Education at a crossroads: will AI fix learning or break it?

Purpose This paper explores the implications of artificial intelligence (AI) for the future of education. It critically examines how AI is not simply a support tool but a transformative force that is capable of redefining educational models, teaching roles, curriculum design and student engagement. The study aims to offer a roadmap for educational institutions to harness AI’s potential while safeguarding against its risks. Design/methodology/approach The paper adopts a comprehensive conceptual and analytical approach, synthesizing current academic research, policy recommendations and real-world examples from pioneering institutions globally. It includes a critical review of literature, case studies of early adopters and theoretical frameworks on cognitive science, educational transformation and AI ethics. The analysis is structured thematically to cover curriculum redesign, faculty development, infrastructure needs, policy considerations, ethical governance and assessment innovations. Findings The study finds that successful AI integration in education depends on a phased and prioritized implementation strategy. Early focus areas include empowering educators, building equitable digital infrastructure and adopting adaptive governance models. The research highlights that AI’s greatest value lies in amplifying human capacities such as critical thinking, creativity, ethical reasoning and emotional intelligence. However, it warns that without deliberate policy and institutional intervention, AI may exacerbate existing inequalities and erode psychological safety in learning environments. Practical implications The study provides guidance for multiple stakeholders in the educational ecosystem. For institutional leaders, it offers a phased implementation roadmap that prioritizes faculty development and infrastructure before curriculum redesign, reducing implementation risks and resource waste. Educators can immediately apply the framework by automating routine tasks and experimenting with AI-enhanced assessments that evaluate critical thinking rather than memorization. Policymakers can use the findings to develop targeted funding programs for under-resourced institutions and update accreditation standards to recognize AI-enhanced competency-based learning. The research also guides technology developers in creating educationally aligned AI tools that enhance rather than replace human connection in learning. Most critically, the study provides specific metrics for tracking AI integration success beyond traditional test scores, including measures of creative problem-solving, ethical reasoning and human-AI collaboration skills. These practical applications enable institutions to navigate AI integration while avoiding common pitfalls of hasty implementation or widening educational inequities. Originality/value This paper contributes original value by reframing AI as a catalyst for elevating human-centered learning. It provides actionable guidance for educators, policymakers and technologists to collaboratively design an education system that prepares learners for an AI-driven world. The work stands out by addressing both the visionary possibilities and the pragmatic challenges of AI adoption, including resource disparities, faculty readiness, ethical implications and the need for continuous improvement and measurable outcomes.