Facilitators and Barriers of Artificial Intelligence Adoption in Business – Insights from Opinions Using Big Data Analytics
Arpan Kumar Kar () and
Amit Kumar Kushwaha ()
Additional contact information
Arpan Kumar Kar: Indian Institute of Technology Delhi
Amit Kumar Kushwaha: Indian Institute of Technology Delhi
Information Systems Frontiers, 2023, vol. 25, issue 4, No 5, 1374 pages
Abstract:
Abstract Data-driven predictions have become an inseparable part of business decisions. Artificial Intelligence (AI) has started helping the product and support teams perform more accurate experiments in various business settings. This study proposes a framework for businesses based on inductive learnings related to success and barriers shared on social media platforms. Our goal is to analyse the signals emerging from these conversational opinions from the early adoption of AI, with a focus towards facilitators and barriers faced by teams. Factors like efficiency, innovation, business research, product novelty, manual intervention, adaptability, emotion, support, personal growth, experiential learning, fear of failure and fear of upgradation have been identified based on an exploratory study and then a confirmatory study. We present the learnings through a roadmap for practitioners. This study contributes to the IS literature by delineating AI as a determinant of success and introduces a lot of organizational factors into the model.
Keywords: Information systems adoption; Artificial intelligence; Machine learning; Chatbots; Marketing automation; Big data analytics (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://link.springer.com/10.1007/s10796-021-10219-4 Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:infosf:v:25:y:2023:i:4:d:10.1007_s10796-021-10219-4
Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10796
DOI: 10.1007/s10796-021-10219-4
Access Statistics for this article
Information Systems Frontiers is currently edited by Ram Ramesh and Raghav Rao
More articles in Information Systems Frontiers from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().