{"resourceId":"campos-singleton-ai-diffusion-gaps-2026","versions":[{"version":"external-eb1ea8c9a9f751f8830643e6a926de98446b6f9cbd3752bd9b89319d7b61139e","resource":{"id":"campos-singleton-ai-diffusion-gaps-2026","title":"National principal survey: AI use outruns policy/training, with disadvantage and sector integration gaps","organization":"Christopher Campos (University of Chicago) and John Singleton (University of Rochester)","sector":"Academic economics / education research","geography":"United States (national sample of about 1,200 traditional public, charter, and private K-12 schools)","publishedAt":"June 2026 (working paper; Booth Review coverage 11 Sep 2026)","publicationDate":"2026-06-01","eventDate":null,"sourceName":"Author PDF (cqcampos.com) / NBER w35347","sourceLabel":"Academic working paper PDF (national principal survey)","sourceUrl":"https://www.cqcampos.com/assets/pdf/ai_integration_paper.pdf","evidenceClass":"academic-research","outcomeClass":"cautionary","topics":["governance-procurement","accessibility-workforce","operating-model","infrastructure"],"finding":"Campos and Singleton’s June 2026 working paper reports an original national survey of K-12 principals (fielded Dec 2025 to Feb 2026) measuring institutional AI integration. Teacher AI use spread rapidly while scaffolding lagged: 58% of principals report no written generative-AI policy; 76% report no AI-tutoring license/contract; 67% did not use ESSER funds for AI. An integration index combining policy, training, student-use guidance, leadership, and tools shows schools serving more disadvantaged students score 0.07 to 0.11 SD lower per SD of disadvantage, and charter/private schools score 0.23 to 0.44 SD lower than traditional public schools. District size accounts for roughly one-third of the public-school disadvantage gap; principal enthusiasm and budgets raise integration levels but do little to close gaps. Why now: after 2026-09-23 coverage of NYC/LA pauses reverberating nationwide, this evidence reframes pause-versus-enablement as a system-capacity equity problem, not merely a values debate.","sledRelevance":"Gives SLED buyers an equity lens for GenAI: buying tools without district-scale implementation capacity can widen integration gaps for disadvantaged and non-district schools. Supports engagements that build shared policy, PD, and vendor infrastructure rather than school-by-school experimentation.","evidence":"Original survey with school-tied invitations merged to federal demographic data and reweighted; randomized participation incentives used to probe selection; correlational gaps with controls; not an achievement RCT.","architectureImplications":"Favor district- or consortium-level approved platforms, shared DPAs, and common PD pipelines over fragmented school-site consumer accounts—especially where district scale is the scarce resource.","governanceImplications":"Written policies, student-use guidance, and training must be treated as core integration investments; interventions that only nudge principals or free discretionary spend are unlikely to close disadvantage gaps.","securityPrivacyImplications":"Paper measures institutional scaffolding, not vendor security posture; shallow integration implies many schools may be using tools without contracts—raising privacy/procurement risk.","caveats":"Principal self-report; integration is not learning outcomes; June 2026 vintage requires why-now framing; charter/private lag may partly reflect different governance models.","streamIds":["k12"],"roles":{"sales":"Sales framing: lead with integration equity, not access. This survey shows AI reached most schools while policies and tutoring contracts did not, with lower integration where students are more disadvantaged and in charter/private settings. Propose a district-scale capacity engagement—shared policy, PD, and contracted tools—without claiming closing the index gap will raise test scores (the paper does not show that).","engineering":"Engineering framing: architect for district-wide tenants, roster-aware auth, and contracted tutoring endpoints rather than unmanaged consumer AI. Prerequisites include written policy and scale-appropriate vendor agreements. Constraints: survey cannot dictate a single product stack. Proof of value: movement on policy/training coverage and contracted tool share across high-disadvantage schools—not click counts alone.","delivery":"Delivery framing: build a district AI integration program (policy, PD, approved tools, student guidance) with explicit equity targeting. Ownership sits with the superintendent cabinet; regional/ESA support may substitute where district scale is thin. Acceptance criteria: written policy live, training reach targets in high-need schools, and tutoring/tools under contract where used. Risks include deepening shallow adoption and leaving charters/privates without shared infrastructure."},"roleDetails":{"sales":{"customerProblem":"AI tools spread school-by-school while disadvantaged and non-district schools lag on policy, training, and contracted supports.","stakeholders":["State chiefs","District superintendents","Charter/private leaders","ESA/co-op directors","Equity officers"],"discoveryQuestions":["Do you have a written GenAI policy today?","What share of schools have AI tutoring under contract?","How does integration differ by FRPL or neighborhood income?","What shared services exist for small/charter schools?"],"valueHypothesis":"A system-level integration program can raise scaffolding where school-level enthusiasm cannot close gaps.","potentialEngagement":"6 to 8 week AI integration equity diagnostic: index baseline, gap analysis, shared-service options, and board-ready roadmap.","unsupportedClaims":["That closing the integration index raises achievement","Guaranteed equity gains from any single vendor","That small districts can match large-district capacity without shared services"]},"engineering":{"fit":"District/consortium platforms with shared identity, logging, and contracted AI services; poor fit for unmanaged consumer tools.","architectureIntegration":"Central IdP, approved-model gateway, optional tutoring SIS integrations, and school-site configuration baselines.","prerequisites":["Written GenAI policy","Procurement vehicle for DPAs","PD delivery channel","Equity-targeted rollout list"],"constraints":["Survey is correlational","Sector governance differences","Rapid product change"],"security":"Prefer contracted processing with no-training clauses; inventory and disable unmanaged consumer AI on managed devices where policy requires.","proofOfValue":["Policy coverage by school type","Training completion in high-disadvantage schools","Share of AI use under contract"]},"delivery":{"work":"Draft/adopt policy, stand up PD, negotiate contracted tools, and publish student-use guidance with equity monitoring.","dependencies":["Legal/privacy","Finance/procurement","ESA or co-op partners for small systems","School leader communications"],"ownership":"Superintendent/cabinet owns integration program; equity office monitors gap metrics.","skillsAdoption":"Train principals and teacher champions together so adoption is not left to individual tinkering.","governanceCheckpoints":["Policy adoption","Contract execution","PD wave completion","Quarterly gap dashboard"],"acceptanceCriteria":["Written policy in force","Documented training reach in target schools","AI tutoring only via approved contracts where offered"],"risks":["Shallow adoption labeled as success","Charter/private exclusion","Scale bottlenecks without shared services"]}},"retrievedAt":"2026-09-25T03:10:40Z","enrichedAt":"2026-09-25T03:17:50Z","enrichmentBasis":"retrieved source","accessibilityWorkforceImplications":"Lower integration in higher-disadvantage schools risks unequal access to guided AI supports and unequal exposure to unguided risks; workforce PD capacity is part of the gap.","procurementImplications":"Prefer cooperative purchasing and shared DPAs that extend large-district capacity to smaller and charter systems; budget for training/policy as complements to licenses.","operatingModelImplications":"Shift from bottom-up teacher experimentation to system operating models where policy, PD, and contracted tools co-evolve.","sourceVerification":{"openedUrl":"https://www.cqcampos.com/assets/pdf/ai_integration_paper.pdf","referenceExcerpt":"most principals (58%) report that a written policy governing generative AI is not currently in place","promptVersion":"sled-research-v4.0","model":null,"basis":"agent-reported inspection"}}}]}