A governance-first approach to district AI transformation
Prepared by
Dr. William Gideon — Program Director
Dr. Marie Martin — Research & Curriculum Lead
Dr. Charles Martin — Technology & Innovation Lead
Every design decision in this program emerges from a singular conviction: board members are accomplished professionals who deserve learning experiences as sophisticated as the governance decisions they must make.
The IMDP is grounded in IDEO Human-Centered Design augmented by Costanza-Chock's Design Justice principles, ensuring that the communities most affected by AI governance decisions — students, families, classified staff, communities of color — shape the frameworks, not merely comment on them after the fact.
Paulo Freire's anti-banking pedagogy is the ethical backbone: board members are not empty vessels to be filled with AI knowledge. They arrive with decades of professional expertise, community knowledge, and governance intuition. The program activates and channels that expertise toward AI governance, rather than replacing it with technocratic content.
Check for learning at the beginning, not the end. Governance scenarios reveal what board members already know — and what they don't know they don't know — before any content is delivered. Expertise is honored, not bypassed.
Board members receive governance toolkits, not tests. Policy templates, evaluation rubrics, budget frameworks, and community engagement protocols they can use during actual board work. The toolkit is the assessment.
The LEVER Framework (Leverage, Environment, Velocity, Execution, Repetition) serves as both what board members learn about and how the training itself is designed. The medium is the message.
"Nothing about us without us" is not a slogan — it is the design methodology. Community voice, equity analysis, and lived experience are centered in every governance framework the program produces.
Four facilitated sessions — two full-day retreats and two half-day working sessions — spaced 3–4 weeks apart, with between-session application activities that connect training to real governance work. Total participant investment: approximately 30–35 hours across 4 months.
Board members build foundational AI literacy through hands-on exploration, examine the 7 Disruptive Technologies landscape, immerse in WEF labor market data, and analyze organizational AI adoption evidence from OpenAI, Anthropic, Microsoft, and Google DeepMind. Establishes the convergence understanding (Kurzweil + Chace + Anyon) that grounds all subsequent governance work.
7 Enabling Learning Objectives I Do — Facilitator LedDeep examination of the 4-Level Digital Divide (Access, Skills, Outcomes, and TRPEC's proposed 4th level: Agency), data privacy and legal frameworks (FERPA, COPPA, California law), equity audit methodologies, JD Mapping for workforce impact analysis, and community voice integration through Dr. Cortes' Bridge-Building Framework.
7 Enabling Learning Objectives We Do — Co-FacilitatedBoard members produce a draft board-ready AI governance policy and community engagement plan, applying the Berkeley DGRI governance framework, the AI Engineering Playbook's champion model adapted for governance, and Design Justice facilitation principles. Output is a policy document ready for public comment period.
6 Enabling Learning Objectives You Do Together — Board LedBoard members finalize an AI vision statement, develop a 3-year budget framework with Engineering Playbook phase mapping, design governance dashboards and quarterly review rhythms aligned to Kotter's 8-step change model, and establish the LEVER organizational operating system for continuous AI governance.
7 Enabling Learning Objectives You Do — Board IndependentSix instructional methods designed specifically for accomplished governance professionals. Every method produces governance output — the learning and the deliverable are one and the same.
Governance scenarios that reveal what board members already know — and what they don't know they don't know. Inspired by the Top Gun metaphor: elite professionals confronting novel tactical environments. Expert learners are identified at the beginning and invited to contribute as co-facilitators, honoring expertise rather than discovering gaps only after content delivery.
Provocations, not lectures. Real case studies from district AI adoption, WEF labor market data, community voices, and convergence predictions (Kurzweil, Chace, Anyon) create productive disequilibrium. Board members encounter information that challenges assumptions and generates authentic inquiry — the kind of questioning that leads to informed governance.
Hands-on exploration with governance guiding questions at every station. The question is "What should we govern?" — not "How do we use this tool." Five stations including the 7 Disruptive Technologies exploration ensure board members develop governance capacity for continuous technological disruption, not a single technology adoption event.
Board members produce real governance outputs: policies, SWOT analyses, vision statements, budget frameworks, community engagement plans, superintendent evaluation criteria. The output is the learning. Nothing is hypothetical — every deliverable is designed for actual board adoption.
Pocket-sized governance reference cards, digital resources on the TRPEC Learning Portal, policy templates, evaluation rubrics, and facilitation guides. Board members build their governance toolkit throughout the program. The toolkit is the assessment — if board members are using the tools in governance, the learning has transferred.
I Do (facilitator models governance thinking), We Do (collaborative governance work with facilitated support), You Do (independent governance practice with coaching). Applied specifically to governance capacity, not generic instruction — each module shifts the locus of control closer to board independence.
Every module is anchored in primary research — organizational evidence, labor market data, convergence literature, and governance frameworks that give board members the evidentiary foundation for consequential decisions.
| Research Domain | Key Sources | Governance Application |
|---|---|---|
| Organizational Evidence | OpenAI (8x message growth), Anthropic (28% to 59% daily AI; "managers of AI agents"), Microsoft (80% abandonment, 201–301 gap), Google DeepMind (research-first approach) | Understanding why organizational readiness — not model performance — is the bottleneck for AI adoption at district scale |
| WEF Labor Market Data | 170M new jobs, 92M displaced, 39% skills transforming, $7T GDP impact, 43% of OECD teachers never studied ICT | Evidence base for community communication and urgency framework for board action |
| Convergence Literature | Kurzweil (AGI 2029), Chace (Economic Singularity), Anyon (Radical Possibilities — education reproduces hierarchy without intervention) | Urgency narrative connecting technology acceleration, economic disruption, and educational equity into a single governance imperative |
| Governance Frameworks | Berkeley DGRI (Diagnose, Governance, Redesign, Reuse, Iterate), AI Engineering Playbook (4-phase), Kotter 8-Step Change, 4-Level Digital Divide, Dr. Cortes Bridge-Building | Repeatable governance processes for technology decisions that transfer across all disruptive technologies |
| 7 Disruptive Technologies | AI, Quantum Computing, Blockchain/Web3, Biotechnology/CRISPR, Edge Computing, Autonomous Systems, Photonic/Neuromorphic Computing | Preparing boards for continuous technological disruption rather than a single AI adoption event |
| TRPEC Original Research | Dr. Martin's "The Fourth Industrial Superintendent" (USC, 2026), LEVER Framework, Dr. Gideon's district leadership experience, Dr. Martin's documented AI adoption journey (914 interactions) | Proprietary frameworks and authentic practitioner evidence that no competitor can replicate |
"Only 30% of AI pilots scale to full organizational adoption." — Berkeley Digital Government Research Institute. This is why governance must precede implementation. Tool-level training without governance infrastructure is a waste of resources.
Board members are accomplished professionals. They do not need tests — they need governance outcomes. Assessment in this program is measured by what boards do, not what individuals score.
The program employs the Kirkpatrick 4-Level Model extended with a TRPEC 5th Level: Equity Impact. Traditional assessments are replaced entirely by governance output: policies adopted, budgets approved, superintendent evaluations updated, community engagement conducted, and governance rhythms established.
The LEVER self-assessment serves as both diagnostic and growth tool — board members complete it in Module 1 (baseline) and revisit it in Module 4 (growth). The 66-day governance rhythm check confirms that governance habits have reached automaticity, per Lally et al. (2010).
Session evaluations, facilitator observations, real-time polling via TRPEC Governance Platform
LEVER self-assessment growth, governance output quality, toolkit completion and personalization
AI governance on board agendas, superintendent evaluation criteria updated, 66-day rhythm check
AI policy adopted, budget aligned, community town hall conducted, governance dashboard operational
4-Level Digital Divide addressed in policy, community voice documented in governance record, equity audit conducted
Board governance involves the most sensitive data a district possesses: budget deliberations, personnel discussions, strategic plans, equity audits, vendor contracts, and community engagement records. No third-party platform should touch this data.
No district data touches any third-party platform. All collaboration, polling, whiteboarding, policy drafting, and governance work occurs exclusively within TRPEC's proprietary secure infrastructure. District data isolation ensures no cross-district access is possible.
Real-time polling, collaboration, whiteboarding, and policy drafting during facilitated sessions. Each district receives a unique access code. No data is shared across districts. Supports Brown Act-compliant governance activities with full audit trails.
All modules, self-study resources, toolkits, videos, and reference materials in a single secure environment. District-specific credentials ensure only authorized participants access their content. Between-session resources and reflection prompts are delivered here.
Secure dashboard displaying AI readiness metrics, governance rhythm tracking, technology inventory, achievement data, and equity indicators. Each district receives a unique code and isolated data environment. Supports quarterly governance review cycles.
Data Retention Policy: District data is retained for the duration of the engagement plus 12 months. At that point, the district may export all data or request permanent deletion. No district data is used for any purpose beyond the specific engagement.
Phase 1 (this program) builds governance capacity. The full 5-year model transforms the entire district — from boardroom to classroom — through a systematic progression aligned to both the AI Engineering Playbook and Kotter's change management research.
Governance capacity building through the Board Member AI Leadership Training (this IMDP), followed by superintendent strategic planning sessions and cabinet AI leadership development. Establishes the governance foundation, urgency coalition, and strategic vision that authorize all subsequent transformation.
Technology infrastructure assessment and buildout, principal and teacher leader development, union partnership establishment, and community engagement deepening. The governance rhythms established in Year 1 begin to produce systematic AI adoption decisions grounded in equity and community voice.
The critical identity shift: teachers transform from content deliverers to learning designers who orchestrate AI-enhanced learning experiences. This is the year that reaches the classroom — and it succeeds because three years of governance, infrastructure, and leadership have created the conditions for authentic transformation rather than tool adoption.
District-wide scaling of successful AI integration practices, sustainability planning, cross-department coordination, and advanced governance maturity. The LEVER organizational operating system is fully embedded, and governance rhythms have reached automaticity across all levels of district leadership.
Anchoring transformation in district culture, establishing mentorship and knowledge transfer systems for board turnover, creating district-to-district learning networks, and positioning the district as a regional leader in AI-integrated education governance. The 7 Disruptive Technologies framework ensures readiness for whatever comes next.
Three doctoral-level education leaders with complementary expertise in district governance, research methodology, and educational technology — combining practitioner credibility with scholarly rigor.
DSAG, Ed.D. in Educational Leadership, University of California. Former Interim Superintendent with deep expertise in board-superintendent dynamics, California education policy, district governance, and organizational change at the district level. Leads program design and facilitation.
Ed.D. in Educational Leadership, University of Southern California. Author of "The Fourth Industrial Superintendent" — a 170-page doctoral study of educational leadership in the age of artificial intelligence. Leads research integration, curriculum development, and equity analysis.
Ed.D. in Educational Technology, University of Florida. Documented AI adoption practitioner with 914 interactions across 18+ platforms. Leads technology demonstrations, platform development, and the authentic practitioner perspective that grounds theoretical frameworks in lived experience.
The Board Member AI Leadership Training meets all applicable legal, accessibility, and regulatory requirements for professional development with elected governance officials.
Full compliance with California open meeting law requirements when board quorum is present
All data handling and platform design aligned with federal student privacy protections
All digital materials meet Web Content Accessibility Guidelines for inclusive access
TRPEC owns training materials; district owns all governance outputs produced during the program
The undersigned acknowledge they have reviewed this Instructional Media Design Package and authorize program development based on its contents.