Artificial intelligence has entered classrooms around the world at an astonishing pace. Tools like ChatGPT and Gemini promise to revolutionize teaching by automating tasks, customizing learning, and expanding access to knowledge. But these tools should not be mistaken for infallible sources of truth – or as replacements for skilled educators despite what some studies seem to insinuate or claim.

These tools clearly offer real advantages, but they are still evolving systems trained on imperfect data – and not a substitute for pedagogical expertise at all.

In this article we explore where AI truly adds value, where it may fall short, and how teachers can stay in control of learning outcomes while using AI responsibly.

The Promise and the Hype of ChatGPT and Gemini

The rise of generative AI in classrooms has been both swift and profound. There is no question about that. Many educators see AI as a gateway to improved personalization, faster feedback, and administrative efficiency, while others seem to be afraid using it at all, especially at universities.

Platforms like ChatGPT can generate essays, solve equations, and even simulate Socratic dialogue. Gemini, Google’s rival, offers similar capabilities, claiming to assist in everything from lesson planning to real-time language translation.

But the capabilities of these tools are sometimes overstated or really misunderstood. Teachers are increasingly encouraged to “integrate AI into the classroom” without sufficient guidance on the risks and limitations of these tools.

AI Is a Tool, Not a Teacher

Effective education depends not on tools but on the craft, creativity, and adaptability of teachers navigating complex classroom dynamics. These include cognitive engagement, social-emotional support, formative assessment, and more – areas that current AI cannot authentically replicate. It might happen in the future, but right now this is not the case at all.

Sure, AI can offer scaffolds for some of these practices, but it often lacks the nuance needed to handle individual differences in learning styles, emotional needs, and social context. Teaching is a science, but also an art and a craft. AI models are neither artists nor artisans; they follow patterns, not pedagogical instincts.

Checking is key when using AI tools like ChatGPT.

Accuracy and Bias Remain Core Concerns in ChatGPT and Gemini

Critically, large language models can, and do, generate misinformation. A similar issue arises with many enterprises who faced challenges assessing the reliability of AI outputs, particularly in domains requiring nuanced judgment or ethical reasoning.

The issue? Hallucinations. Hallucinations occur when AI tools like ChatGPT and Gemini produce false or fabricated information, and they are a direct result of how these systems are built. These models do not “know” facts in a traditional sense; instead, they predict the next word in a sentence based on patterns learned from vast quantities of text. If the training data includes inconsistencies, misinformation, or gaps, the model may confidently generate incorrect statements that sound plausible. Furthermore, when asked about niche, ambiguous, or novel topics where clear information is lacking, the model may “fill in the gaps” with made-up content. This tendency is exacerbated by the absence of real-time fact-checking mechanisms in current AI architectures.

Add to this that countries like Russia are intentionally flooding the internet with misinformation – millions of webpages filled with fake news – specifically to influence the output of AI tools like ChatGPT. These manipulative strategies exploit the way AI models are trained on publicly available web data, thereby distorting information retrieval and amplifying biased or false narratives.

In education, this becomes a serious risk. A misinterpreted historical fact or a flawed mathematical explanation can derail a student’s understanding. Educators must act not as passive consumers of AI output, but as active verifiers and curators of AI-generated content.

The Danger of Pedagogical Complacency

There is an additional, subtler risk: pedagogical complacency. Teachers may begin to rely too heavily on AI for content creation, losing their professional judgment or capacity for creative lesson design. When students can auto-generate answers, critical thinking and inquiry-based learning can atrophy unless teachers actively design around these capabilities.

There is a clear need to preserve the complexity of teaching even while integrating new technologies. This means using AI for what it does well – generating ideas, drafting scaffolds, supporting administrative efficiency – without outsourcing the core mission of education: nurturing informed, analytical, and ethically aware citizens.

Best Practices for Integrating AI in Education

1. Center AI Use on Pedagogical Goals

Ensure that AI tools serve clearly defined educational outcomes, not technological novelty. Begin with instructional objectives – then determine where AI can meaningfully enhance learning, assessment, or equity.

2. Ensure Personalized Learning Without Sacrificing Human Judgment

Use AI-driven systems to create adaptive, student-centered pathways, offering real-time feedback and differentiated content. However, teachers must remain the final arbiters of assessment and progression.

3. Prioritize Ethical Data Use and Privacy

Establish clear, school-wide policies for data collection, consent, and usage transparency. Safeguard sensitive student data through strong encryption, clear accountability structures, and minimized data retention.

4. Identify and Mitigate Algorithmic Bias

Before deployment, test AI systems on diverse datasets. Involve educators in reviewing outputs for bias in grading, recommendations, or content delivery.

5. Support Teachers with Ongoing Professional Development

Equip educators with the skills to critically evaluate, integrate, and monitor AI tools in classrooms. Training must go beyond technical use—covering AI literacy, ethics, and collaborative pedagogy.

6. Foster Student Awareness and Critical Thinking on AI

Incorporate AI literacy into the curriculum. Teach students to analyze AI outputs, question bias, and understand ethical implications.

7. Balance Automation with Human Connection

Automate administrative tasks (e.g., grading, attendance) to give educators more time for mentorship, project-based learning, and emotional support.

8. Adopt Transparent AI Frameworks

Develop institutional guidelines for responsible AI use. These should cover consent, accountability, content accuracy, and escalation protocols for error correction.

9. Use AI to Enhance Accessibility and Inclusion

Deploy AI tools to support students with disabilities, language barriers, or limited resources. Ensure accessibility features like text-to-speech, translation, or adaptive pacing are equitably distributed.

10. Evaluate AI’s Educational Impact Continuously

Track performance data, but also collect qualitative feedback on AI’s effect on student engagement, trust, and well-being. Adjust policies as technologies—and their consequences—evolve.

Teachers Remain at The Heart of Learning

AI tools like ChatGPT and Gemini represent powerful assets for modern education – but only when their integration is intentional, transparent, and guided by educational priorities. Teachers remain at the heart of learning, and AI should enhance their impact, not replace their role.

Educators must lead with both openness and skepticism, ensuring that AI enriches student learning without compromising human judgment, equity, or trust. That balance is your responsibility as a teacher.


I have a background in environmental science and journalism. For WINSS I write articles on climate change, circular economy, and green innovations. When I am not writing, I enjoy hiking in the Black Forest and experimenting with plant-based recipes.