In a paper describing the results of randomized controlled trials led by the Stanford SCALE Initiative, 355 students in grades 1 to 5 in two school districts were assigned either to use an AI literacy tutor independently or to use the same platform with support from a human tutor. In both, the goal was to improve reading achievement.
But there are other promising approaches that flip the model: rather than asking AI to replace human tutors, AI can help them become more effective. In one large randomized trial, an AI tool that provided real-time instructional suggestions to human tutors improved student mastery, with the largest gains occurring among less experienced tutors. This suggests a different vision for the future of personalized learning, one where AI and human support work together to meet the needs of tutors and individual students. The right mix will vary depending on the subject and grade level. Assuming stronger engagement, some students may thrive with primarily AI-supported learning. Others may benefit from AI tutoring paired with periodic human encouragement and accountability. Still others will require sustained relationships with human tutors, teachers or mentors.