Research Background: The retail industry is undergoing a significant transformation driven by the integration of Artificial Intelligence (AI) technologies. AI implementation faces challenges, notably risk of malfunctions, which disrupt internal operations. In the context of this research, "non-consumer AI malfunctions" are defined as disruptions in AI systems that are utilized within the organizational operations of retail businesses. Our investigation is motivated by the recognition that while AI has the potential to redefine retail operations fundamentally, a nuanced understanding of how to manage and learn from AI malfunctions, particularly in non-consumer contexts, is essential for realizing this potential fully. This study underscores the importance of researching how organizations effectively respond to such malfunctions and recover from them. Research Purpose: The purpose of this research is investigating diverse mitigation strategies adopted by retail organizations in response to non-consumer AI malfunctions, and to construct a comprehensive framework to address this. Method: This research adopts an exploratory qualitative approach, utilizing semi-structured interviews to gather in-depth insights. Data was collected from key personnel across various retail companies, employing inductive coding using the Gioia Methodology Theory, to identify and analyse emerging themes. In total, interview data from 12 retail specialists was collected and analysed. This methodology is grounded in Sociotechnical Systems Theory, capturing the complex interplay between social and technical factors, ensuring a comprehensive understanding of the strategic responses of retail organizations to AI malfunctions. Conclusion: Our study contributes to various research gaps, as it is the first comprehensive study on non-consumer AI malfunctions in the retail industry. By developing a comprehensive framework for addressing non-consumer AI malfunctions, the study contributes to the ongoing advancement of knowledge and understanding in this important area of study. Our study extends the theoretical understanding of the interplay between technology, organization, and strategies, highlighting their inseparable relationship when addressing non-consumer AI malfunctions. Our findings reveal that effective management of AI malfunctions requires adjustments in both social and technical systems, emphasizing the importance of organizational resilience and adaptability.