AI, digital equity, and social sustainability in beauty retail: Fairness-aware governance and entrepreneurial pathways for inclusive AI adoption

The integration of Artificial Intelligence (AI) in the personal care and cosmetics sector has significantly transformed consumer experiences, offering AI-powered beauty recommendations, augmented reality (AR) try-on tools, and personalized skincare solutions. However, despite these advancements, consumer trust remains a critical barrier to adoption due to concerns over algorithmic fairness, inclusivity, data privacy, and transparency. This study investigates consumer perceptions of AI-driven beauty solutions within the UK and Ireland, exploring the factors influencing trust, adoption, and ethical considerations in AI-powered cosmetics retail. Employing a quantitative research approach, this study utilizes an online survey distributed to a diverse consumer base in the UK and Ireland, with data collected between 2020 and 2021, capturing insights from AI adopters and skeptics. The data were analyzed using descriptive statistics, regression analysis, and factor analysis to determine key drivers of consumer trust in AI-powered beauty solutions. The study is theoretically underpinned by the Technology Acceptance Model (TAM), Trust and E-Trust Theories, and Critical Realism, providing a socio-technical lens to examine how AI influences consumer decision-making, confidence, and engagement. Findings reveal that while AI has the potential to enhance shopping experiences, consumer skepticism remains high due to biases in AI recommendations (85.96 %), lack of algorithmic transparency (62 %), and concerns over data privacy (79 %). The research also identifies the gap between AI innovation and consumer literacy, highlighting the need for explainable AI (XAI) models and fairness-aware algorithms. This study contributes to the growing discourse on responsible AI adoption by emphasizing the need for inclusive AI models, transparent decision-making frameworks, and stronger data privacy measures. The findings provide actionable recommendations for AI-driven beauty brands, including the implementation of bias audits, privacy-preserving AI frameworks, and consumer education initiatives to enhance trust and adoption. By integrating fairness-aware AI governance, the personal care and cosmetics sector can foster ethical AI deployment that aligns with consumer expectations and industry best practices.