The future of learning is personalized: Why investors cannot afford to ignore AI in education

Investments in comprehensive educational resources are vital as their societal value continues to grow. Artificial Intelligence applications in education (EdTech) are increasingly capable of tailoring education to the unique nuances of each learner’s behavior. Investment in EdTech is driven by the expansion of individualized learning approaches that revolve around the prediction and prescription paradigm of learner behavior. To illustrate the timing of this paradigm shift, this paper addresses the extent to which AI prediction and prescription learning approaches are tailored to educational needs. The core argument revolves around the centrality of adaptive learning systems, automated content delivery, predictive analytics, and intelligent tutoring systems. To reflect the value of investment, each stakeholder is given a unique value proposition to consider. In this, improved educational institutional outcomes and student engagement are secondary to the low cost and ease of intervention, predicated on the assumption that education is provided to learners in the country of origin and abroad. Ethical issues of the evolution such as data breaches, algorithmic bias, and even the replacement of teachers in the 4th industrial revolution are some of the issues this paper sheds light upon. Investors who focus on the realization of sustainable and scalable ventures are hardly able to ignore these issues. The paper corroborates the mainstream opinion which states that the growing technological infrastructure, market demand, and real-world validation have made AI in education an asset of unparalleled significance. Keywords: Artificial Intelligence, Personalized Learning, EdTech, Investment, Adaptive Learning, Learning Analytics, Ethics in AI, Educational Technology.