Building AI Literacy in Schools: Moving from Mystery to Mastery

Most educators know that students already use AI at school and in their daily lives—and that they have an important role to play in helping them understand it. But even as pressure grows for schools to step into that role, uncertainty around policy and practice has held administrators and districts back from formulating a comprehensive response.

A lot of the AI conversation understandably focuses on “how do we control AI usage?” Given how much technology has lowered the bar for cheating and made plagiarism harder to detect, it’s not something schools should ignore—but it’s not a complete response.

A comprehensive response to AI integration in education teaches children AI literacy, giving them the foundational understanding, skills, and support to become ethical and responsible architects of the technology rather than passive consumers.

Theorist Douglas Rushkoff argues that understanding technology is essential for participating in society:¹

In this article, we will explore the current state of AI literacy in schools, examine its limitations, imagine what a better state should look like, and suggest steps school leaders and educators can take to get there.

Why AI Literacy Matters Now

As with catching and riding a wave, the opportunity to shape how students understand and engage with AI is fleeting. AI literacy can make the difference between students becoming passive consumers of the technology or informed users and creators of it.

The challenge for educators is that learners are already using AI and they’re not waiting for schools to catch up. Globally, 86% of students regularly use AI in their studies, yet half don’t feel prepared, and 58% believe they lack knowledge.²

We’re at a pivotal moment when the decisions schools make today will determine whether students learn to surf AI with confidence or get swept up in the wave. The longer students go without genuine AI literacy, the greater the risk that we miss crucial developmental opportunities and that problematic patterns of AI use harden into habit.

Here are just a few examples of what’s at stake:

• Students left unevenly prepared for life and work in an AI-driven world.
   
• Underdeveloped critical thinking, creativity, and problem-solving skills from over-reliance on AI-generated answers.
   
• Social and cognitive costs as students grow too dependent on AI for support and connection.
   
• Increased risks around privacy, safety and responsible technology use.

The Current State of AI Learning in Schools

AI learning in schools is fragmented and inconsistent, making it difficult for districts and administrators to develop a comprehensive response. The result? Reactive stances that vary from school to school.

For some, AI is about compliance; for others, it's framed as a productivity tool or a cheating risk. Yet none of these perspectives alone helps students develop a deeper understanding of how AI works and how to use it responsibly.

Let’s look at the four biggest hurdles.

1. Over-Emphasis on Usage vs True Understanding

Many conversations about AI education tend to focus on the most visible parts: LLMs or AI chatbots. In particular, educators often focus on how to use these tools, including prompt engineering, productivity use cases, and the capabilities of different models. This isn’t AI literacy; it’s tool fluency. And while tool fluency is valuable, it’s also temporary. Skills gained using today’s tools may not be applicable to new ones that emerge in the future.

A more sustainable approach is to teach children the fundamentals of AI and how it’s built, so their skills can adapt and grow alongside AI’s development.

2. Educator Readiness is a Bottleneck

Understandably, some educators lack confidence in teaching AI. According to a LEGO® Education-led survey of educators worldwide, 81% view AI literacy as a priority, but only 42% feel equipped to teach it effectively.³ Even among computer science (CS) specialists who have received AI-focused training, only 49% report feeling confident.⁴

Although these findings focus on teacher readiness, the same confidence gaps extend to school and district leaders. When administrators are asked to set policy, make procurement calls, and define what good AI instruction looks like without clear answers across the sector, their uncertainty filters into classrooms. So, while lack of training and experience is part of the issue, without a shared infrastructure that includes standards, vetted curriculum, and clear policy, a cohesive AI literacy response is difficult.

3. Student Confidence is Outpacing Competence

Globally, 79% of teachers agree that students are confident in using AI, but 63% also agree that students are not competent AI users.⁴

Despite their confidence, AI use without competence can do more harm than good. When children’s understanding of AI is “prompt goes in, authoritative answer comes out,” they’re susceptible to the bias and misinformation inherent in these systems. The same mindset can also lead to the deterioration of fundamental learning skills like critical thinking and problem-solving due to cognitive offloading or an overreliance on AI to do their thinking.

4. Schools Are Trying to Catch Up to a Moving Target

For something as complex and decentralized as the education system, change happens slowly. Schools need time to catch up and adapt to new, rapidly evolving technologies, but during this period, there’s uncertainty and fragmentation.

However, the education system has experienced disruption before. New technologies like computers, smartphones, and even radio were disruptive in their time but are now part of daily life and, in some cases, even the curriculum. Change can be slow, but that doesn’t mean progress isn’t happening. The adjustment period we’re in now takes time, but we’re still heading in the right direction.

What a Better State of AI Literacy Should Look Like

If AI literacy education is currently fragmented and reactive, the aim should be something broader, more intentional and more lasting. The goal isn’t students’ fluency in a single AI tool or to craft the perfect usage policy. It’s to help them understand the mechanics of AI, where it works, where it fails, and what responsible use requires.

As Andrew Sliwinski, Head of LEGO® Education Product Experience, explains:⁵

A better approach to AI literacy education in schools includes:

1. Prepared and Empowered Educators

Effective AI literacy starts with competent and confident teachers who are supported to make sound instructional decisions. This doesn’t mean they need to be AI specialists, but they do need to understand the goals, key ideas and risks well enough to guide students. This is not just relevant for CS and technology specialists, but all educators. The more teachers who have the knowledge to be competent AI facilitators, the greater the access to and equity in AI learning will be.

2. Prioritizing the Underlying Technical Foundations That Transfer

Robust AI education empowers students to become not just competent users of technology but also architects of it, too. That starts with a foundation in core CS concepts, including algorithms, data representations, abstraction, and machine learning. These skills give students the tools to outlast fluency with a specific chatbot or platform.

What’s more, these building blocks should be core subjects alongside math and reading because they are too crucial in preparing students for the AI-powered world to be relegated to electives.

3. Agency & Empowerment over Fear & Prohibition

It’s understandable to feel cautious about AI. But preparing students with caution alone is not an effective strategy. If students only encounter AI through bans, warnings, or suspicion, they miss the chance to develop the judgment and confidence they will need outside the classroom.

Instead, educators should inspire curiosity and creativity by providing students with structured opportunities to explore AI, where they can ask questions and make mistakes in a safe environment. But student agency doesn’t mean handing control to AI. It means helping students to know when to rely on their own thinking, peers, and teachers.

How Do We Get There?

If the better state is clear, the real challenge is operational: what must change at the classroom, school, and district levels to move from a scattered response to meaningful AI literacy?

AI learning does not emerge from mandates alone; it requires support, design choices, and shared confidence.

1. Prepare Teachers to Facilitate AI Learning, Not Just Manage Its Use

Teaching a rapidly evolving topic like AI requires guidance and support from school leaders and districts. That means investing in training and providing effective solutions that reduce prep time and help close the confidence gap many educators feel.

Beyond facilitating professional development, school leaders also need to create conditions that allow this learning to happen. This includes setting aside time and space from daily work and providing explicit permission to apply the learning in the classroom.

Professional development (PD) should empower teachers not only to teach AI literacy but to use AI in their own roles. Rather than relying on one-off training sessions, strong PD strategies provide educators with ongoing support, practical resources, and classroom-safe tools that help them teach AI with confidence as the technology and its applications evolve over time.

2. Create AI Policies That Go Beyond Acceptable Use

AI policies shouldn’t sit in isolation or belong to a single department. If the AI use policy is positioned as an IT policy, it’s easy to assume responsibility rests solely with IT. But AI touches many aspects of school life, so an effective AI policy should reflect that.

To do this, AI should be addressed within existing policies, such as instructional policy, code of conduct, and data protection policies. This approach makes AI use everyone’s responsibility and better fosters the conditions for meaningful AI literacy across classrooms, schools, and districts.

3. Build AI Literacy on a Computer Science Foundation

AI might feel a lot like sailing into uncharted waters, but it’s built on CS fundamentals. In fact, 8 out of 10 teachers believe AI belongs within computer science education.³

Implementing AI literacy is challenging, in part because many aspects need to be developed from the ground up. CS, on the other hand, already has established frameworks, making it a powerful starting point for AI literacy. Not only because there are curriculum, standards, and instructional practices to build on, but also because teaching these fundamentals is one of the most impactful ways to give students the tools they need to start taking the magic box apart and to understand its pieces.

4. Start Early and Scaffold AI Confidence Across K–8

We can’t expect new surfers to ride a wave right away. Learners need to practice the movements and get familiar with the surfboard on shore before trying it in the water. And it’s the same for AI literacy.

Introducing students to AI and CS in age-appropriate ways, early in their education, helps them tackle more advanced concepts later and better understand the technology that already permeates their daily lives.

AI education needs to start in kindergarten and build progressively. This scaffolding supports the development of knowledge and skills while students are still forming problem-solving habits, creative-thinking skills, and beliefs about their identities. That can make the difference between students who identify with CS and AI and those who do not.

5. Make AI Learning Hands-On, Collaborative, and Accessible

Perceptions of how AI literacy might look in practice overlap with common concerns about CS learning—that it’s limited to solitary and screen-oriented work. But this doesn’t have to be the case. There’s plenty of room within these technical disciplines for accessible, multimodal approaches that get students off screens and working together.

Hands-on learning helps students engage with AI in practical and effective ways. By actively building, modeling, coding, and testing, learners can connect abstract concepts to observable cause-and-effect relationships. These experiences build confidence, support comprehension, and create multiple entry points for participation.

Collaborative discussion and problem-solving also strengthen metacognition, encouraging students to reflect on how they think compared to what AI “thinks” and reinforcing the role of humans in AI. When paired with scaffolded and multimodal learning experiences, these approaches can make AI concepts more accessible to a wider range of learners.

Where LEGO® Education Fits In

LEGO® Education supports the future of AI literacy through developmentally appropriate and hands-on learning experiences that help schools build confidence with AI in meaningful, accessible ways. Our goal is to support a future of AI that is safer, more concrete, more collaborative, and more accessible for both teachers and students.

LEGO® Education solutions support:

1. A Hands-On, Collaborative Path to Understanding

Tangible and collaborative learning that makes complex concepts easier to grasp and moves AI learning from passive to active.

2. Safety, Privacy, and Transparency by Design

With clear guidelines for child data protection and transparency around model inputs and data provenance, our AI learning experiences explicitly support student safety and well-being.

3. Built to Support Teacher Confidence

Designed to build teacher confidence, LEGO® Education’s solutions empower teachers and help them feel prepared to teach AI literacy.

What Building AI Literacy Makes Possible

When schools get AI literacy right, the result is not just better AI use. It is increased student agency, better teacher readiness, and a more thoughtful way for schools to engage with new technology without surrendering learning goals to the technology itself.

Defined, being AI literate means having the knowledge, skills, and mindset to

• understand how AI works
• think critically about its capabilities and limitations
• creatively use AI to innovate and solve problems across various technologies and real-world contexts

AI literacy strengthens both present-day and future readiness, so students are prepared not only for today’s tools but also for tomorrow’s world.

AI literacy outcomes:

1. Confident students who are better equipped to question, evaluate, and shape AI now and in the future.
2. Empowered teachers who can deliver clear instructional pathways that engage learners.
3. Schools move from reactive to intentional.
4. AI literacy becomes embedded within a broader future-ready learning model.