Stitching innovation in fashion retail: a systematic review of barriers to digital technology adoption, including AI and marketing automation, in women-led SMEs

Purpose This study systematically reviews barriers to digital technology adoption, including artificial intelligence (AI) and marketing automation (MA), in contexts relevant to women-led small and medium-sized enterprises (SMEs) in fashion and related retail, interpreted through the extended technology acceptance model (TAM++). Design/methodology/approach Following PRISMA 2020, a Web of Science search (2015–2026) retrieved 2,507 records. After screening and a two-reviewer eligibility assessment of 53 records, 25 studies were included. Their full texts were thematically analyzed in MAXQDA, and the resulting categories were interpreted through the three TAM++ thematic categories. Findings Eight categories were identified. Facilitating conditions, social influence, skill gaps/managerial expertise and financial constraints appeared in all 25 studies, followed by job relevance (24), perceived risk and privacy concerns (21), work-life/caregiving conflict (19) and digital trust/security (18). The categories span user, task and technological, social and environmental aspects. All eight also appeared in the 13 studies, including fashion businesses, where costs and task fit received greater emphasis. Research limitations/implications The evidence base is small and mainly concerns related digital technologies: two studies examine AI directly, none examine MA directly and four draw their samples entirely from fashion businesses. The findings indicate conditions for future testing, not causal effects. Practical implications Support for women-led fashion SMEs should combine training, finance, infrastructure, mentoring and trust-building measures and take caregiving demands into account. Originality/value The review offers a gender- and entrepreneurship-specific contextualization of TAM++ and identifies work-life/caregiving conflict as a recurring adoption condition outside existing TAM++ extensions.