AI literacies aren’t theoretical—they’re lived, evolving and deeply embedded in the ways educators, instructional designers, and leaders engage with AI. This second post in the series on AI literacies explores how these roles are shaping and being shaped by AI literacies in real-world educational settings. Missed the first post? Read it here.
I’ve always been fascinated by birds. Living in a desert that borders a water source, I often find myself observing the unique mix of native and migratory birds that pass through—each one with distinct behaviors, adaptations and interactions.
My approach to birdwatching is the same as my approach to AI literacies. While frameworks and rubrics are helpful, the real magic happens in the wild—in classrooms, design labs and leadership discussions where people engage with AI in dynamic, unexpected ways. AI literacies sit within that ecosystem, reflecting the sociocultural contexts and nuance of AI usage across a wide array of communities and learning environments. Like the migration of birds, we’re shifting as a field to a more pluralistic view of the competencies and skills needed to use AI meaningfully across educational contexts.
A Migration from AI Literacy to AI Literacies
For ages, literacy was framed as a singular skill—something that educators and students either possessed or lacked. This binary approach positioned learning as a static checkpoint rather than an evolving set of competencies that shift and adapt over time. The same has happened with AI with institutions often focused on technical proficiency, assuming that exposure to AI tools alone would be enough to prepare learners for AI’s impact on education. But just as birds migrate in response to changing environments, educators have been moving—sometimes gradually, sometimes rapidly—toward a broader, more nuanced understanding of AI’s role in learning.
As AI has become more embedded in course design, teaching practices, and institutional strategy, this migration has accelerated. Educators, instructional designers and leaders have come to recognize that AI is not a single destination to reach but an ongoing journey that requires agility, adaptation, and collective movement. Instead of treating AI literacy as a fixed skill set, they are defining AI literacies as a plural, interconnected set of dimensions—one that reflects the varied ways AI is applied across roles, disciplines, and learning environments.
This shift has also reshaped how educators engage with AI. Faculty members who once hesitated to introduce AI into their teaching due to concerns about expertise have started experimenting, embracing iterative learning rather than waiting to feel fully prepared. Instead of positioning themselves as static knowledge holders, they are migrating toward more exploratory, student-centered engagement with AI, using it as a tool for inquiry rather than mere automation. Instructional designers, responsible for shaping AI-augmented learning spaces, are no longer just automating workflows; they are critically evaluating AI’s impact on learning design, ensuring that AI supports—not replaces—the human connections at the heart of education. Meanwhile, institutional leaders have expanded their focus from AI compliance and risk management to aligning AI literacies with institutional values, ensuring that AI adoption enhances access, equity and innovation rather than reinforcing systemic inequalities.
This migration has led to something powerful: a shared language that allows educators, designers and leaders to communicate more effectively about AI’s evolving role in education. Conversations have moved beyond technical training and into values-driven discussions about what responsible AI usage looks like in different contexts. As a result, students are experiencing AI-infused learning environments that encourage critical thinking, ethical engagement and creative problem-solving—skills that will serve them well in an AI-driven world.
Applying AI Literacies Across Roles: Educators, Designers, and Leaders
How do AI literacies develop in real-world educational settings? Rather than following a linear progression, AI literacies emerge organically as individuals engage with AI tools, confront challenges and refine their approaches over time. Across classrooms, design teams and leadership circles, we see a common theme: those who approach AI with curiosity, adaptability and reflection are the ones who cultivate the deepest AI literacies. Below, we share the findings from a research study commissioned by UNESCO IITE and Shanghai Open University with the goal of surfacing AI literacies as observed across six continents and over 25 countries.
Educators
For educators, AI literacies have begun transforming how faculty engage with their students. Initially hesitant to introduce AI in their classrooms, many instructors feared they needed full mastery before discussing AI with learners. However, by embracing cognitive and constructive AI literacies, they reframed AI as a co-explorer rather than an authoritative source. Faculty who took this approach reported deeper student engagement, as learners saw AI not as an infallible answer machine but as a tool for experimentation, iteration and critical thinking—mirroring the same skills required in research and problem-solving.
Designers
Instructional designers have also undergone a shift, moving from viewing AI as a threat to traditional design workflows to recognizing it as a means to extend creative capacity. Many designers began by experimenting with AI-generated content, only to find that raw AI outputs often lacked the nuance and depth needed for higher-order learning experiences. By developing critical and cognitive AI literacies, they learned to train AI tools for low-level production tasks while reserving their expertise for high-impact instructional strategies. This shift allowed them to spend more time on meaningful course enhancements, such as designing authentic assessments, refining alignment with learning objectives, and incorporating AI as a feedback and quality assurance tool.
Leaders
For leaders, the development of AI literacies has been pivotal in shaping institutional strategy. Many initially focused on policy enforcement and risk management, but as AI usage and literacies evolved, they began integrating AI into broader institutional goals around access, innovation, and inclusion. Leaders with strong civic and communicative AI literacies have played a crucial role in facilitating interdisciplinary collaboration, ensuring that AI adoption aligns with institutional culture and values. As a result, rather than AI policy being dictated from the top down, leaders, faculty and designers are now engaging in shared, ongoing discussions about responsible AI use—building a culture where AI literacies are not just supported but actively cultivated.
AI Literacies Taking Flight
The development of AI literacies is not a passive process—it requires ongoing exploration, reflection and shared learning. This means embracing the uncertainty that comes with technological change, not as a barrier, but as an opportunity to develop new ways of thinking, creating, and collaborating.
For those looking to deepen their engagement with AI literacies, there are many ways to continue the journey. The Dimensions of AI Literacies taxonomy offers a structured guide for understanding the dimensions that shape AI engagement, while the AI Literacies Applied collection highlights real-world examples of these literacies in action. A free Brightspace mini-course called AI Literacies Unlocked provides a hands-on learning experience, offering practical strategies for developing AI literacies in different educational contexts. New publications from UNESCO IITE will soon share further insights, helping institutions around the world navigate AI’s role in shaping the future of learning—you can visit the Opened Culture website to explore these open educational resources as they are posted. And for those already seeing AI literacies emerge in their work, an open database of case studies allows any educators and practitioners from around the world to share their experiences, contributing to a growing community of knowledge and practice.
AI literacies are no longer a fixed set of competencies to be acquired but an ever-moving process of observation, adaptation, and collective learning. Just as migratory birds rely on environmental cues and one another to navigate changing landscapes, so too must we remain attuned to the shifting nature of AI in education. The key is not to seek a final answer but to embrace the movement—continuously watching, questioning, and evolving alongside the technology itself.
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