Nexus between Factors Influencing the Adoption of Artificial Intelligence and Small Business Management Performance in Bayelsa State, Nigeria

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 micro- 
enterprises 
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 R- 
value 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

enjoy relatively high positivity levels. Written 
discussion's highly user-friendly nature