Artificial and emotional intelligence: two key forces for teachers' professional development in an era of uncertainty
TL;DR
It is concluded that AI-supported teacher development should be assessed not only by efficiency or personalisation, but by its capacity to expand, protect, and sustain human professional relationships.
Abstract
The expansion of artificial intelligence in education is moving faster than institutions' capacity to protect teacher wellbeing. Current debates often oscillate between technocentric optimism, which equates success with personalisation and scale, and pre-emptive rejection driven by fears of dehumanization. This conceptual and critical synthesis proposes a different evaluative criterion: AI may support teachers' socio-emotional professional development only when it functions as relational infrastructure rather than as a symbolic substitute for human accompaniment. The manuscript introduces relational densification as a criterion for examining whether AI-supported initiatives strengthen the professional relationships associated with teacher wellbeing, including trust, mentoring, peer support, collaboration, psychological safety, and reduced isolation. It also clarifies that these relationships may have downstream implications for students through classroom climate, pedagogical responsiveness, and socio-emotional support. The article distinguishes among different AI-mediated functions, including coordination systems, recommendation tools, analytics, conversational agents, and emotional AI, and examines their differentiated ethical and pedagogical risks. Particular attention is given to affective data governance, the political economy of educational AI, cultural and linguistic specificity, and critical AI literacy as a socio-emotional competence. The article concludes that AI-supported teacher development should be assessed not only by efficiency or personalisation, but by its capacity to expand, protect, and sustain human professional relationships.