Despite AI being a major driver that fuels high performance in micro-enterprises, its adoption rate in Bayelsa State, Nigeria, is very low. The main objective of this research is to determine the factors that influence the adoption of AI and how it affects the management of microenterprises in Bayelsa State, Nigeria. Specifically, the study sought to examine the factors as stated by Okoye et al. (2024); they are perceived trust, perceived usefulness, perceived ease of use and willingness to use the system. The guiding theory was the Theory of Reasoned Action (TRA). A descriptive survey research design was adopted for this study, with stratified random sampling technique and a self-constructed questionnaire used to generate data for the study; both content and face validation were done on the instrument. Results of this study indicate that SMEs recorded a high mean score (M = 4.07), representing that the integration of artificial intelligence tools and strategies is largely seen as a positive boost towards overall performance within sampled small businesses in the micro-enterprise sector. Of various AI constructs, consider Perceived Trust (M = 4.04, SD = 0.801) as an important element which leads us to the conclusion that trustworthiness concerning AI systems prevails as a requirement for proper digital transformation adoption within the context of small to medium business enterprises (SMBEs). Perceived usefulness scored a slightly lower mean value (M = 3.84) while having the highest deviation measure (SD = 0.965), letting participants perceive variability in evaluation outcomes on this factor with a relatively higher credible measure. Pain-Free Buying The perception about usability is also relatively high with reference to AI technologies through participants’ observation (M=3.94); however, it doesn’t indicate full agreement, yet there may be variations in levels of literacy skills or system intricacy. Among factors considered, willingness to change the organisation’s direction/pathway receives a higher rating (M=3.99; SD=0.876), demonstrating most forms SME operations display great readiness for artificial intelligence-driven changes. more strategic planning implementation process Business owners’ perceptions on AI-related constructs appeared to be good predictors, as concluded from the model summary with an Rvalue equalling 0.912, signifying a robust positive link between such perceptions and SME performance level. Whenever variables are included, observed R² comes out at a level close to the figure following presentation. Closed-type questionnaires were distributed among SMEs consisting of managers/owners over a period of months in order to justifiably elicit the required response data. Technologies represented by the firm’s managers/owners