Authors :
T D C Pushpakumara; Fazeela Jameel Ahsan
Volume/Issue :
Volume 10 - 2025, Issue 3 - March
Google Scholar :
https://tinyurl.com/ycxm99y8
Scribd :
https://tinyurl.com/yy43sju3
DOI :
https://doi.org/10.38124/ijisrt/25mar1490
Google Scholar
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
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Abstract :
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.
Keywords :
Artificial Intelligence (AI), Service Industries, AI Adoption Strategies, Infrastructure Limitations, Ethical Concerns in AI, Data Privacy Challenges, Organizational Resistance, Sustainability in AI Integration.
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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.
Keywords :
Artificial Intelligence (AI), Service Industries, AI Adoption Strategies, Infrastructure Limitations, Ethical Concerns in AI, Data Privacy Challenges, Organizational Resistance, Sustainability in AI Integration.