• CBSE has drafted a curriculum covering Classes 3 to 12 on AI and Computational Thinking (CT), which will be reviewed and finalized by NCERT.
• The curriculum emphasizes AI as a fundamental, universal skill, integrated into students' learning experience to develop skills like problem-solving, analytical thinking, creativity, and collaboration.
• The approach is gradual and inclusive, starting from foundational levels in Class 3 with progression across higher classes.
• The curriculum also focuses on the ethical application of AI, under the concept "AI for Public Good."
• Resource materials, teacher training modules through NISHTHA, and digital content are being prepared with the finalization expected by December 2025 to enable smooth implementation.
• The initiative includes extensive collaboration among CBSE, NCERT, KVS, NVS, IIT Madras, and other expert bodies, with the expert committee led by Prof. Karthik Raman of IIT Madras.
• Existing modules like “Skilling for AI Readiness” (SOAR) are already being implemented in Classes 6–8 as a precursor.

• Middle School (Classes 6-8): Focuses on "AI Inspire" modules to develop AI readiness, appreciation for its applications in daily life, and an understanding of its ethical considerations through engaging activities, games, and multi-sensorial learning. Key topics include:
  • Introduction to AI and its applications.
  • The three domains of AI: Data, Computer Vision, and Natural Language Processing (NLP).
  • AI Project Cycle framework (Problem Scoping, Data Acquisition, Data Exploration, Modelling, Evaluation).
  • Ethical considerations, AI bias, and AI access.
  • Basic programming skills using gamified platforms or tools like PictoBlox.

• Secondary Level (Classes 9-10, Subject Code 417): AI is available as an optional skill subject. The curriculum deepens the understanding of concepts and introduces practical skills:
  • Revisiting the AI Project Cycle, AI domains, and ethics.
  • Introduction to basic Python programming and its applications.
  • Data Science fundamentals (collection, analysis, visualization).
  • Computer Vision (image basics, processing, neural networks).
  • Natural Language Processing (text processing, chatbots, NLTK library).
  • Evaluation metrics for AI models.

• Senior Secondary Level (Classes 11-12, Subject Code 843): The curriculum offers a deeper, more technical and conceptual understanding, preparing students for future careers in the field. Key topics include:
  • Advanced Python programming with libraries like NumPy, Pandas, and Scikit-learn.
  • Machine Learning algorithms (supervised, unsupervised, deep learning, regression, clustering).
  • Mathematical foundations for AI (statistics, probability).
  • Data literacy and storytelling with data.
  • Generative AI concepts.
  • Development of a comprehensive capstone project applying learned skills to real-world problems. 

• Practical Focus: Emphasizes hands-on activities, projects (often linked to Sustainable Development Goals), and the use of AI tools/software (e.g., PictoBlox, Orange Data Mining, Lobe.ai).
• Industry Collaboration: Developed with support from partners like Intel and IBM to align with industry standards and provide resources for teacher training.
• Holistic Skills: Integrates "employability skills" such as communication, self-management, and entrepreneurship alongside subject-specific technical skills.
• Ethics and Bias: Strong focus on the ethical implications of AI, including bias, transparency, and data privacy.
• Future Planning: From the 2026-27 session, AI and computational thinking will be integrated into the curriculum starting from Class 3 to build foundational literacy from a younger age. 

Download Pdf