Artificial Intelligence for Disaster Risk Management in the Beauty Industry

The increasing reliance on AI in the beauty industry has significantly enhanced various business operations, including customer experience personalization, supply chain management, and product innovation. However, this integration also introduces vulnerabilities, particularly in the realm of Disaster Risk Management (DRM). This study explores the role of AI in mitigating disaster-related risks within the beauty industry, focusing on predictive analytics, supply chain resilience, cybersecurity, and crisis response. A qualitative research approach was adopted, drawing on an extensive review of secondary data sources, including industry reports, case studies, and peer-reviewed literature. Findings indicate that AI-driven predictive models can enhance disaster preparedness by forecasting potential risks, enabling proactive decision-making, and improving operational continuity. Additionally, AI facilitates real-time monitoring of supply chains, allowing for swift identification and resolution of disruptions. Despite these advantages, challenges such as data privacy concerns, algorithmic biases, and regulatory compliance remain critical considerations. Ethical implementation and robust security measures are essential to maximizing AI's benefits in DRM. Future research should focus on developing standardized risk assessment frameworks and fostering industry-wide collaboration to refine AI-driven DRM strategies.