International audience
The paper aimed to examine the issues associated with AI in business decision decision-making based on bias, competence, the absence of a comprehensible strategy, and inadequate attention to strategic, legal, and explainability factors. Study Design: Qualitative research design. Place and Duration of Study: MFIs in Zimbabwe between November 2024 and January 2025. Methodology: Purposive sampling was used to select four participants with specialized expertise in the research area of this study. Each of the four interviewed participants had a diverse role in artificial intelligence (1 partnership manager,1 concept manager for analytics and AI, one legal consultant, and one software engineer). The study highlights how AI is revolutionizing strategic decision-making in relation to automation, predictive analysis, and organizational efficiency. Participants brought a number of important topics, such as explainability difficulties, gaps in AI knowledge and biases in decision-making. 100 percent of the respondents agreed that AI systems and technologies are more effective as assisting tools for those who make decisions than as completely independent solutions. The report offers solutions to these issues, including developing diverse teams to contribute a range of viewpoints, putting explainable AI systems in place to guarantee transparency, and raising AI literacy throughout enterprises to reduce competence gaps. These contributions are noteworthy because they address the operational and ethical issues that come up when using AI in decision-making while also providing useful advice for companies wishing to use it.Conclusion: The findings offer valuable guidance for companies looking to adopt AI technologies into their decision-making frameworks, assisting them in overcoming existing obstacles in this area. However further research may be required on a larger scale to validate the findings.