Artificial Intelligence Decision Support Systems as Predictors of Managerial Decision Quality among Small Retail Business Owners in the Case of Greater Accra, Ghana

Quality decisions made at work have become pivotal for business transformation and prosperity in the modern era. Grounded in this notion, this study investigated an artificial intelligence (AI) decision support system as a determinant of quality managerial decision-making using retail business owners in Accra and Tema Metropolis in Greater Accra, Ghana. The study specifically investigated how decision automation affects decision timeliness, assessed how the utilization of predictive analytics influences decision accuracy, and evaluated the degree of the relationship between real-time information support and decision effectiveness. The study adopted a quantitative research model in which small-scale business owners served as the unit of analysis. Findings indicated that decision automation positively affected decision timeliness with “r2 = 0.815, p < 0.05”; in addition, a significant positive influence was exerted by the utilization of predictive analytics on decision accuracy with “r2 = 0.713, p < 0.05”. Furthermore, real-time information support had a positive and significant relationship with decision effectiveness with “r = 0.805, p < 0.05”. These findings demonstrate that decision support capabilities stemming from AI-powered systems can adequately enhance quality managerial decision-making by ensuring more accurate, faster, and more effective decisions among owners of small-scale businesses. Grounded in the Technology Acceptance Model and Bounded Rationality Theory, the study specifically inquired into how decision automation affects decision timeliness, assessed how the use of predictive analytics influences decision accuracy, and evaluated the degree of the relationship between real-time information support and decision effectiveness. In conclusion, adopting AI decision support systems remains a strategic resource that is pivotal to improving operational performance and business competitiveness among small-scale retail businesses in the region. Thus, owners of small-scale businesses should increase their use of predictive analytics, invest more in AI-powered decision support technologies, and incorporate real-time information systems into their decision-making process. Therefore, government agencies and business associations should promote training in artificial intelligence decision support systems for small retail businesses because of their impact on Ghana’s development economy.