AI literacy has become essential for IT professionals, enabling informed decision-making, and the ability to harness the technology for automation, efficiency, and problem-solving across business operations.
IT pros who understand AI can make more informed decisions about integration, risk, and innovation, but AI literacy is not limited to IT specialists.
Iris Adae, Vice President of Data and Analytics at KNIME, stresses leaders across functions need to know both the capabilities and limitations of AI.
“Many requests ask for AI when simpler automation would suffice,” she says.
Judging when AI adds value and when traditional tools are more efficient is now a critical leadership competency.
Core competencies of AI literacy
Developing AI literacy requires a combination of technical fluency, ethical awareness, and strategic application.
This includes foundational knowledge of machine learning (ML) and generative AI (GenAI), data literacy, ethical awareness, and collaboration with AI systems.
Doug Gilbert, CIO and Chief Digital Officer at Sutherland Global, frames this as three tiers of literacy: foundational fluency for all employees, role-specific expertise for “super users,” and leadership acumen for executives who must connect AI adoption to strategy and ROI.
Prompt engineering, an emerging skill emphasized by Adae, is increasingly critical for effective interaction with AI tools.
Data quality and governance underpin successful outcomes, with biased or incomplete data undermining results regardless of technical proficiency.
Responsible and ethical AI literacy
Understanding the ethical implications of AI is inseparable from technical skills. Derek Ashmore, AI Enablement Principal at Asperitas, explains AI literacy requires awareness of bias, privacy, and unintended consequences, paired with frameworks that ensure responsible use.
“The most effective approach treats AI literacy as a shared organizational responsibility,” he says.
Executives provide vision, technical leaders guide standards, and all employees contribute by engaging, experimenting, and applying AI responsibly in their roles.
Soft skills such as ethical judgment, adaptability, and critical thinking are critical complements to technical literacy, while change management and collaboration across business and IT teams--often overlooked—are decisive for success.
“AI is there to augment, not take over,” Gilbert says.
The ability to challenge assumptions, question outputs, and maintain accountability ensures human judgment remains central. For organizations, embedding ethical AI literacy means balancing experimentation with safeguards.
Adae emphasizes the need for compliance teams to work closely with IT and learning teams to define guardrails while encouraging practical application.
Building scalable AI literacy programs
Organizations are increasingly treating AI literacy as a shared responsibility, with successful programs embedded directly into workflows, not confined to classrooms.
Sutherland, for example, delivers “10-minute plays” inside collaboration tools like Microsoft 365 and Jira, combined with labs, sandboxes, and role-based certification.
Ashmore says he agrees that scalability depends on role-specific training, modular content, and hands-on experimentation.
“This ensures employees not only understand concepts but also practice using AI tools effectively in their day-to-day tasks,” he says.
Adae stresses the importance of integrating AI literacy into real work from the start, noting that learning only sticks if you can apply it immediately.
Microlearning modules and practical projects help employees build confidence while reinforcing organizational standards.
Adae highlights creativity as a differentiator in an AI-first world, noting the ability to think outside the box and adapt to evolving technologies helps teams harness AI for innovation rather than treating it as a static tool.
Who leads the push for AI literacy?
Responsibility for AI literacy cannot rest solely with IT departments. Executives must provide sponsorship and resources, IT leaders must set technical standards, and HR and L&D teams must ensure scale and tracking.
Gilbert underscores a shared approach where CIOs and CDOs secure governance, HR integrates skills into role playbooks, and business units embed AI into existing workflows.
Dedicated teams aligned with the CDO are often best placed to lead enterprise-wide literacy efforts, but they must work in close collaboration with compliance and training teams.
Preparing for the future of work
AI literacy is not a one-time skillset but a continuous learning process. Technologies evolve rapidly, requiring IT professionals to update their knowledge of new models, frameworks, and enterprise applications. Without a mindset of continuous learning, even skilled practitioners risk falling behind.
The future of AI literacy lies in combining technical training, ethical frameworks, and collaborative learning across organizations and educational institutions.
“Education and training must help employees use AI responsibly while fostering creativity and adaptability,” Adae says.
For IT leaders, the path forward is clear: embed AI literacy into daily work, balance technical and soft skills, and ensure responsibility is shared across the organization.
In doing so, enterprises prepare their workforce not only to keep pace with AI but to lead in applying it strategically and responsibly.
“Without AI literacy, organizations risk misusing AI, underestimating its impact, or falling behind competitors who are able to harness its full potential,” Ashmore says.
Ready to build AI literacy that advances your career and strengthens your organization? CompTIA AI Essentials gives you the fundamentals to understand and apply AI responsibly, while AI Prompting Essentials shows you how to interact effectively with AI tools and apply them responsibly across your workflows, from strategic planning to daily productivity.