Risk Assessment of AI and Recommender Systems in Social Commerce: A Case Study of SMEs Leveraging Social Media
DOI:
https://doi.org/10.70112/ajms-2025.14.1.4271Keywords:
Artificial Intelligence (AI), Small and Medium-Sized Enterprises (SMEs), Risk Management, Recommender Systems, SocialAbstract
This study investigates the application of artificial intelligence (AI) and recommender systems for risk assessment and management in small and medium-sized enterprises (SMEs) across social platforms such as WhatsApp Business. It evaluates the accuracy, usability, and impact of AI on risk profiling, management, and user engagement in online retail and social commerce. A quantitative survey was conducted with 200 SME participants to assess the performance of the AI tool. Results indicate that 56.5% of participants rated the tool as “more accurate,” while 23% rated it as “highly accurate” compared to traditional techniques. Usability received high ratings, with 60.3% of respondents rating it as “very good,” and 49.7% indicating they would recommend it. Notably, female and younger users reported higher levels of satisfaction and trust, potentially reflecting demographic differences in technology adoption. Furthermore, 85% of participants were unaware of AI tools for risk management, highlighting a significant knowledge gap. This study underscores the need for increased awareness, simplicity, and accessibility of AI solutions tailored to SMEs. The predictive model demonstrated a high level of effectiveness, with a Nagelkerke R² value of 0.871. Future recommendations include integrating chatbot applications, enabling offline functionality, and improving navigation to enhance trust and user acceptance. These enhancements could support the effective integration of AI into the digital economy, benefiting SMEs and offering implications for developers, policymakers, and business owners.
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