AI Literacy as a Condition of Leadership
Why AI Adoption Fails Without Executive Vision and Technological Literacy
The Upper Echelons Theory, formulated by Donald C. Hambrick and Phyllis Mason in 1984, holds that the cognitive characteristics, values, experiences, and educational background of senior executives directly influence an organization’s strategic decisions and, by extension, its performance. In other words, organizations reflect their leaders.
Applied to artificial intelligence, this perspective demonstrates that the culture and knowledge of leaders—rather than the technology itself—are the decisive factors determining success or failure in AI adoption. The cultural legitimacy of leadership in the age of AI resides precisely in the ability to transform oneself first, and then to guide others through the same process of reformulation.
A recent report highlights that many executives lack the minimum level of AI literacy necessary to identify relevant opportunities or assess risks. This deficiency leads to poorly grounded decisions and, in the worst cases, to the absence of strategic vision. No tool can compensate for a leadership team that fails to grasp the scope of what it is implementing. Advances in artificial intelligence have revealed a critical weakness across many organizations: the insufficient preparation of their leaders to understand the reach of these technologies and to guide their application with strategic perspective. Research consistently shows that a significant proportion of failed AI projects can be attributed to top management’s inability to interpret what AI integration entails—culturally and organizationally.
A 2024 study by Technische Universität Darmstadt, building on the Upper Echelons Theory, concludes that AI literacy within top management teams (TMT AI literacy) is directly correlated with a company’s ability to transform AI’s potential into concrete and strategically aligned results. The researchers identify two key capabilities: the ability to recognize opportunities that AI creates for the business model, and the ability to translate those opportunities into practices coherent with corporate strategy. Where this literacy is absent, initiatives tend to fragment into isolated pilots or remain confined to technical departments, without generating real organizational impact.
The MIT Sloan Management Review adds another perspective: many executives remain uncomfortable with AI because they have not embraced continuous learning as an essential part of their role. AI literacy does not require leaders to become data scientists or engineers, but rather to cultivate the disposition to understand the processes, risks, and opportunities emerging from the interaction between people and technology. Without such openness to learning, strategic decisions are taken without the full picture, limiting foresight and reducing resilience.
Fast Company (2024) underscores a recurring error: framing AI purely as a technological issue under the domain of IT or a Chief AI Officer. This externalization reflects a leadership gap, since artificial intelligence—like electricity or computing in earlier eras—operates as a transversal force that reshapes workplace culture and redefines authority within organizations.
AI Literacy as a Strategic Risk
Industry analyses reinforce this conclusion. Gartner estimates that up to 85% of AI projects fail to scale, primarily due to the absence of executive leadership capable of sustaining cultural transformation. McKinsey and PwC have identified the AI literacy gap at the executive level as one of the greatest strategic risks facing companies today. And a 2025 Axios report shows that investors increasingly evaluate executives’ AI proficiency as a signal of trust and governance.
Impact on Non-Digital-Native Sectors
The consequences are particularly evident in industries that were not born digital but now rely heavily on AI in their operations:
Renewable energy: Predictive maintenance of turbines or optimization of power purchase agreements requires leaders who understand how algorithms reshape risk management and stakeholder relations. Without that understanding, initiatives remain confined to technical peripheries and fail to integrate into corporate strategy.
Healthcare: Hospitals and insurers are investing in AI for diagnostics and predictive analytics. Without AI-literate leadership, these tools face resistance from professionals and regulatory uncertainty, delaying their impact on patient care.
Banking: Credit risk and compliance processes are increasingly automated, but a lack of executive vision often leads algorithms to be perceived as opaque “black boxes,” eroding trust among employees and clients.
Across these sectors, the constant is not the absence of technology but the insufficient preparation of leadership to articulate the cultural transition that AI demands.
An Urgent Proposal
The evidence points to a clear conclusion: AI literacy must become an essential component of leadership education. Business schools and executive training programs can no longer restrict themselves to traditional disciplines. They need to integrate curricula that prepare future leaders to understand artificial intelligence in its technical, ethical, and cultural dimensions.
Only with such preparation will it be possible to ensure that AI does not remain a collection of disconnected projects or rhetorical promises. Technological literacy at the highest levels of leadership is now a prerequisite for turning AI into an organizational framework capable of fostering trust, competitiveness, and meaning in the digital age.
Referencias:
Technical University of Darmstadt (2024). Executive AI Literacy: A Text-Mining Approach to Understand AI Skills of Leaders. Springer.
MIT Sloan Management Review (2024). Why Executives Can’t Get Comfortable with AI.
Fast Company (2024). The AI Gap in Executive Leadership Teams.
Gartner (2023). AI Project Scaling Report.
McKinsey & Company (2023). The State of AI in 2023.
PwC (2023). AI Predictions.
Axios (2025). AI Learning Gap Fuels Investor Concerns.
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