The Center for Reinventing Public Education (CRPE) has a new report out, titled “AI is Evolving, but Teacher Prep is Lagging: A First Look at Teacher Preparation Program Responses to AI.” This report, which you can read in its entirety here, raises important questions about how we’re preparing future educators for a changing landscape. Their findings highlight a disconnect: while education schools acknowledge AI’s growing presence in classrooms, most are responding with piecemeal solutions rather than thoughtful systemic approaches.

The data is telling: most teacher prep programs are still fixated on surface-level concerns like preventing ChatGPT plagiarism, while missing the bigger picture of AI’s transformative potential. Even more concerning, faculty indifference and resistance threaten to create a generation of teachers unprepared for tomorrow’s classrooms.

What stands out in CRPE’s findings is the gap between institutional awareness and actual readiness for change. Most teacher prep programs lack the capacity for meaningful adaptation, and faculty engagement varies widely. This isn’t surprising – systemic change is hard, and rushing to embrace any new technology without careful consideration would be unwise.

They do highlight, in the report, several examples of colleges that are doing it right. I was proud to see that the Mary Lou Fulton Teachers College was featured in the report – and specifically the work being done by the AI in Education, Learning Futures Collaborative. I have written about this elsewhere (“GenAI in Education: MLFTC’s Systems Approach“), but it was good to see it represented in this report as well.

Concluding thought: While CRPE’s report on teacher preparation and AI offers valuable insights, its opening claim that “AI has transformed the education landscape” deserves closer scrutiny. The reality is more nuanced – while AI tools are increasingly available in educational settings, their actual impact on teaching and learning practices remains largely unstudied and unclear. As researchers and scholars, we need to maintain a critical stance, carefully examining both the potential and limitations of AI in education rather than assuming transformation has already occurred. Keeping this in mind, I am glad to say that at MLFTC’s Learning Futures Collaborative, we’re taking a deliberately measured approach – one that critically reflects on AI’s role in education, excited by the opportunities, measured about the claims we make and more importantly sensitive to negative impacts to our learners and the world at large.