Abstract
This conceptual paper examines generative AI use as a sequence of judgments rather than a one-time adoption decision. TAM is used to describe how users approach the technology before or during early use, whereas ECM is used to interpret evaluation after experience has accumulated. The analysis distinguishes expectations formed before substantial use from judgments made after users complete real tasks. At the earlier stage, perceived usefulness, ease of use, risk, AI literacy, and calibrated trust are relevant to adoption. Later, users reassess the technology in light of whether expectations were met, how useful the tool proved in practice, how satisfied they were, and how much checking or correction was required. Continued use is therefore treated alongside temporary discontinuance and subsequent return. Task-technology fit, AI fatigue, and cognitive offloading are discussed as conditions that may change these transitions. The framework remains conceptual and should be tested with longitudinal observations and behavioral records.
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