Standards Into Systems: AI as Your Professional Learning Plan Design Partner

The Design Challenge

Developing comprehensive professional learning plans that truly align with Learning Forward’s Standards requires deep thinking, stakeholder input, and careful evidence mapping. The structural work alone—creating frameworks, organizing documents, aligning to research—often consumes weeks that could be spent on strategic dialogue and contextual refinement.

AI as Accelerator, Not Automator

This think tank demonstrates how Shanghai American School developed an AI-assisted Plan Generator to accelerate the foundational architecture of professional learning plans. Rather than replacing the critical thinking required, AI handles the time-intensive structural tasks: organizing frameworks based on Killion’s Assessing Impact, creating evidence collection templates aligned to Guskey’s levels, and drafting initial content grounded in research.

What Participants Experience

Live demonstration of AI generating the scaffolding for a comprehensive plan
Two hands-on protocols showing how AI amplifies human thinking rather than replacing it
Bias-checking practices that ensure AI outputs serve your context, not vice versa
Strategic discussions about where acceleration helps versus where human expertise is irreplaceable

The Real Impact

What typically takes 40-60 hours of structural work can be compressed to 4-6 hours of focused refinement. This isn’t about speed for speed’s sake—it’s about freeing leaders to invest more time in what matters: engaging stakeholders, adapting to local context, and building buy-in for meaningful change.

Participants Leave With:

  • Framework templates and implementation guides
  • Bias-checking protocols for AI outputs
  • Clear understanding of where AI accelerates versus where humans lead

Learning Outcomes:

  • Analyze the Architecture – Examine how AI tools can operationalize Learning Forward’s Standards and Killion’s design principles, identifying which structural tasks benefit from acceleration versus which require human expertise
  • Apply AI-Human Protocols – Practice two collaborative workflows (Needs Canvas and Logic Model Builder) that demonstrate how AI amplifies rather than replaces professional judgment in plan development
  • Evaluate AI Outputs – Use a six-point bias and relevance audit to critically assess AI-generated content, ensuring outputs align with local context and equity considerations
  • Navigate Ethical Considerations – Articulate safeguards for data privacy, voice equity, and transparent communication about AI’s role in the planning process

Facilitated By

Scott Williams

Associate Director of Educational Programs, Shanghai American School

Scott Williams is Associate Director of Educational Programs at Shanghai American School (SAS), where he empowers learning, enables collaboration, and bridges ideas across diverse educational contexts. With 23 years of experience spanning four countries, Scott architects comprehensive systems that integrate curriculum design, professional learning, and coaching to translate research into measurable classroom impact.
At SAS, Scott leads strategic development of curriculum initiatives and the Coaching Program, working with 15 instructional and technology coaches across two campuses. His approach, informed by emerging AI applications and evidence-based practices, has transformed coaching from helpful conversations to evidence-rich growth cycles that elevate both teaching practice and student learning.
A skilled facilitator with deep expertise in collaborative team development, Scott leverages coaching foundations and research-based facilitation strategies to navigate complexity and build collective capacity. His systems innovations address the adaptive challenges facing modern education—from aligning curriculum frameworks and professional development systems to implementing knowledge management tools under the “One School” vision. Through this work, he creates sustainable structures where educators thrive and students succeed.