Bridging textile design and AI: An innovative methodological approach for the Ghanaian Textile Designer

Purpose: The study aimed to investigate the feasibility of employing selected artificial intelligence (AI) software to generate contemporary textile designs. Focusing on bridging textile design and AI, with a methodological approach for the Ghanaian Textile Designer. With AI emerging as a transformative force in multiple industries, including textiles, the research sought to assess its capacity to enhance design processes and meet consumer preferences. Methodology/Design: Three AI software programs, including Playground, Leonardo, and Lexcia, were selected for the study. Each was provided with identical prompts to generate contemporary textile designs. The outputs were then systematically analysed to identify similarities, differences, and overall design quality. Findings: The results showed that while the software received identical prompts, the generated designs displayed notable variations, alongside some shared visual features. The AI-driven process proved significantly faster and more efficient than traditional methods and yielded designs consistent with consumer specifications. Practical and Social Implications: The findings suggest that AI tools can substantially improve productivity, creativity, and responsiveness in textile design. Introducing AI-based design tools to textile designers in Ghana could enhance competitiveness, foster innovation, and better align production with evolving market demands. Originality: This study offers an early exploration of the comparative application of multiple AI software tools for contemporary textile design, contributing novel insights into their feasibility, efficiency, and adaptability within the Ghanaian textile industry context.