Four-phase AI roadmap for new campus builders: Learn Basics (weeks 1-2), Apply to Content (weeks 3-4), Build Workflows (months 2-3), Teach Students (month 4+).
Build AI learning culture by sharing experiments openly, creating a dedicated discussion space, and running monthly AI challenges. Culture beats curriculum for lasting AI adoption.
Do a 30-day sprint using AI on one real task daily. By day 30, you'll have practical experience that creates genuine confidence — no course required.
Combat AI fatigue with a 90-day depth rule: pick two or three core tools, commit to mastering them, and ignore every new launch during that period. Depth beats breadth.
The most valuable AI skills for educators are prompt engineering, workflow design, content curation, and building AI-enhanced learning experiences. Focus on application, not technical depth.
You need to be two steps ahead of your students, not an expert. Build confidence through 30 days of daily AI use, then teach from your real experience and stories.
Keep an AI learning journal with prompts that worked, tasks completed, and lessons learned. Build a personal prompt library organized by task type for reuse.
Experiment with AI on internal tasks first, keep a testing folder, and never publish AI output without human review. This lets you move fast without risking your reputation.
Four non-negotiable AI skills for educators in 2026: prompt writing, output evaluation, workflow integration, and ethical judgement. Master these through daily practice, not formal study.
Informal AI learning through daily use on real tasks is more effective than formal courses for most educators. Start experimenting now — a course can fill gaps later if needed.