Gainful or Dark Gamification? Three Perspectives on Unlocking AI’s Potential for EdTech Research and Practice

The convergence of gamification and artificial intelligence (AI) in educational technology (EdTech) holds transformative potential for learning, yet the distinction between gainful and dark gamification remains undertheorized. Grounded in the mechanics, dynamics and aesthetics framework and synthesizing self-determination theory, flow theory and experiential learning theory with practitioner perspectives from EdTech stakeholders, this perspective article examines how AI can enable gainful gamification while mitigating its darker manifestations. Four AI affordances, namely accessibility, personalization, automation and interactivity, are identified and mapped across primary, secondary, higher education and professional learning segments. A triple-layered AI stack, comprising machine learning algorithms, predictive analytics triggers and real-time adaptive mechanics, is proposed as an enablement architecture anchored in the GAFCC (goals, access, feedback, challenge and collaboration) gamification design framework. The study positions AI as a dependable, though conditional, ally for responsible gamification, and sets out a research and practice agenda for EdTech stakeholders.