Understanding artificial intelligence readiness among vocational and technical education lecturers for sustainable teaching in Nigeria

Artificial intelligence (AI) is changing educational practice and prompting lecturers to integrate emerging technologies while maintaining pedagogical quality, human agency and professional responsibility. Although research on teacher AI competence is expanding, limited qualitative evidence explains how vocational and technical education (VTE) lecturers in Nigeria understand AI readiness and conditions for sustainable AI supported teaching. This study explored AI readiness for sustainable teaching in Nigerian VTE. An interpretivist paradigm and qualitative descriptive design were adopted. Semi structured interviews were conducted with 35 purposively selected participants: 20 university VTE lecturers and 15 industry experts with relevant professional and digital or AI experience. Data were analysed thematically using Braun and Clarke’s approach. Findings indicated that participants understood AI readiness as a multidimensional professional capacity involving digital confidence, adaptability, critical thinking, ethical consciousness and pedagogical judgement. They identified inadequate training, limited infrastructure, insufficient institutional support, policy uncertainty and difficulties integrating AI with practical vocational learning as major barriers. Competencies required for sustainable AI supported teaching included technological, pedagogical, vocational content, ethical, critical evaluation, assessment and continuous professional learning. The study brings together educational and occupational perspectives to offer insight into AI readiness within Nigerian VTE. It proposes a tentative conceptual relationship linking lecturer qualities, enabling institutional conditions and integrated competencies with sustainable AI supported teaching. Here, sustainable teaching refers to continuing, appropriate and responsible AI use that supports learning while preserving practical vocational experiences. The findings support investment in professional development, institutional infrastructure and guidance, and stronger university industry collaboration. However, the study examined reported perspectives rather than directly assessing AI competence or measuring teaching sustainability over time.