AI Literacy: Why Every Executive Leader Must Grasp the Foundations of Artificial Intelligence

June 24, 2025

The ongoing digitization of enterprise functions has placed artificial intelligence at the center of executive conversation. For leaders charged with operational, strategic, or fiduciary responsibility, the ability to comprehend AI is quickly becoming essential, not peripheral. This competence—commonly referred to as AI literacy—merits clear definition and measured discussion.

Defining AI Literacy

AI literacy refers to a working understanding of how artificial intelligence systems are structured, how they function, and how their outputs may be interpreted, contested, or applied. It does not imply technical proficiency in programming or data engineering. Rather, it denotes an informed capacity to engage with AI technologies thoughtfully, with regard to their design, application, limitations, and consequences.

Executives who are AI literate are not expected to build algorithms. They are, however, expected to understand the assumptions behind a model, question the reliability of a forecast, and recognize when a system’s logic may be flawed or misaligned with business goals.

The Executive Relevance

1. Strategic Decision-Making Now Involves Technical Judgment

In years past, technical matters could be assigned to specialists with little involvement from executive leadership. Today, the pervasiveness of AI in customer engagement, logistics, human resources, and financial forecasting has altered that dynamic. Decisions involving automation, risk models, and predictive tools now fall directly within the purview of senior management. Executives must be capable of distinguishing between meaningful innovation and ill-considered adoption.

2. Governance Standards Require Competency

With increasing scrutiny from regulators, shareholders, and the public, senior leaders are now expected to maintain oversight of systems that were previously outside their scope. Algorithmic fairness, data provenance, and model transparency are no longer niche concerns. They are governance obligations. A boardroom conversation about liability, compliance, or risk mitigation is incomplete without reference to the AI systems in operation.

3. Leadership Requires Language Alignment

Most business functions now interact with AI-enabled systems in some form—whether through CRM automation, fraud detection, dynamic pricing, or talent analytics. Without a shared vocabulary, leadership cannot facilitate effective dialogue between technical teams and business units. AI literacy enables senior leaders to ask appropriate questions, interpret outputs with discernment, and engage in productive collaboration with data professionals.

4. Talent Development Depends Upon AI-Aware Leadership

As internal teams adopt new tools and workflows influenced by machine learning or automation, leadership must be prepared to guide those transitions. This includes anticipating the training required, understanding potential disruption to legacy processes, and setting clear expectations for performance and ethical boundaries. Delegating these matters without understanding their implications invites both inefficiency and reputational risk.

Where to Begin

Executives interested in strengthening their AI literacy might consider the following measures:

• Allocate time each quarter for structured reading on current developments in artificial intelligence, particularly as they relate to business strategy, ethics, and policy.

• Participate in formal programs or seminars oriented toward non-technical leaders, offered through business schools or research institutes.

• Establish internal forums or working groups that include data professionals, operational leaders, and legal advisors, focused on the governance and deployment of AI systems.

• When evaluating new tools or technologies, insist upon clarity regarding model assumptions, data sources, limitations, and potential failure modes.

Final Considerations

The question is no longer whether AI will influence the modern enterprise. It already has, and will continue to do so with increasing breadth and depth. The more pressing concern is whether those in positions of authority possess the conceptual fluency to manage these changes responsibly. AI literacy is not a future skill. It is a present necessity for those entrusted with directing institutional outcomes, safeguarding resources, and stewarding public trust.