The End of Average: AI and Learner Variability, from Classroom to Career

What if we designed education and workforce systems around learner variability instead of retrofitting support after students fall behind? For decades, support for learning differences has been siloed, reactive, and often cut off after high school. AI challenges that model. As personalization and skills development scale, the real question is whether we will use AI to redesign systems for every learner or reinforce the inequities they were built on. This conversation brings together leaders across K12, research, and workforce innovation to explore what must change to ensure support does not end at graduation and opportunity truly extends from classroom to career.