Artificial intelligence is transforming decisions that were once the privileged domain of executives. It sees patterns where we only notice fragments. It reframes complexity into computation and simulates futures faster than a leadership retreat can align a calendar. AI accelerates everything except wisdom.

The most profound shift identified in recent research is not technological. It is human. AI forces leaders to confront a devaluation of what once defined their role: exclusive access to information, years of experience turned into instinct, and the ability to choose without hesitation. When machines learn faster than people can, leadership can no longer be grounded in being the smartest person in the room.

A qualitative study of 23 senior executives across Europe reveals four strategic leadership capabilities required in AI-intensive environments. These capabilities are not simply new competencies to add to a development plan. They reshape how power, judgment, and accountability are distributed. They operate across personal belief systems, organisational practices, and relational ecosystems of partners, customers, and communities. And they gain strength not just through top-down direction, but through bottom-up initiative and learning at the edges of the organisation. (AI-LEADER-RESEARCH.pdf)

What this research ultimately shows is that AI does not replace leaders. It redefines the work of leadership. It asks leaders to choose what is worth preserving when everything can be automated.

Each capability calls leaders into a deeper inquiry: What is leadership when intelligence is no longer scarce? And perhaps more importantly: Who are we, as leaders, when our certainty is no longer the point?

1. AI open mindset

Leadership begins as a willingness to be changed. The first requirement of leadership in an AI world is not technical. It is existential. Leaders are being asked to set aside the comfort of knowing and embrace the discomfort of becoming. AI disrupts the long-held belief that experience automatically leads to better judgment. It replaces prestige with questions. In this environment, expertise can become brittle if it is not supported by ongoing curiosity.

The study shows that AI transformation starts not in the IT roadmap but in the internal stance of executives. It begins when leaders choose to learn publicly rather than delegate privately. Leaders who personally experiment with AI signal to others that courage, not certainty, earns influence. They demonstrate that vulnerability is not a liability. It is a strategy for cultural evolution.

Although senior participation gives technology legitimacy, the research reveals that many breakthroughs arise from the middle of the organisation. These are the people who notice where processes get stuck and imagine a better way. The most impactful AI initiatives in several companies originated from middle managers or operational teams who took initiative without waiting for permission. Top leaders must create the conditions for such ideas to surface, be tested, and move into the mainstream.

External shocks can accelerate this mindset. The COVID-19 pandemic and competitive pressure pushed companies to rethink how work gets done and to see AI as essential rather than optional. The organisations that moved quickest were led by executives who viewed disruption as an invitation to change, not a reminder to defend the status quo.

This mindset is not really about technology adoption. It is about releasing defensiveness. It is about replacing the question “Do I understand enough?” with “Am I willing to learn what I do not yet understand?”

It is the move from expertise to curiosity. From protecting status to enabling possibility. From being the answer to becoming the learner-in-chief.

Practical shift for leaders: Make curiosity visible. Engage with AI in ways others can observe. Share what you are learning and what still confuses you. When leaders learn out loud, they turn uncertainty into permission for growth across the organisation.

2. AI strategic co-thinker

Partnering with intelligence that is not our own Artificial intelligence is no longer just a tool that executes commands. It is becoming a collaborator in strategic thinking. Executives interviewed in the study describe using AI systems to explore options, simulate long-term consequences, and surface patterns hidden by human intuition. They are developing decisions with AI, not only after AI.

This collaboration shifts how leaders think about their own role. When predictive models can outline the risks, costs, and ripple effects of multiple futures in minutes, leaders must reconsider what value they bring to the table. It is not speed. It is not data mastery. What remains uniquely human is judgment that accounts for meaning and context and relationships that cannot be quantified.

However, the leaders in the research are clear that AI must not be treated as a source of truth. They emphasise the importance of formulating the right strategic questions so the system is solving the real problem rather than the most obvious one. They highlight the need to filter and refine outputs, questioning what might be flawed or incomplete. Outputs must be interpreted through the lens of lived experience, stakeholder impact, and organisational purpose.

This is a new discipline of leadership. It calls for humility to recognise where AI sees more clearly. It also demands courage to intervene where the machine is blind. Strategy becomes a shared act of intelligence, where neither human nor machine is sufficient alone.

AI can illuminate what is possible. Only leadership can decide what is right. And once the decision is made, only leadership can take responsibility for the outcome.

Practical shift for leaders: Treat AI as a thinking partner rather than a decision substitute. Invite it into early strategic conversations. Then apply critical interpretation before action so that human values remain the anchor for organisational choices.

3. Multi-level connector

Leadership as the design of a learning community, AI does not simply change the tools of work. It changes who participates in shaping the future. The research highlights a profound shift in the role of middle managers. They are no longer expected to merely implement decisions from above. They are becoming connective leaders who translate strategy into experimentation and insight into action.

Middle managers are closest to what customers feel, what systems struggle to process, and where delays hide inside processes. The organisations in the study are investing in these roles and giving them the autonomy and skills to prototype AI solutions and to learn from small risks before they become large ones. New hybrid positions have emerged to bridge leadership and technology, including AI product managers, data translators, and specialists who ensure ethical integrity in design and deployment.

This connective function also extends outside organisational walls. Leaders are cultivating partnerships with universities, suppliers, and technology providers in order to access new knowledge and accelerate innovation. AI is becoming a shared language that allows different actors to build solutions together more fluidly than in traditional transactional relationships.

What these changes reveal is a different logic of leadership. It is no longer defined by how many decisions a leader controls, but by how many people are able to contribute. Authority distributes. Ownership deepens. Innovation becomes a community activity.

AI exposes the limits of solitary expertise. It rewards those who invite participation. It asks leaders to consider whether success is better measured by how effectively they connect talent and insight across boundaries than by how well they personally direct outcomes.

Practical shift for leaders: Focus less on being the point of origin for strategic ideas and more on building the pathways through which ideas can travel. Equip and trust the middle of the organisation. Create partnerships that allow learning to move freely in and out of the enterprise.

4. Ethics risk management

The work of leadership is to protect what must not be lost. Artificial intelligence does not only automate tasks. It also automates judgment. In doing so, it introduces a new category of risk that is both powerful and subtle. Leaders interviewed in the study recognise that biased data, opaque algorithms, and overconfidence in automated decisions can create harm before anyone realises it is happening.

Trust, once broken by an unethical decision, does not recover easily. The executives emphasise the need for visible ethical governance. Many organisations have established cross-functional committees that review AI use cases and update ethical guidelines regularly to keep pace with rapidly evolving risks. These committees bring together technical expertise, legal perspectives, and business judgment so that decisions reflect more than efficiency.

Transparency also becomes essential. Employees and customers need confidence that AI is being used responsibly and that data about them is treated with dignity. Leaders must ensure that decisions influenced by AI can be explained and defended and that someone remains accountable for outcomes. Technology may support fairness, but ethical responsibility cannot be delegated to a model.

AI is capable of optimising performance. Leadership ensures that performance does not come at the expense of people. Where the system sees patterns, leaders must see consequences. Where AI excels at predicting behaviour, leaders must stay committed to protecting rights.

Stewardship is not a soft virtue. It is a strategic capability that protects legitimacy and reputation in a world where trust is fragile and transparency is demanded.

Practical shift for leaders: Treat ethics as a continuous practice rather than a compliance milestone. Include a human review of AI influenced decisions where stakes are high. Make fairness and accountability non-negotiable conditions for every deployment.

Wrap up

AI makes leadership more human, not less. The leaders in this research recognise that AI will increasingly influence the choices that shape organisational futures. They also recognise that intelligence in a system does not guarantee wisdom. The study’s framework illustrates that the required strategic capabilities are interdependent. A mindset open to learning strengthens the ability to co-think with AI. Strong relationships enable ethical governance to reach every layer of the organisation. When these forces reinforce one another, AI becomes a catalyst for shared progress rather than a source of disruption.

Ultimately, AI challenges the idea that leadership is defined by the possession of answers. Knowledge is no longer a scarce resource. What remains scarce, and therefore precious, is the courage to learn in public, the discipline to apply judgment, and the integrity to protect what matters most to the people who place their trust in us.

This moment calls leaders back to the essence of their role. Leadership must concern itself with how technology shapes relationships, how it distributes power, and how it influences what people believe is possible for themselves and others. AI can produce outcomes with extraordinary speed, but only leadership can ensure that those outcomes contribute to a future that is fair, meaningful, and grounded in shared humanity.

The work is not to compete with AI. The work is to become the kind of leader who uses AI to elevate human contribution. Intelligence will continue to rise. Leadership must rise with it, not through greater certainty, but through greater care. That is where trust is earned. That is where organisations grow. And that is where the real future of work is being built.

Reflection questions for leaders

  1. When was the last time you allowed others to see you learn something new that challenged your expertise, and what did that experience signal to the organisation about what is valued here?

  2. In your current AI decisions, how often do you rely on the convenience of automated answers rather than engaging more deeply with the questions that determine what is right for people and the business?

  3. Who is invited into shaping how AI is used in your organisation, and who might still be on the outside waiting for permission to contribute their insight or concern?

AI Fluency is one of the one hundred leadership capabilities in the Leadership Library.

Do you have any tips or advice for leading in harmony with AI?

What has worked for you?

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Thanks for reading!

Reference: Bevilacqua, S., Ferraris, A., Matzler, K. and Kuděj, M. (2026..odd I know) ‘Strategic leadership at high altitude: Investigating how AI affects the required skills of top managers’, Journal of Business Research, 205, 115878.