AI’s transformative impact doesn’t just lie in the technology, but in the human capacity to harness its benefits.
Without the AI literacy to engage knowledgeably, ethically, and strategically with artificial intelligence, institutions risk an implementation gap: with policy ambitions on one side and actual practice on the other.
To enable staff and students to leverage the benefits of AI for improving student and institutional outcomes, education leaders are turning their attention to AI literacy-building initiatives.
In this article, we draw on findings from KPMG’s 2025 global AI use survey, which outlines the scale of ‘inappropriate, complacent, and non-transparent’ AI use in the workplace, plus sector-specific research that finds a lack of clarity and coherence in educational AI use.
We conclude with concrete strategies for education leaders to build AI literacy in their institution: to further pedagogical and operational goals in the age of AI; to shift from fragmented to strategic AI adoption; and to appropriately leverage AI for institutional reputation and sustainability.
Why is building AI literacy an imperative for education leaders?
AI literacy is the potentially missing link between institutions’ AI policy and day-to-day practice. Informed use of AI can streamline administrative tasks and unlock new models of teaching and learning, as well as support wider objectives around student success, workforce preparedness, and inclusivity. But only when people know how to use it effectively.
While institutions are increasingly AI-positive – creating policies that encourage appropriate, ethical engagement for students and faculty – rapid AI evolution means people may struggle to keep up with the tools available to them.
AI literacy is the key to unlocking the many benefits of AI in education – from accelerating administrative workflows and improving equity in assessment, to creating more time for teaching and supporting student outcomes.
Here are five key benefits to be aware of:
- Administrative and operational efficiency
- Excellence in teaching and pedagogy
- Enhanced student outcomes and graduate quality
- Stronger academic integrity
- Improved research capacity
What are the risks of low AI literacy in education?
Low AI literacy risks staff and students using AI in a way that doesn’t support institutional goals, such as:
- Ineffective, inconsistent, or inappropriate staff use.
- Students misstepping into misconduct due to a lack of clarity.
- Missed opportunities to implement transformative tools.
Research indicates that AI literacy isn’t keeping pace with technology adoption, and this requires leadership intervention.
The wider workplace picture – lessons from KPMG’s global AI use survey
A 2025 global study by KPMG and the University of Melbourne found that 58% of employees intentionally use AI at work on a regular basis, but 61% have no AI training, and half report limited knowledge.
As a result:
"Many employees report inappropriate, complacent, and non-transparent use of AI in their work, contravening policies and resulting in errors and dependency."
Importantly, misuse isn’t necessarily intentional. KPMG highlights that "inadequate training, guidance, and governance of responsible AI" often leads to missteps, such as uploading copyrighted material into a public AI tool, or making mistakes using AI.
They also find that "governance and training to support responsible AI use appear to be lagging adoption."
Across all sectors, only two in five workers say their organization offers training in responsible AI use or has clear policies and governance frameworks in place.
KPMG concludes:
"There is an urgent need for organizations to proactively invest in responsible AI training and the AI literacy of employees to promote critical engagement with AI tools [and] put in place mechanisms to effectively guide and govern how employees use AI tools in their everyday work, and to promote greater accountability, transparency, and employee engagement."
The education sector challenge – findings from HEPI and Turnitin
Research from the UK’s Higher Education Policy Institute (HEPI) suggests that educational institutions aren’t always rising to this challenge.
HEPI found that only 35% of students feel supported by their institution to develop AI literacy, and just 42% believe staff are equipped to help them use AI effectively. Students also report confusion caused by inconsistent approaches to AI use among different staff members.
This is reinforced by research from Turnitin, which finds 95% of respondents think AI is being misused in the institution—though views differ among students, educators, and administrators on what amounts to cheating.
Not only that, but 50% of students, 39% of educators, and 28% of academic administrators do not know how to use AI effectively in their role.
Plus, different student demographics have varying levels of access to and confidence in using AI tools. HEPI found that students from historically marginalized or underrepresented groups in higher education are less likely to engage with AI, putting them at further disadvantage.
This lack of clarity and capacity risks deepening inequities: some students and staff will advance with AI fluency, while others are left behind.
Turning its attention specifically to education, KPMG reflects on this challenge, stating:
“Educators must equip students for a workplace where AI is a ubiquitous tool – ensuring they develop both human-AI collaboration proficiency, together with the essential human skills that underpin leadership, innovation, collaboration, and ethical decision-making.”
Together, these findings make one thing clear: institutional success, sustainability, and reputation rely on building AI literacy for educators, faculty, and students.
Five strategies to build AI literacy across your institution
AI literacy isn’t just a question of providing training; it’s a question of providing leadership. Education leaders need to model informed AI use and strengthen buy-in, allocate resources for training, and create structures for accountability.
By embedding AI literacy across staff and students, institutions can shift from fragmented approaches to cohesive, strategic adoption – creating a culture of innovation, critical engagement, and continuous learning.
1. Set a clear vision and strategic alignment
AI use must be strategic and aligned to clear outcomes related to your educational ethos and institutional goals. For example, student outcomes, graduate employability, operational efficiency, research, and innovation.
Consider a cross-functional steering committee that involves academic, administrative, IT, data, procurement, and student support representatives to develop your AI-literacy-building roadmap.
2. Review policies and governance
AI literacy requires clear and transparent guidance on the appropriate use of AI tools.
Start by reviewing student, staff, and institutional AI policies across key areas of AI usage, including ethical use cases in teaching and learning, accountability and disclosure of AI use, data and IP security, safeguarding, equity, and addressing bias.
Consider using a traffic light system to help people easily identify allowed, restricted, and discouraged uses of AI, since misunderstanding AI heightens the risk of academic misconduct and erodes trust.
3. Implement training and ongoing development for staff
Provide professional development opportunities – such as workshops, peer networks, and hands-on training with AI tools – to help faculty understand both the tools students are using and those that can enhance their teaching.
Training should also cover general AI topics such as GenAI prompt engineering, bias mitigation, and best practices for integrating AI into teaching and administration (UK Government).
Remember that AI evolves rapidly, and institutional AI literacy needs to keep pace. Invest in continuous professional learning for both staff and students, recognizing that AI literacy is not a one-off exercise but a long-term strategic commitment.
4. Provide student support and access to AI tools
Without deliberate support, access to AI tools and confidence in their use risk becoming a new dividing line. Women, lower-income students, and marginalized groups are already less likely to benefit from AI (HEPI).
By embedding AI literacy into the curriculum and providing access to core AI platforms, institutions can level the playing field and promote inclusive student success, as well as meeting rising student expectations. Currently, only 24% of students say their institution provides such access, despite 53% believing they should (HEPI).
Without dedicated AI literacy initiatives, only digitally advantaged students are likely to benefit from AI innovation and support, risking wider equity gaps across the institution.
5. Work with industry for employment-readiness
AI can impact student skill development. It’s essential to shape that in the right direction.
The World Economic Forum’s Future of Jobs Report 2025 finds graduates need a mix of technical and interpersonal skills to succeed, with AI and big data topping the list of fast-growing demand.
Teaching students how to use AI and LLMS, as well as question, verify, and critically engage with AI tools, is a vital skillset for the future of work.
KPMG recommends institutions work with industry to understand their AI literacy requirements, to ensure curricula prepare students to join the AI-ready workforce.
AI literacy resources for education leaders
- The UK government has an AI audit tool to help education leaders reflect on their current position.
- The National Centre for AI has a useful list of UK universities’ AI guidance.
- AI for Education has a list of all US states’ school AI policies.
- The Australian Framework for Generative AI in Schools provides a six-prong approach to educational governance.
- The US Department of Education publishes an inventory of its AI use cases for full transparency – something institutions could also consider.
Overview: Bridging policy and practice through AI literacy
As Turnitin’s research reminds us, the challenge is not only the presence of AI in education, but the preparedness of people to use it well. Schools and universities must build institutional AI literacy to empower staff and students to use AI with confidence, integrity, and purpose.
AI policies provide direction, but AI literacy brings them to life. Without understanding and experience, even the best-crafted rules can remain abstract and difficult to follow. When students and staff are AI-literate, policies can be applied with confidence and adapted as technologies evolve, with this ongoing alignment between policy and practice driving a responsible AI culture.
Institutions that prioritize AI literacy position themselves as leaders in digital transformation, enhancing their reputation, attracting students, and shaping a future-ready, ethical, and innovative learning environment.