AI has already arrived in business, but leaders are still stuck in the 20th century.
We are experiencing a paradoxical moment in organizations. On the one hand, the media bombardment about the “imperative need” to adopt Artificial Intelligence has generated systemic anxiety. On the other hand, there is a real leadership vacuum regarding how to integrate this technology without disrupting the organizational culture in the process.
We've spent too much time discussing what tools to buy and too little time talking about who we need to be to lead this change.
In this regard, it is important to focus on three key points for this process:
1. Break free from the loop of “empty urgency”
The market is pushing us into a race where the prize seems to be speed, not purpose. But the adoption of AI isn't a software update that gets installed on a Friday afternoon; it's a redefinition of how human talent adds value.
When leaders only talk about the "obligation to innovate," without outlining a clear roadmap, all we generate in our teams is resistance and fear. True innovation doesn't stem from the fear of becoming obsolete, but from a strategic vision of becoming better.
2. AI is not delegated, it is led
There is a latent risk in organizations: "bystander leadership." This is when partners, directors, or managers approve AI budgets but continue to manage their processes using 20th-century logic. AI is perhaps the first technology that cannot simply be "deferred" to the IT department. If a leader doesn't understand the tool's capabilities, biases, and ethical dilemmas, they lose the authority to ask their team to adopt it. We cannot demand agility from an organization if, as leaders, we are not the first to experiment with the uncertainty that AI brings.
3. Example as the only antidote to fear
Today's leader's responsibility is not to be an expert in algorithms, but to be an example of adaptability . This means embracing technical vulnerability, recognizing that we don't have all the answers, and learning alongside our teams, while maintaining ethical transparency that clarifies which processes will be automated and which human capabilities—such as creativity, empathy, and critical thinking—will be more valued than ever.
Above all, it requires active use : there is no discourse that is more convincing than seeing a leader optimizing their own agenda, analyzing data, or refining strategies through AI in an ethical and conscious manner. The adoption of AI will only be successful if we make technology work for people, and not the other way around. But that balance won't come from a user manual, but from leaders who take responsibility for bridging the gap between the old paradigm and the future we are already living in.
However, to lead by example and be the driving force behind this transition, the leader's training should not be technical, but strategic and operational.
Based on this premise, it is essential to address four key aspects: first, developing critical AI literacy to understand the different types of AI, their characteristics, and uses. Second, creating a “leadership sandbox” by dedicating a few minutes each day to AI tools that support daily responsibilities.
Third, it is necessary to promote business ethics committees, forming working groups to discuss information governance, biases, risks, and security. Finally, reverse mentoring should be encouraged , where the pyramid is inverted and leaders rely on those team members most involved with the tools to mentor them.
But, fundamentally, it is necessary that, as leaders, we remember: less pressure for speed and more commitment to direction.
