Myths vs. Reality: What AI in Education Actually Does

AI in education is surrounded by hype, fear, and misunderstanding. These misconceptions often slow innovation, confuse decision-makers, and create unnecessary resistance among faculty and students. This session cuts through the noise with a clear, evidence-based look at what AI actually does in modern learning environments. We’ll unpack the most common myths—from “AI replaces teachers” to “AI encourages cheating” to “AI collects too much data”—and contrast them with real-world practices from classrooms, student services, and academic technology teams. Participants will see how AI supports, rather than replaces, human expertise by automating repetitive tasks, improving feedback loops, identifying at-risk learners earlier, and enabling more personalized learning pathways. Using examples from diverse institutional contexts, we’ll explore how educators, students, and administrators experience AI differently, and why understanding these perspectives is essential for successful adoption. Attendees will leave with a grounded understanding of AI’s capabilities, limitations, and ethical considerations, along with practical strategies for communicating about AI with stakeholders who may be skeptical or overwhelmed. This session is designed for anyone navigating AI adoption in higher education: faculty; instructional designers; IT leaders; student success teams; and administrators seeking clarity, confidence, and actionable insights.