The integration of artificial intelligence into learning represents a paradigmatic transformation in contemporary education, offering unprecedented scale personalisation whilst also posing ethical and equity challenges. This article presents a critical and practical perspective on the potential and limitations of educational technologies and artificial intelligence to support academic success, analysing collaborative digital tools, adaptive systems and intelligent tutors, artificial intelligence as support for self-regulated learning (Zimmerman model) and systemic risks such as privacy, algorithmic biases and the global digital divide. Through systematic review of recent literature (Scopus/ERIC/WoS databases), empirical evidence is mapped regarding gains in motivation, retention and autonomy, balanced by technical and social limitations. The chapter’s flow ranges from basic platforms to advanced applications, critical challenges, and sustainable, integrative proposals. It is concluded that artificial intelligence potentiates self-regulation cycles but requires ethical frameworks for equitable implementation, and proposes practical recommendations for educators, institutions and public policies towards Education 4.0. This analysis contributes to the academic debate on responsible artificial intelligence and promotes autonomous and inclusive learning on a global scale.
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