The textile industry faces increasing scrutiny for its environmental pollution, waste of water and energy resources, labor issues, and inefficiencies throughout the value chain (Pedersen and Gwozdz, 2014). As global agendas, such as the United Nations Sustainable Development Goals (SDGs) and the European Green Deal, call for urgent transformation, technology emerges as both a potential enabler of sustainability and a tool to mitigate the textile industry impacts. However, existing literature remains fragmented, often analyzing technologies in specific operational conditions or focusing on a singular dimension of sustainability. By conducting a systematic literature review of recent academic contributions (2020–2024), this study examines how technologies support the environmental, economic, and social pillars of sustainability in the textile industry. The review identifies and categorizes 88 articles from the Scopus database, revealing a diverse yet disconnected research landscape. From the content analysis, technologies are grouped into three clusters: emerging, established, and process-oriented. To offer an integrative perspective, the paper introduces a multi-level taxonomy that links technologies to specific sustainability-related weaknesses across the textile value chain. Findings show that while some technologies, especially Blockchain and data-driven systems, demonstrate convergent sustainability benefits, most generate partial or domain-specific improvements, such as Artificial Intelligence (AI) which raises concerns related to equity and digital exclusion (Park et al., 2020). The social dimension remains the least addressed, emphasizing the need for comprehensive strategies and governance frameworks to guide equitable technological adoption. This research offers a structured framework to help vertically integrated textile companies understand how technology adoption can address their sustainability challenges and provides practical insights for aligning business practices with innovation and SDGs objectives.