Behavioral Intentions Toward Generative AI: A Symbiotic Human-AI Relationship

Generative AI is transforming digital marketing by reshaping how employees collaborate with technology in creative tasks. This study extends the Technology Readiness and Acceptance Model (TRAM) by integrating Attribution Theory of Motivation, the Theory of Reasoned Action (TRA), and Self-Determination Theory (SDT) to capture both cognitive and affective drivers of adoption. Survey data from 600 employees across 122 Egyptian digital marketing agencies were analyzed using structural equation modeling to test the expanded framework, with findings contextualized using the TCCM approach. Results indicate that the novelty of generative AI enhances perceived enjoyment, leading to greater engagement and reduced resistance. Unexpectedly, discomfort acted as a catalyst by encouraging exploration, whereas insecurity influenced perceived ease of use but not behavioral intention. Employees prioritized simplicity and efficiency, preferring seamless integration over complex interactivity. This study refines TRAM, challenging established views on discomfort, and advances cross-contextual perspectives on human–AI adoption in emerging markets.