Textile wet processing, i.e., desizing and bleaching, dyeing, printing, and finishing, is one of the most complex and resource consuming stages in textile production. The processes involve multiple parameters, such as temperature, rate of rise in temperature, pH, chemical concentration, bath liquor ratio, and time, which must be controlled precisely to achieve consistent and desired product quality. Traditional process control relies largely on manual supervision and conventional automation systems, often leading to process variations, increased resource consumption, and inconsistent quality. Artificial Intelligence (AI) offers significant opportunities to enhance process control by enabling predictive modelling, real-time monitoring, and intelligent decision support. This paper examines the potential applications of AI in textile wet processing, with a focus on process optimisation, defect prediction, resource efficiency, and smart manufacturing. The paper highlights the technological framework, implementation opportunities, and challenges associated with integrating AI-assisted systems in textile wet processing industries.