Artificial intelligence is embedded in schools everywhere, and the adoption rates tell you how fast this has happened. By the 2024-25 school year, 85% of teachers and 86% of students used AI tools in some capacity, making this technology mainstream rather than experimental. But here’s what nobody’s really saying out loud: while AI promises to transform education, it’s simultaneously creating serious problems, known as AI in education risks, that schools aren’t prepared to handle.
The reality of AI in education risks is complex, and it’s crucial to address these challenges as we move forward.
Let me walk through what’s actually happening in classrooms instead of just repeating the optimistic narrative about personalized learning and efficiency gains.
These AI in education risks are often overlooked in favor of the benefits touted by technology advocates.
Understanding the implications of AI in education requires a critical lens on its integration.
Half of Students Feel Disconnected From Their Teachers
Overview of AI in Education Risks
Exploring the landscape of AI in education risks helps us identify potential issues that may arise as reliance on technology increases.
This one matters more than the statistics suggest because it gets at something fundamental about education, particularly regarding AI-related risks. Fifty percent of students report feeling less connected to their teachers when AI enters the classroom.
Teachers see this disconnection too: 47% worry that increased AI use is hurting peer-to-peer connections between students. Parents feel it as well—50% fear that reliance on AI will weaken students’ social development. The problem isn’t AI itself; it’s what happens when schools shift learning from human interaction to software interactions. Students spend more time with algorithms and less time in conversations that require vulnerability and real thinking.
This matters because social skills, empathy, and the ability to work through problems with another human being develop through actual human connection, not through interactions with machines. Over time, when students miss those opportunities, something important gets lost in their development.
Neglecting AI in education risks can lead to significant long-term consequences for student development.
Algorithms Are Perpetuating Historical Inequalities in Grading and Admissions
Here’s where the technical meets the deeply unfair: AI grading systems, college admissions algorithms, and learning analytics platforms are trained on historical data, which reflects historical inequalities. Non-native English speakers get penalised unfairly by AI grading systems that weren’t built to account for language diversity. Predictive analytics used in college admissions amplify long-standing inequities by assuming that past patterns should predict future potential.
These challenges highlight the need for transparency and accountability in how AI is implemented, especially concerning AI in education risks.
The developers of these systems usually don’t intend to discriminate—bias seeps in through the data itself and through teams that lack diversity in their development process. Once bias is encoded into algorithms, it’s harder to see and much harder to fix because the system applies it consistently across thousands of decisions. Black students have reportedly received fewer academic resources when algorithms identified them as “at-risk” based on limited historical data.
The uncomfortable truth is that the system treated everyone equally—it just treated them unequally in the direction historical inequality was already pushing. That’s how algorithmic bias works: it doesn’t add new discrimination; it scales up existing discrimination and makes it invisible because a computer made the decision.
Addressing AI-related risks in education is essential to creating a fair and equitable learning environment.
Data Privacy Concerns Jumped Dramatically in Just One Year
Schools are collecting enormous amounts of data about students—every answer, how long they spend on each question, what subjects they struggle with, and sometimes even voice recordings and facial recognition data from proctoring software. Educators’ privacy concerns grew from 24% in 2024 to 27% in 2025, which might not sound like much until you realise that’s a 12% jump in a single year.
In light of AI in education risks, schools must prioritise privacy and security in their data practices.
The Proctorio breach affected 444,000 students’ records, which isn’t theoretical—that happened. When schools use third-party AI tools, student information lives on company servers, and schools often have no idea what happens to that data afterward. Companies might share it with other businesses, use it for their own research, sell it to advertisers, or keep it indefinitely. Once data leaves the school, the school loses control over it.
Biometric data—facial recognition from proctoring software and voice samples from language learning apps—is collected and stored permanently. A student doesn’t really have a meaningful way to delete it or prevent its use later. This data follows them through their educational history and beyond.
Students and educators alike need to be aware of AI in education risks to navigate the digital landscape responsibly.
Teachers Are Using AI Without Training or Understanding
Here’s a statistic that should concern anyone involved in education: 85% of teachers are using AI, but only 48% received any training or professional development from their schools on how to use it. Less than half of teachers have received any preparation for this technology that’s supposed to fundamentally change their classrooms.
Without proper training on AI in education risks, teachers may inadvertently compromise student safety.
Of the teachers who did get training, less than a third learned what AI actually is and how it works at a basic level (25%). Only 29% got meaningful guidance on using AI tools effectively in their actual classrooms. Just 17% learned how to monitor or check AI systems for problems. Teachers are expected to integrate technology they don’t fundamentally understand, and they’re making decisions about student data without training on how to protect it or even recognize when it’s being misused.
The situation with students is similar in many ways: 48% of students got some information about AI from their school, which means 52% are just figuring it out on their own. Only 12% were taught what AI actually is at any meaningful level. Only 17% learned about the genuine risks. Only 22% learned their school’s actual AI policies. Without this foundational understanding, students can’t make informed decisions about when to use AI and when they actually need to develop their own skills.
Ensuring students understand AI in education risks is paramount for their future success.
Critical Thinking Weakens When Students Always Have Instant Answers
Seventy percent of teachers worry that AI weakens critical thinking and research skills among students, and they’re seeing this concern play out in their classrooms every day. When students find answers quickly through AI instead of struggling through the problem-solving process, they don’t develop the ability to sit with confusion or to reason through incomplete information. They accept what AI says instead of questioning it because the faster path becomes the default path.
Teachers should be equipped to discuss AI in education risks with students to foster critical thinking.
When students always have instant answers available, they don’t practice researching or develop the judgment needed to evaluate information quality. They don’t learn to reason or to sit through the productive struggle that builds problem-solving capability. These skills take time to develop because they require struggle—and the struggle is where learning actually happens, not where it gets in the way of learning.
A student graduating in 2030 will have gone through their entire education with AI constantly available, which raises a serious question about what that does to their critical thinking ability, their creativity, and their capacity to solve problems nobody’s ever solved before. This is a long-term educational concern that doesn’t show up in current test scores.
As students graduate, grappling with AI in education risks will be crucial for their adaptability.
Tech-Fueled Harassment Is Creating New Risks for Students
The Center for Democracy and Technology flagged something that doesn’t get adequate attention: AI is creating new vectors for students to harass and bully each other in ways that previous technology didn’t enable. AI chatbots can be weaponized for targeted harassment. Deepfake technology can humiliate students with disturbing effectiveness. Surveillance tools intended for security can be repurposed to invade privacy.
Addressing AI in education risks will help create a safer online environment for students.
This isn’t theoretical or hypothetical—students are already experiencing this right now. Unlike traditional bullying that at least had boundaries within a school, this harassment can spread globally and remain online permanently, accessible to anyone with a search engine.
Economic Inequality Is Actually Getting Worse Despite the Promise
Ultimately, discussions around AI in education risks must be integrated into school curricula.
AI in education was supposed to level the playing field by providing personalised learning for everyone and equal access to high-quality tutoring and resources. The reality isn’t matching that promise. Schools with money buy premium AI tools and can afford proper teacher training and ongoing support. Schools without money get the free or cheap tools, they don’t get training, and they don’t get the resources needed to implement systems effectively.
The AI education market is exploding—it grew from $7.57 billion in 2024 to a projected $112.30 billion by 2034. That money is flowing to the schools that can already afford cutting-edge technology, not to schools in low-income neighbourhoods. The gap between well-resourced and under-resourced schools is widening, not narrowing, and AI is accelerating that inequality rather than solving it.
Funding disparities further exacerbate AI in education risks, making it a critical area for reform.
What Schools Actually Need to Do
Training is essential—not just any training, but meaningful professional development on how AI actually works, what risks it poses, and how to use it responsibly in educational contexts. Schools need clear policies that determine which AI tools are allowed, what data can be collected, and how that data stays protected. Transparency with parents is non-negotiable because parents need to know what AI tools their kids are using and why those tools were chosen.
To protect students, schools must commit to addressing AI in education risks through comprehensive training.
Regular audits of AI systems matter because schools need to verify whether algorithms are treating students fairly, whether data is actually secure, and whether the tool is actually helping students or just creating new problems. Innovation is essential, but protecting students’ data, their relationships, and their development as independent thinkers matters more.
Final Remarks
As we reflect on AI in education risks, we can shape a more equitable educational landscape.
AI in education isn’t inherently harmful, and the technology could genuinely help students learn more effectively if implemented thoughtfully. But right now, schools are adopting AI too fast without adequate safeguards, letting companies deploy tools in classrooms without proper oversight, and expecting teachers and students to navigate these systems without meaningful training or preparation.
The decisions schools make in the next year regarding AI in education risks will determine whether the technology genuinely helps bridge educational gaps or deepens existing inequalities.