Artificial Intelligence Adoption in Service Industries: A Systematic Literature Review of key Drives, Barriers, Challenges, and Strategies

Artificial Intelligence (AI) is reshaping service industries by automating processes, enhancing decision-making, and delivering personalized customer experiences across sectors like tourism, healthcare, finance, and governance. This systematic literature review consolidates findings from over 100 studies to explore the drivers, barriers, and strategies influencing AI adoption. While AI-driven advancements such as robotic process automation (RPA) and predictive analytics enable efficiency and innovation, significant challenges like infrastructural limitations, ethical concerns, and organizational resistance hinder its widespread adoption. High implementation costs, socio-economic disparities, and data privacy issues further complicate integration efforts, particularly in underdeveloped regions and resource-constrained industries. To address these barriers, the study highlights strategies like targeted training, policy-driven investments in digital ecosystems, and robust data governance frameworks. Additionally, balancing AI automation with human interaction emerges as a critical factor for stakeholder trust and acceptance. This review emphasizes the importance of interdisciplinary collaboration to align technological advancements with societal and organizational goals, ensuring that AI adoption fosters sustainability, inclusivity, and long-term growth in service industries.