What Is AI Literacy? Why It Matters Today
Artificial Intelligence (AI) is ceasing to be a theoretical notion in the laboratory. It is now used to drive search engines, recommendation systems, industrial control, medical diagnosis, customer support and even creative applications such as text and image generators. In industries, AI is influencing decisions, strategies, and outcomes. Through such a quick integration, a new term has become a necessity of the contemporary employee and management – AI literacy.
The concept of AI literacy is the skill to learn, communicate with, analyze, and ethically use AI technologies in ways that are significant. It does not just know about the existence of AI; it is about knowing what AI does, how it functions, and why its application has effects both good and bad. This includes:
- Learning the fundamentals of AI (e.g., machine learning, neural networks, natural language processing).
- Understanding the process of AI system decision-making.
- Making informed decisions when and how to apply AI tools.
- Understanding ethical, societal, and governance AI implications.
— and practicing responsible and safe AI in your sector.
Other research frameworks divide AI literacy into several dimensions, such as technical understanding, socio-ethical consciousness, and critical analysis of AI results. These models note that AI literacy is not an exclusive skill of technologists, but a socio-technical skill that every part of society needs.
AI Literacy vs. Digital Literacy
Whereas digital literacy aims at knowing general digital tools (e.g., email, spreadsheets, social media), AI literacy is more precise, i.e. how intelligent systems work, how they make predictions or decisions and how humans ought to interact with it in a reflective way. The concept of AI literacy is being perceived as the new literacy necessity that defines the world of the twenty-first century, having become a successor of reading, writing, and digital literacy.
AI Literacy Core Competencies
- The skills to ensure that people are best considered as AI literacy.
- Understand AI applications: Understand the application of AI and its significance.
- Understand AI behaviour: Understand that AI outputs are not always (infallible) true.
- Evaluate the quality and bias: Measure the quality and reliability of the AI systems.
- Implement AI tools successfully: Implement AI tools to complement work, not to substitute human judgment.
- Reflect upon ethical and legal aspects: Learn about privacy, accountability and transparency.
Studies indicate that interdisciplinary perspectives should also be included as part of the comprehensive picture of AI literacy such that they introduce technical, social, ethical, and futuristic skills.
The AI Era of Leadership: What AI Literacy Means to Leaders
- The Strategic Imperative of AI Literacy.
AI is transforming the world of organizations. AI can affect decision-making across all levels, starting with the automation of the routine and providing strategic insights driven by data. AI literate leaders are able to:
- Where AI can be used to make things happen.
- Assess AI projects in terms of risk, payoff and ethical compliance.
- Smart AI strategy communication with stakeholders.
- Lead in responsible usage of AI.
Conversely, leaders who are not AI literate will be replaced by the rate of change and make technologically blind or even damaging decisions. AI literacy is not an option anymore, but it is the cornerstone of significant leadership within digitally-driven organizations.
AI Literacy Levels among Leaders
There is no AI literacy on one scale. Rather, it may be pictured as three connected capability layers:
- Basic AI Fluency
Learning the basics and the effect of AI on business and society.
- Applied AI Competence
Understanding how to implement AI solutions in strategic decisions and operations.
- Advanced AI Leadership
Creating change, governance, policy, and innovation of an organization using AI.
The more the leader is involved with AI, the higher the probability of developing competitive advantages, prudently managing risk, and resulting in ethical adoption of AI.
AI Literacy as Competitive Advantage
Leaders that are robust in AI literacy are able to:
- Formulate AI policy and governance structures.
- Connect the technical and business stakeholders.
- Assess suppliers and AI technology more carefully.
- Expect AI to bring disruptions to their industries.
- Develop resilient cultures when there is constant innovation.
AI literacy will enable the leaders to see beyond technology buzzwords and position AI as a strategic asset their organization needs rather than a threat.
Doctorate in AI: What Is It and What Does It Offer?
The doctorates with respect to AI can be broadly divided into two:
- Research Doctorates (PhD)
These are dedicated to original research, the development of the frontier of AI knowledge and theory.
- Professional PhD (e.g. DBA in AI)
These are dedicated to strategic leadership and business impact, governance, and innovation with the use of AI.
The two pathways both lead to a doctoral title, however, with different outcomes and target audiences.
Doctorate in AI (DBA in AI/ML) at IMET Worldwide
An outstanding example of a professional doctorate is the Doctor of Business Administration (DBA) in Artificial Intelligence (AI/ML) program at IMET Worldwide. Such a program is a contrast to a classical academic PhD because it focuses on professionals and leaders with experience and aims to include high-level AI approaches into their leadership portfolios.
Important aspects of the AI Doctorate Program at IMET Worldwide:
- 100% Online Delivery: Convenient design to fit working professionals.
- 1:1 Mentorship: Expert mentors provide direct guidance during the research process.
- Global Availability: Open to the professionals all over the globe, especially the C-Suite executives and top leaders.
- Publication Support: Help to publish the research in the well-known journals and platforms.
Result: The graduates obtain the prestigious prefix of Dr., which adds credibility and leadership power.
The program is usually 12-24 months, during which the emphasis is placed on AI/ML governance, risk management, strategy, and solving real-world problems.
The program is designed for those leaders who want to bring their expertise in the industry to strategic research, thought leadership, and boardroom power in AI initiatives.
Do Leaders need a doctorate in AI?
At this point, the most significant question appears: Do leaders need a doctorate in AI?
To Most Leaders AI Literacy, Doctorate Is Optional. It is evident that modern leadership must be AI-literate. Leaders must be able to:
- Know how AI can be used in their strategy.
- Assess AI project proposals and claims with vendors.
- Lead teams by ethical and governance issues.
- Share AI strategy with stakeholders.
The range of avenues through which AI literacy can be acquired are:
- Professional certificates
- Professional executive training.
- Seminars and practical courses.
- Industry conferences and knowledge networks
These paths can often be more practical and cost-effective than a doctorate for many leaders.
2. When a Doctorate Can Be Valuable
While not strictly required for leadership, a doctorate, especially one focused on AI can be valuable when a leader’s role involves:
a. Thought Leadership and Global Influence
If the objective is to become a recognized authority in AI strategy, policy, or innovation, a doctorate helps formalize that expertise.
b. Governance and Ethical Leadership Roles
Leaders heading AI governance, compliance, or policy councils may benefit from the depth of understanding a doctoral study affords.
c. Academic or Research-Driven Leadership
If a leader wishes to teach, consult globally, or contribute to academic literature, a doctorate becomes highly relevant.
In short, a doctorate amplifies credibility and depth, but is not the only route to effective AI leadership.
3. The Trade-Offs: Time, Cost, and Relevance
Doctorate programs — including those like IMET Worldwide’s DBA in AI/ML — require significant investment in time, research, and sometimes cost. Leaders must weigh:
- Opportunity cost: Time away from operational leadership
- Return on investment: Does the doctorate open new strategic opportunities?
- Relevance: Does the program align with the organization’s evolving needs?
For some leaders, targeted AI literacy programs or executive courses may deliver comparable impact without the length or depth of a doctorate.
Building AI Literacy at Every Level of Leadership
AI literacy shouldn’t be reserved for senior executives alone. Organizations benefit when:
- Teams across functions understand AI’s role
- Decision-makers can discern AI strengths and limitations
- Ethical and governance frameworks are shared responsibilities
- AI literacy becomes part of continuous learning and culture
Investing in AI literacy at organizational levels — not just individual credentials — yields better integration of AI strategy, implementation, and responsible use.
Conclusion: Bridge the Knowledge, Not Just the Hierarchy
In a world where AI shapes strategic decisions, customer experiences, and operational efficiency, AI literacy is no longer optional — it is essential for leaders at all levels.
However, a doctorate in AI is not a universal requirement for leadership. It is a powerful differentiator for leaders seeking thought leadership, academic authority, or governance roles deeply tied to AI strategy.
Programs such as the Doctorate in AI/ML offered by IMET Worldwide provide senior professionals with research-based credentials, mentorship, and publication support that help bridge experience with academic rigor and strategic influence.
Ultimately, leaders should aim for a balanced approach:
- Gain foundational AI literacy early
- Apply AI insights to strategy and ethics
- Consider advanced credentials like a doctorate when aligned with career goals and organizational needs
In the AI era, the most effective leaders are those who blend practical experience, strategic acumen, and informed understanding of AI — whether through certificates, courses, or doctorates.
