This systematic literature review investigates the influence of technological knowledge on user acceptance, intention, and utilization of Artificial Intelligence (AI), synthesizing findings from 25 empirical studies published between 2021 and early 2025. Employing an integrated Antecedents-Decisions-Outcomes (ADO) and Theories-Contexts-Methods (TCM) framework, the analysis reveals that research in this period predominantly utilizes quantitative SEM methods based on TAM and UTAUT frameworks, largely within higher education contexts. Key findings indicate that technological knowledge facets, particularly Objective Knowledge (e.g., AI literacy) and Self-Efficacy, are critical antecedents to AI adoption, though their influence is often indirect. These factors frequently shape adoption outcomes by impacting core perceptual mediators, notably perceived ease of use, perceived usefulness, and trust. The synthesis highlights significant gaps, including limited methodological diversity, a narrow contextual focus, under-explored theoretical perspectives beyond TAM/UTAUT, and insufficient investigation into actual AI usage behavior. Addressing these gaps through diversified research approaches is crucial for advancing a comprehensive understanding of AI adoption dynamics.