organizational-readiness
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- PaperEdArXiv (OSF Preprints)17 Jul 2026
Why AI Implementation Fails in Schools: The Human Readiness Gap
Dr NIRMALA KRISHNAN
A critical audit reveals that existing technology adoption models fail to explain recurring AI implementation failures in schools because they were built for bounded change episodes with fixed protocols, not for the open-ended, relational nature of AI adoption. Through case analysis of two failed large-scale initiatives at Los Angeles Unified School District, the paper identifies a 'Human Failure Chain' and a 'Human Readiness Gap' between typical pre-adoption assessments (funding, devices) and the organizational conditions needed for success. The paper proposes process-tracing studies to validate this causal model.
Original abstract
This paper conducts a critical audit of the theoretical models most often used to plan, justify, and explain artificial intelligence (AI) implementation in schools, and asks why none of them adequately explains the pattern of failure that recurs across technology generations. Individual-level acceptance theories (the Technology Acceptance Model; the Unified Theory of Acceptance and Use of Technology), diffusion theory, organization-level adoption frameworks (the Technology-Organization-Environment framework), sequential change-management models (Kotter's eight-step process), and implementation science (the Consolidated Framework for Implementation Research; the National Implementation Research Network's implementation-driver model) each illuminate part of the adoption process but were built for change episodes with properties AI implementation in schools does not share: a fixed protocol to be delivered with fidelity, a bounded start and end point, or a rational individual decision-maker as the unit of analysis. Using two documented, procurement-sound, well-resourced AI and technology initiatives at the same U.S. school district that nonetheless collapsed the Los Angeles Unified School District's 2013 one-to-one iPad programme and its 2024 “Ed” AI chatbot this paper traces a recurring causal sequence, termed here the Human Failure Chain, that existing models do not name. It argues that a Human Readiness Gap exists between what districts typically assess before AI adoption (funding, devices, vendor credentials, policy compliance) and the organizational and relational conditions that determine whether adoption succeeds. The paper does not claim to have tested this causal sequence statistically; it offers a critical synthesis and an illustrative case analysis and proposes the comparative and process-tracing studies that would be required to establish the Human Failure Chain as a validated causal model. Keywords: AI implementation failure; educational technology; implementation science; organizational readiness; technology adoption theory; school transformation