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- PaperEdArXiv (OSF Preprints)17 Jul 2026
Human Readiness as the Missing Variable in AI Adoption in Education
Dr NIRMALA KRISHNAN
This paper positions the construct 'Human Readiness for AI in Education' against seven established technology-adoption and organizational-change models, arguing it is a distinct organization-level construct spanning five dimensions. It specifies the discriminant-validity tests the construct must pass to avoid being deemed redundant, emphasizing the need for empirical validation.
Original abstract
A theoretical contribution to organizational scholarship requires more than the introduction of a new label for a familiar phenomenon; it requires showing what factors an existing account omits, how those factors relate to one another, and why the resulting explanation improves on what came before (Whetten, 1989). This paper undertakes that task for Human Readiness for AI in Education, a construct introduced in a companion paper (Krishnan, 2026a) as the primary determinant of whether artificial intelligence (AI) implementation benefits a school. Rather than introducing new theory, this paper positions Human Readiness systematically against seven established accounts of technology adoption and organizational change the Technology Acceptance Model, the Unified Theory of Acceptance and Use of Technology, Diffusion of Innovations theory, Technological Pedagogical Content Knowledge, the Substitution-Augmentation-Modification-Redefinition model, the Concerns-Based Adoption Model, and Weiner's theory of organizational readiness for change comparing each on level of analysis, outcome variable, core constructs, and explanatory scope. It argues that Human Readiness is not a relabeling of any single existing construct, but a candidate organization-level construct whose five proposed dimensions span territory these accounts divide across separate literatures. Because the value of that claim rests entirely on demonstrating that Human Readiness is empirically distinct from its nearest neighbors, the paper closes by specifying, using established construct-validation methodology (Cronbach & Meehl, 1955; Campbell & Fiske, 1959; Fornell & Larcker, 1981; MacKenzie, Podsakoff, & Podsakoff, 2011), the discriminant-validity tests the construct must pass and the outcome under which it should be judged redundant and retired. Keywords: human readiness; construct validity; technology acceptance; organizational readiness for change; discriminant validity; theory development