Augmented leadership: The new executive profile for the AI era

As AI accelerates, its influence on leadership development is undeniable. Augmented leadership has emerged as a strategic capability—a management profile that moves beyond the limits of traditional leadership and develops skills attuned to today’s paradigm shift. 

Although some still view AI as a threat, this new capability is more than just another tool. It’s a competitive lever that will separate the relevant from the irrelevant. 

In an article for Harvard Deusto Business Review, David López López, Associate Dean of the Full-Time MBA at Esade, and Patricia Rodríguez García, an academic collaborator in the program, propose a framework for understanding and developing this new profile. It combines algorithmic potential with executive know-how to set a new leadership standard. 

AI: from technical tool to structural force

AI has moved far beyond its origins as a process-automation technology. It has become a structural condition of modern leadership, reshaping everything from strategy and finance to talent management and organizational culture. 

This shift disrupts a long-standing model in which the executive was expected to have all the answers. AI encourages more horizontal, collaborative, and multidisciplinary ways of working—approaches open to experimentation, probabilistic scenarios, and rapid iteration. This stands in sharp contrast to traditional, hierarchical, control-oriented leadership and demands a new mindset: moving from heroic leadership to facilitative leadership. 

Importantly, implementing AI does not mean outsourcing decisions to algorithms or blindly accepting their outputs. The challenge lies in understanding how algorithms work, applying strong governance, and integrating them critically and strategically and in line with the organization’s strategic goals. 

The four core competencies of augmented leadership

The new profile is not a technologist in the classic sense, but a leader who combines instinct, knowledge, and experience with the power of data. This means leaving behind the comfort offered by ‘business intuition’—a gut feeling built over years of experience—to contrast and enrich it with algorithmic evidence. 

This is a cultural and personal leap. Augmented leaders are measured not only by vision and execution but by how well they use AI as a value lever. López and Rodríguez identify four essential competencies: 

1. Algorithmic literacy

Stanford University’s AI Index 2024 reports that only 23% of executives clearly understand how AI systems operate in their companies. This knowledge gap is risky. Augmented leaders must grasp the fundamentals of machine learning, data bias, and model limitations in order to ask critical questions and make responsible decisions. They don’t need to become engineers—but they do need to develop a shared language with technical teams.

2. Strategic application

Deloitte has found that only 28% of AI initiatives deliver real business impact. Augmented leaders know where AI can create competitive advantage: predicting employee turnover, personalizing campaigns, or redesigning operational and logistics processes based on patterns such as weather trends. This isn’t about digitizing existing workflows; it’s about reimagining the business model with algorithmic support.

3. Ethical leadership and governance

AI is not neutral—it reflects the biases in its training data. Amazon’s now-abandoned recruiting algorithm, which discriminated against women, is a cautionary example. Ethical leadership means taking responsibility for the processes and their impacts. Augmented leaders must prioritize transparency, accountability, and fairness. As López and Rodríguez put it, applying AI “is not about automating for automation’s sake, but about asking which human capabilities the algorithm expands, which decisions it improves, and which biases it may introduce.”

4. Change management and organizational culture

The biggest obstacle to AI adoption is cultural, not technical. Many organizations still view AI with fear or distrust rather than as a catalyst for talent. Leaders must change that perception, encourage experimentation, and democratize learning. Companies such as Nestlé (with its ‘AI for All’ program) and Repsol (with its open innovation lab) show how training employees in AI fundamentals can boost innovation and engagement. Ultimately, the augmented leader is a change agent who connects technology with human development.

Becoming an augmented leader

Developing into an augmented leader isn’t about stacking up technical credentials—it’s about embracing a mindset of openness and adaptability. Executives can start with a few practical steps: 

• Talk with the data or innovation team to understand which decisions are already supported by algorithms.
• Design a personal plan for algorithmic literacy, with short, specific, and practical courses.
• Identify a strategic AI use case at the executive committee level.
• Promote the ethical evaluation of algorithms in use within the organization.
• Discuss AI openly in corporate culture, dispelling fears and promoting its use, learning, and trial-and-error. 

These are small, incremental actions that don’t require engineering expertise—just curiosity, sound judgment, and a willingness to change. 

By strengthening the partnership between human talent and algorithms, leaders and organizations have the chance to redefine themselves and remain competitive—now and in the future. Ignoring this shift carries the risk of being left behind.