OpenAlex · Aktualisierung stündlich · Letzte Aktualisierung: 22.03.2026, 10:32

Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.

Drivers, barriers and social considerations for AI adoption in business and management: A tertiary study

2020·337 Zitationen·Technology in SocietyOpen Access
Volltext beim Verlag öffnen

337

Zitationen

1

Autoren

2020

Jahr

Abstract

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 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 stakeholders' perspectives. 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 and evaluation. 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.

Ähnliche Arbeiten

Autoren

Institutionen

Themen

AI in Service InteractionsArtificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI
Volltext beim Verlag öffnen