Colleges and K‑12 systems continue to scramble to integrate generative AI into teaching while guarding against academic dishonesty and harm to student development. Panels of educators and researchers urged a cautious, evidence‑driven approach—"go slow and steady"—and recommended local experimentation and faculty‑led research into impacts on learning. Higher ed institutions report widespread but uneven adoption: some faculty use AI for lesson planning and accessibility, others ban tools entirely amid legal and ethical concerns. Surveillance, assessment redesign, and faculty development were cited as immediate priorities. Institutions that succeed will pair clear policy, professional development, and curricular redesign to preserve learning goals while exploiting AI’s potential to personalize instruction and reduce administrative burden.