Artificial Intelligence and the Management of Emerging Financial Risks in Small and Medium-Sized Enterprises in Mali (Revue Internationale de la Recherche Scientifique (Revue-IRS))

Summary

• The study surveyed 140 professionals from small and medium-sized enterprises in Mali and interviewed 10 participants selected by purposive sampling.p.2
• Fieldwork took place between 26 January 2026 and 20 February 2026, and data were analysed with SPSS and Excel.p.2
• Anomaly detection and analysis scored the highest values, at 27.6% efficiency and 28.5% risk reduction.p.10
• In the organisational performance table, anomaly analysis and detection reaches 28% efficiency and 29% risk reduction.p.11
• Fraud detection has a mean of 4.3 with a standard deviation of 0.5 and a significance of 0.001.p.12
• General user satisfaction with AI has a mean of 4.1, while ease of use scores 3.8, indicating moderate satisfaction.p.13
• Accountants are the largest group of respondents at 15%, followed by financial managers at 12.9%.p.9

Key insights

1. Automation and productivity reach 26.9% efficiency and 27.6% risk reduction in Malian SMEs.p.10
2. Task automation is rated at 27.1% efficiency and 28.1% risk reduction.p.11
3. Reduction in accounting errors has a mean of 4.2 with a significance of 0.002.p.12
4. Perceived added value of AI tools scores 4.2, showing users see real gains in their work.p.13
5. Acceptance of financial software has a mean of 4 with a standard deviation of 0.6.p.13
6. Development of internal skills has a mean of 4.3, the highest in the organisational improvement indicators.p.14
7. The author notes that AI is not a lasting competitive advantage unless accompanied by investment in training and digital infrastructure.p.7