments
• Willingness to adjust strategy as capabilities evolve
• Transparent communication about what’s known and unknown

Managing Workforce Anxiety at Scale

Employee anxiety about technology isn’t new, but the scale and intensity are different with AI. This isn’t fear of learning a new software system. It’s fear about whether professional skills developed over decades will remain valuable.

Leaders need to:

• Address these concerns directly and honestly
• Invest visibly in workforce development
• Create psychological safety during transition
• Make hard calls about workforce evolution with humanity

This is emotionally demanding leadership that many executives aren’t prepared for.

Understanding What AI Can and Can’t Do

Leaders don’t need to become AI experts, but they need enough understanding to:

• Evaluate vendor claims critically
• Recognise when AI is and isn’t the right solution
• Understand the ethical implications of AI decisions
• Set appropriate expectations for their teams

This requires ongoing learning. The capabilities are evolving too fast for one-time education to suffice.

Balancing Efficiency and Human Value

AI enables significant efficiency gains. But pure efficiency isn’t always the goal. Leaders need to decide:

• When to prioritise speed versus quality
• Which human touchpoints matter enough to preserve
• How to capture efficiency gains without dehumanising work
• Where the organisation’s values constrain optimisation

These are judgment calls without clear right answers.

The Questions Leaders Need to Ask

Rather than prescribing a new leadership model, here are the questions leaders should be asking themselves and their teams:

About strategy:

• How might AI capabilities affect our competitive position?
• What should we be building versus buying?
• Where are the risks of over-investing versus under-investing?
• How do we stay adaptable as the technology evolves?

About people:

• Which capabilities will be more valuable as AI advances?
• How do we develop those capabilities in our workforce?
• Who is most at risk and what do we owe them?
• How do we maintain engagement during uncertainty?

About themselves:

• Where do I need to develop my own understanding?
• What biases might affect my AI-related decisions?
• How do I model the learning mindset I want from my team?
• Am I addressing concerns directly or avoiding them?

Common Leadership Mistakes

I see leaders making predictable errors as they navigate AI adoption.

Delegating AI decisions entirely to technical teams. AI has strategic, ethical, and human implications that require leadership judgment. You can’t outsource this.

Focusing on technology over people. The technology usually works. The implementation fails because of human factors. Invest accordingly.

Chasing hype. The most successful AI adoptions solve real business problems. The failures chase whatever’s generating buzz.

Either-or thinking. “AI or people” is a false choice. The question is how AI and people work together most effectively.

Assuming AI is someone else’s concern. If you lead people whose work AI might affect, AI is your concern. Every leader needs at least baseline fluency.

What to Actually Do

Here’s my practical advice for leaders navigating AI:

Invest in Your Own Understanding

You don’t need to become technical, but you need enough familiarity to ask good questions and evaluate answers. Take a course. Use the tools yourself. Read beyond the hype pieces.

Talk to Your People

Find out what they’re worried about, excited about, and confused about. Listen more than you talk. Use what you learn to shape your approach.

Make AI Capability Development a Priority

Put real resources behind it—time, budget, attention. Signal through your actions that this matters.

Model the Learning Mindset

Let your team see you experimenting with new tools. Share your learning process, including frustrations and failures. Demonstrate that continuous learning is expected of everyone, including leaders.

Make Decisions Deliberately

Some AI decisions can wait. Others need to be made now. Distinguish between them. Don’t rush into major commitments without understanding implications. But don’t wait so long that you fall behind.

Lead with Humanity

Remember that behind every efficiency metric is a person with a family, a mortgage, and career hopes. You can pursue organisational goals and treat people with dignity. In fact, you must.

The Leadership Opportunity

Periods of technological disruption are difficult to lead through. They’re also leadership opportunities.

The leaders who help their teams adapt successfully will build tremendous loyalty and credibility. The leaders who hide from the challenge or pretend it isn’t happening will lose trust.

Your people are looking to you for guidance. Not for certainty you can’t provide, but for honest engagement with the challenges ahead. For investment in their development. For decisions that balance business needs with human concerns.

That’s always been what leadership is about. AI just raises the stakes.

The Bottom Line

Is leadership in the AI age fundamentally different? Mostly not. The core requirements haven’t changed.

But AI does introduce genuine new challenges: greater technological uncertainty, heightened workforce anxiety, the need for new technical fluency, and complex trade-offs between efficiency and humanity.

Meet these challenges with the same fundamentals that have always defined good leadership: clear direction, honest communication, investment in people, good judgment, and the courage to make hard calls.

That’s what leadership has always required. AI doesn’t change that. It just demands more of it.