In 2025, I have noticed a notable increase in job postings focused on hiring AI leaders, including roles such as Head of AI, on LinkedIn.

In fact, in many interactions in the "real world" and on LinkedIn, I’ve been in touch with many recruiters and managers who have shared their views on how their leaders are hiring newly created "Head of AI" or "AI Leader" positions. In many cases, the silence that follows when I share my perspective on the topic is louder than the statement itself.

You see it in the glances—some imagine a technical lead with a PhD and GitHub full of neural networks. Others want a business-savvy strategist who communicates effectively with the board. And then there’s the camp that just wants “someone who knows how to use ChatGPT safely.” - Good luck, because that’s the problem...

Even at companies as mature as they appear, people still speak different dialects when discussing AI leadership. It’s probably slowing them down, not because they lack the ambition, but because they haven’t clarified the role AI should play in their organization’s growth.

What I see behind the scenes

In my experience working across various sectors, I’ve engaged with product managers, lawyers, compliance teams, and frontline sales staff, each bringing a unique perspective and set of expectations regarding AI integration. Understanding these diverse viewpoints is crucial, as it highlights the multifaceted nature of AI's impact on different roles within an organization, for example (not exhaustive) :

- Sales wants AI that can analyze customer behavior and preferences, improving engagement and increasing conversions.

- Legal seeks AI as a protective measure, helping to identify compliance issues and mitigate risks associated with regulatory scrutiny.

- Aftermarket desires faster, automated responses to customer inquiries, reducing the volume of support tickets and enhancing customer satisfaction.

- Leadership aims for a strategic AI vision that drives innovation while ensuring minimal disruption to existing workflows and processes.

This isn’t dysfunction. It’s reality, and what we’re facing is not a skill gap. It’s a definition gap.

I believe we’re treating "AI leadership" like a role when it’s actually a capability—one that needs to be spread, shaped, and sustained across different layers of the business.

What I’ve learned (and keep learning)

In a world that is changing by the hour (DeepSeek effects, trade wars, geopolitical uncertainties, and what's next...), effective leadership is paramount, and for business leaders who are navigating the complexities of AI implementation, it's crucial to assess the readiness of individuals stepping into leadership roles.

As someone who went through this in first person, I try to help during my conversations by sharing my framework that outlines key characteristics that define strong AI leaders, whether they are new hires or emerging talent from within the organization:

1. Influence matters more than algorithms. If a person can’t drive alignment between IT, business, and compliance—they’re not leading AI, they’re babysitting it.

2. The best AI leaders simplify with precision. They don’t talk down. They translate complexity into meaningful trade-offs. They know that the hardest part of AI isn’t the tech—it’s the organizational trust to use it.

3. Strategic patience is a superpower. Many AI use cases fail not because the idea was wrong, but because the timing was. AI leaders know how to read the tempo of change—and wait until the conditions are right to act boldly.

4. They make learning visible. Whether it’s prompt engineering, regulatory impact, or model drift—AI leaders show their process. Not just outcomes. That builds credibility.

Where this hits home

In your company, you should be moving deliberately. Not slow. Deliberately.

That means you're not just chasing the latest shiny demo—you should be building use cases that make sense for how you work, sell, and serve. Sometimes that looks unexciting from the outside. But inside? It’s a shift in how you think about responsibility, value, and human-machine collaboration.

In my view, the best AI leaders aren’t visionaries sitting in a corner (we need those, too, but let's discuss them in another article). They’re connectors. They listen more than they speak. And they know their real job isn’t to "do AI"—it’s to help the organization grow into AI.

So… what does your version of AI leadership look like? Is it a single role? A distributed responsibility or a more comprehensive cultural trait?

Would love to hear how others are approaching this, especially across industries. Maybe between all our definitions, we’ll finally get one that works.