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عنوان انگلیسی مقاله:
Drivers, barriers and social considerations for AI adoption in business and management: A tertiary study
ترجمه فارسی عنوان مقاله:
رانندگان ، موانع و ملاحظات اجتماعی برای پذیرش هوش مصنوعی در مشاغل و مدیریت: یک مطالعه عالی
Sciencedirect - Elsevier - Technology in Society, Journal Pre-proof, 101257. doi:10.1016/j.techsoc.2020.101257
The number of academic papers in the area of Artificial Intelligence (AI) and its applications across business
and management domains has risen significantly in the last decade, and that rise has been followed by an
increase in the number of systematic literature reviews.
The aim of this study is to provide an overview of existing systematic reviews in this growing area of research
and to synthesise their findings related to enablers, barriers and social implications of the AI adoption in
business and management.
The methodology used for this tertiary study is based on Kitchenham and Charter’s guidelines , resulting in
a selection of 30 reviews published between 2005 and 2019 which are reporting results of 2,021 primary
These reviews cover the AI adoption across various business sectors (healthcare, information technology,
energy, agriculture, apparel industry, engineering, smart cities, tourism and transport), management and
business functions (HR, customer services, supply chain, health and safety, project management, decisionsupport,
systems management and technology acceptance).
While the drivers for the AI adoption in these areas are mainly economic, the barriers are related to the
technical aspects (e.g. availability of data, reusability of models) as well as the social considerations such as,
increased dependence on non-humans, job security, lack of knowledge, safety, trust and lack of multiple
Very few reviews outside of the healthcare management domain consider human, organisational and wider
societal factors and implications of the AI adoption.
Most of the selected reviews are recommending an increased focus on social aspects of AI, in addition to more
rigorous evaluation, use of hybrid approaches (AI and non-AI) and multidisciplinary approaches to AI design
Furthermore, this study found that there is a lack of systematic reviews in some of the AI early adopter sectors
such as financial industry and retail and that the existing systematic reviews are not focusing enough on
human, organisational or societal implications of the AI adoption in their research objectives.
Keywords: artificial intelligence | business | machine learning | management | systematic literature review | tertiary study