AI as the Hidden Curriculum: How Learning is happening through AI Without being Taught?

Penta Minds

Vignesh, Prakash, Parisutham Institute of Technology and Science; Muskan, Joshi, Guru Gobind Singh Indraprastha University; Priya, Saxena, Guru Gobind Singh Indraprastha University; Shivani, Guru Gobind Singh Indraprastha University; Aditi, Gargi College

Research (anything related to the use of AI in a research context)

AI as the Hidden Curriculum: How Learning is happening through AI Without being Taught? — A ground-level research study exploring how students and faculty of higher education institutions across diverse tiers in India are informally adopting, using, and learning through AI tools outside of any structured curriculum or formal instruction.

AI is entering higher education not through policy or pedagogy, but through peer exchange, experimentation, and ambient digital exposure — yet no systematic evidence exists of how this is actually happening, especially across diverse institution tiers in countries like India. This use case matters because the informal AI learning gap is also an equity gap: students with better resources extract far greater value from AI, amplifying existing inequalities. Making this hidden curriculum visible is essential for designing inclusive, evidence-based AI governance frameworks that reflect ground realities rather than assumptions.

Our team is motivated by the lived experience of being students in a system where AI use is widespread but unacknowledged — neither taught responsibly nor governed thoughtfully. We aim to document the informal pathways through which AI competence is built, identify the tensions between efficiency and deep learning, and co-create practical tools (an AI Literacy Toolkit and Responsible Use Guidelines) that serve students at all institution types. Our learning objectives include developing research and fieldwork skills, contributing student voices to global AI governance discourse through GPAI, and producing policy-relevant evidence that bridges the gap between how AI is used on the ground and how it is discussed at the policy level.