The rapid diffusion of generative artificial intelligence into everyday work has made employee acceptance, rather than technical capability alone, the decisive condition under which such tools translate into productivity. This paper develops a conceptual framework that extends the Technology Acceptance Model to the use of generative artificial intelligence by Generation Z employees working in public and private organisations in Bangkok. The paper is conceptual: it synthesises the acceptance literature, the contemporary evidence on artificial intelligence in organisations, and the performance-appraisal tradition in human resource management, and it reports no empirical data. Three acceptance beliefs drawn from the model, namely perceived usefulness, perceived ease of use and attitude toward using, are defined, decomposed into observed variables, and linked to employee performance conceptualised through the dimensions of accuracy and quality, quantity of output, time, quality of delivered work and overall efficiency. Three principal propositions relate each acceptance belief positively to employee performance, and two auxiliary propositions reproduce the internal structure of the acceptance model for future extension. The paper further proposes a research design in which a five-point Likert questionnaire, validated through item-objective congruence assessment and a pilot test of reliability, would be administered to a sample of Generation Z employees in Bangkok and analysed with multiple linear regression to derive a predictive equation for employee performance. The expected contribution is a generation-specific and context-specific acceptance model, together with a validated instrument and a testable research agenda for human capital management in Thailand.
Keywords: Technology Acceptance Model, Generative artificial intelligence, Generation Z employees, Employee performance, Conceptual framework.