Sign language, a vital mode of communication for the deaf and hard of hearing community, is facing significant challenges in translation. Sign language translation using generative AI stands poised as a revolutionary approach to address the profound communication barriers encountered by this community. In this review paper, we delve deeply into the cutting-edge techniques, methodologies, and real-world applications shaping this transformative field. Central to our exploration is the recognition of sign language as not just a mode of communication but a vital lifeline for those with hearing impairments. Through a thorough analysis of existing literature, we highlight the urgent need to move beyond traditional manual translation methods. By harnessing the power of generative AI, we have the potential to revolutionize sign language translation. This means not only achieving greater accuracy and efficiency but also fostering more emotionally resonant communication experiences for deaf and mute individuals. This review paper explores the comparison of various techniques in the domain of sign language translation, in particular, artificial intelligence technologies as the main transformative force. The study discusses two separate techniques, including Convolutional Neural Networks [1], and Neural Machine Translation (Camgoz et al. in Proceedings of the IEEE conference on computer vision and pattern recognition [7]) and performs performance analysis as part of the comparison of the above methodologies. Various metrics are of interest, such as accuracy, precision, recall, and F1 score. Moreover, the paper provides an insight into the role generative adversarial networks (Stoll et al. in Proceedings of the 29th British machine vision conference (BMVC 2018). British Machine Vision Association [16]) may play in automatically creating sign animations using a text or a verbal description. GANs (Elakkiya et al. in Expert Syst Appl 182:115276 [12]; Stoll et al. in Proceedings of the 29th British machine vision conference (BMVC 2018). British Machine Vision Association [16]), by repeatedly improving their perception of the spatial and temporal mechanics of sign language, may become instrumental in introducing new modes of communication. As a result, this review paper highlights the roles that artificial intelligence, especially generative AI (Mallory in Society for information technology & teacher education international conference. Association for the Advancement of Computing in Education (AACE) [10]; Feuerriegel et al. in Bus Inf Syst Eng 66(1):111–126 [11]), plays in the development of sign language translation and communication in general.