Beyond AI Literacy and Adoption: AI-Integrative Capability and Responsible Implementation Conditions among Indian Educators

Abstract

Artificial intelligence (AI) is increasingly embedded in educational practice, yet educator preparedness extends beyond adoption, exposure or familiarity. Recent Responsible AI Readiness scholarship conceptualises preparedness as a multidimensional capability involving AI knowledge, professional judgement, ethical awareness, human agency and enabling institutional conditions. This study examines AI-integrative capability and responsible-implementation conditions using an anonymised secondary dataset of 208 educators from India. Quantitative analyses examined Content Knowledge (CK), Pedagogical Knowledge (PK), AI-Technological Knowledge (AI-TK), AI-Technological Content Knowledge (AI-TCK), AI-Technological Pedagogical Knowledge (AI-TPK) and AI-TPACK, complemented by documented qualitative thematic evidence on implementation conditions. Results showed that CK and PK were comparatively high (M = 3.458 and 3.399), whereas AI-specific domains were more moderate. AI-TPK showed the strongest association with AI-TPACK (ρ = .677, p < .001). AI familiarity was significantly associated with AI-TPACK (H(2) = 24.015, p < .001, η² ≈ .368), whereas prior AI exposure was not independently significant after adjustment. The HC3 robust regression model explained 63.0% of the variance in AI-TPACK (adjusted R² = .611), with AI-TK independently associated with AI-TPACK (B = 0.500, β ≈ .477, p < .001). Adding AI-TK increased explained variance by 12.7 percentage points (ΔR² = .127). Among educators with available qualitative responses (n = 104), positive orientations toward AI were reported by 80.8%, alongside professional-development gaps (66.3%), AI knowledge and infrastructure constraints (60.6% each) and ethical/privacy concerns (49.0%). Overall, the findings distinguish AI-integrative capability from adoption, familiarity and exposure while indicating that capability alone does not ensure responsible implementation. Responsible AI implementation requires the interaction of educator capability, professional judgement and enabling institutional conditions, supporting a multilevel understanding of Responsible AI Readiness among educators.