District AI implementation needs living guidance and teacher-led redesign
Claim
Effective district AI implementation requires guidance that keeps evolving and curriculum redesign led by teachers, not one-time compliance or tool adoption.
Stance
Supported by the source article as an implementation argument.
Evidence
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The Long Game: Why AI Implementation Is a 3–5 Year Rebuild argues that district policy deadlines should become opportunities for comprehensive guidance rather than mere compliance documents.
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Potkalitsky criticizes reactive approaches where committees and policy frameworks form without clear instructional guidance.
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He argues for teacher-led curriculum rebuilding and describes teachers as the superpower during AI disruption.
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Finding the Right Questions: Why AI Implementation Must Start with Educational Values supports this claim through its discussion of highly relevant for K-12 districts, AI committees, policy design, professional development, tool evaluation, academic integrity, and instructional leadership.
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Beyond Tool Proficiency: Reflections on AI Integration Models supports this claim through its discussion of strong relevance for K-12 AI policy, district implementation, teacher professional learning, infrastructure planning, equity, and AI literacy curriculum.
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Beyond the AI Inflection Point: Central Schools and the Innovation Lab Experiment supports this claim through its discussion of AI literacy, assessment, implementation, or learning design in context.
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Thinking With AI supports this claim through its discussion of AI literacy, assessment, implementation, or learning design in context.
Practical implication
District AI plans should fund and protect teacher collaboration time, cross-disciplinary curriculum rebuilding, and living guidance processes rather than relying only on central-office policy, vendor training, or one-off AI professional development days.