Artificial Intelligence is a branch of Computer Science that has attracted considerable attention from both academia and industry, given its widespread application across everyday life and industrial domains. The textile industry is no exception, and this discipline has multiple applications in industrial activities and the creative processes within this domain. This paper presents a systematic literature review following the Kitchenham & Charters protocol to explore how AI is being applied in textile design. A total of 216 studies were initially identified, of which 86 met the inclusion criteria. The review analyzes the types of AI used such as neural networks, fuzzy logic, and generative models; and their implementation in areas including defect detection, pattern generation, comfort prediction, and automated design. Results show that most AI systems are developed in experimental contexts, often using author-generated datasets, with limited use of standardized or industrial data sources. Evaluation practices combine quantitative metrics with qualitative assessments of aesthetics and feasibility. While some international standards are cited, there is no unified framework for integrating or validating AI tools in the textile sector. This study offers a structured overview of current practices, highlights methodological and standardization gaps. It serves as a reference for both academia and industry, supporting the responsible and informed integration of AI in textile design and production.