A new report titled “How Teachers Are Using AI to Transform Education” reveals that artificial intelligence is already embedded in everyday teaching workflows, with lesson planning, assessment design and presentation creation emerging as the most common real-world classroom applications. The study is based on more than 115,000 AI content generations and insights from over 30,000 teachers using AI tools in daily practice.
AI Use in Classrooms Moves from Theory to Daily Practice
The report finds that AI is no longer a conceptual or experimental tool in education but is actively being used by teachers to improve lesson design, assessment creation, content visualisation, revision material, and classroom engagement. Rather than replacing teachers, AI is being used to augment pedagogy and reduce planning time while improving conceptual learning outcomes.
The analysis draws on anonymised usage data collected over roughly one year, reflecting natural classroom behaviour instead of controlled pilots or perception-based surveys, offering a realistic view of AI adoption in teaching workflows.
Top 10 AI Use Cases Identified in Real Classrooms
The study identifies ten dominant teacher-led use cases emerging from real usage patterns:
- AI-powered lesson planning
- Quiz and worksheet generation for assessments
- Presentation and visual content creation
- Academic writing assistance
- Activity and project-based learning design
- Concept explanation for conceptual clarity
- Video-to-learning resource conversion
- Creative resources such as stories, rhymes, flashcards
- Automated revision notes and study material
- Academic and school event planning
These tools are being used to design richer, multi-modal learning experiences and to convert curriculum goals into classroom-ready instruction.Lesson Planning and Assessment Lead Adoption
Among all use cases, AI-powered lesson planning emerged as the most widely used, with over half of teachers using AI tools to create curriculum-aligned lesson plans integrating explanations, activities and assessments. The data suggests that AI is functioning as daily instructional infrastructure rather than a planning shortcut.
Similarly, quiz and worksheet generators are being widely adopted to create grade-specific assessments, enabling frequent formative evaluation and concept-checking beyond rote memorisation
AI Enhances Teaching, Not Replaces Teachers
A key insight from the report is that teachers are using AI primarily to transform how they teach rather than automate teaching itself. The tools are being used to build deeper conceptual understanding, create experiential learning activities, and design differentiated instructional content suited to diverse learner needs.
The report emphasises that AI’s strongest impact is visible where it supports pedagogy and learning design rather than mere productivity gains. Teachers leverage AI to expand instructional possibilities and spend more time mentoring students and addressing learning gaps.
Barriers to Mass AI Adoption Remain
Despite growing usage, the report highlights that large-scale adoption of AI in education still faces challenges including tool complexity, fragmented platforms, affordability constraints, training requirements, and limited alignment with classroom realities.
Teachers are more likely to adopt AI meaningfully when it is simple, integrated into daily workflows, affordable, and designed around real classroom needs rather than generic chatbot-style interfaces.
Shift from Memorisation to Application-Driven Learning
The study argues that AI adoption aligns with a broader shift in education from memorisation-based learning to application-focused understanding. With information readily accessible, the need now is for conceptual clarity, problem-solving, and real-world application of knowledge—areas where AI-enabled multi-modal teaching frameworks can support educators effectively.
Outlook: Teacher-Led Adoption Will Shape Future of AI in Education
The report concludes that the future of AI in education will be defined by teacher-led adoption at scale, supported by easy-to-use, pedagogy-driven platforms that seamlessly integrate into everyday classroom practice. It positions the current phase as a decisive transition where AI in education has moved from possibility to practical implementation, with long-term impact depending on policy, design and deployment choices made now
