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Artificial intelligence in information systems research: A systematic literature review and research agenda

Author

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  • Collins, Christopher
  • Dennehy, Denis
  • Conboy, Kieran
  • Mikalef, Patrick

Abstract

AI has received increased attention from the information systems (IS) research community in recent years. There is, however, a growing concern that research on AI could experience a lack of cumulative building of knowledge, which has overshadowed IS research previously. This study addresses this concern, by conducting a systematic literature review of AI research in IS between 2005 and 2020. The search strategy resulted in 1877 studies, of which 98 were identified as primary studies and a synthesise of key themes that are pertinent to this study is presented. In doing so, this study makes important contributions, namely (i) an identification of the current reported business value and contributions of AI, (ii) research and practical implications on the use of AI and (iii) opportunities for future AI research in the form of a research agenda.

Suggested Citation

  • Collins, Christopher & Dennehy, Denis & Conboy, Kieran & Mikalef, Patrick, 2021. "Artificial intelligence in information systems research: A systematic literature review and research agenda," International Journal of Information Management, Elsevier, vol. 60(C).
    • Handle: RePEc:eee:ininma:v:60:y:2021:i:c:s0268401221000761
    DOI: 10.1016/j.ijinfomgt.2021.102383
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    Citations

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    Cited by:

    1. Marc Andreas Schmitt, 2022. "Deep Learning in Business Analytics: A Clash of Expectations and Reality," Papers 2205.09337, arXiv.org.
    2. Efpraxia D. Zamani & Conn Smyth & Samrat Gupta & Denis Dennehy, 2023. "Artificial intelligence and big data analytics for supply chain resilience: a systematic literature review," Annals of Operations Research, Springer, vol. 327(2), pages 605-632, August.
    3. Fred Niederman & Elizabeth White Baker, 2023. "Ethics and AI Issues: Old Container with New Wine?," Information Systems Frontiers, Springer, vol. 25(1), pages 9-28, February.
    4. Antoine Harfouche & Bernard Quinio & Mario Saba & Peter Bou Saba, 2023. "The Recursive Theory of Knowledge Augmentation: Integrating human intuition and knowledge in Artificial Intelligence to augment organizational knowledge," Information Systems Frontiers, Springer, vol. 25(1), pages 55-70, February.
    5. Niklas Kühl & Max Schemmer & Marc Goutier & Gerhard Satzger, 2022. "Artificial intelligence and machine learning," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 2235-2244, December.
    6. Shivam Gupta & Sachin Modgil & Choong-Ki Lee & Uthayasankar Sivarajah, 2023. "The future is yesterday: Use of AI-driven facial recognition to enhance value in the travel and tourism industry," Information Systems Frontiers, Springer, vol. 25(3), pages 1179-1195, June.
    7. Zhiyu Cao & Zihan Chen & Prerna Mishra & Hamed Amini & Zachary Feinstein, 2023. "Modeling Inverse Demand Function with Explainable Dual Neural Networks," Papers 2307.14322, arXiv.org, revised Oct 2023.
    8. Emmanouil Papagiannidis & Ida Merete Enholm & Chirstian Dremel & Patrick Mikalef & John Krogstie, 2023. "Toward AI Governance: Identifying Best Practices and Potential Barriers and Outcomes," Information Systems Frontiers, Springer, vol. 25(1), pages 123-141, February.
    9. Michael Vössing & Niklas Kühl & Matteo Lind & Gerhard Satzger, 2022. "Designing Transparency for Effective Human-AI Collaboration," Information Systems Frontiers, Springer, vol. 24(3), pages 877-895, June.
    10. René Riedl, 2022. "Is trust in artificial intelligence systems related to user personality? Review of empirical evidence and future research directions," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(4), pages 2021-2051, December.
    11. Ida Merete Enholm & Emmanouil Papagiannidis & Patrick Mikalef & John Krogstie, 2022. "Artificial Intelligence and Business Value: a Literature Review," Information Systems Frontiers, Springer, vol. 24(5), pages 1709-1734, October.
    12. Siddharth Madhav Joshi & Anubha Shekhar Sinha, 2023. "Knowledge as practice - How Artificial Intelligence can create new knowledge?," Working papers 550, Indian Institute of Management Kozhikode.
    13. Mohammad I. Merhi, 2023. "An Assessment of the Barriers Impacting Responsible Artificial Intelligence," Information Systems Frontiers, Springer, vol. 25(3), pages 1147-1160, June.
    14. Samuli Laato & Matti Mäntymäki & A. K.M. Najmul Islam & Sami Hyrynsalmi & Teemu Birkstedt, 2023. "Trends and Trajectories in the Software Industry: implications for the future of work," Information Systems Frontiers, Springer, vol. 25(2), pages 929-944, April.
    15. Julia Brasse & Hanna Rebecca Broder & Maximilian Förster & Mathias Klier & Irina Sigler, 2023. "Explainable artificial intelligence in information systems: A review of the status quo and future research directions," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-30, December.
    16. Issa Helmi & Lakkis Hussein & Dakroub Roy & Jaber Jad, 2023. "Examining User Engagement and Experience in Agritech," International Journal of Contemporary Management, Sciendo, vol. 59(2), pages 17-32, June.
    17. Ariana Polyviou & Efpraxia D. Zamani, 2023. "Are we Nearly There Yet? A Desires & Realities Framework for Europe’s AI Strategy," Information Systems Frontiers, Springer, vol. 25(1), pages 143-159, February.
    18. Sood, Kirti & Singh, Simarjeet & Behl, Abhishek & Sindhwani, Rahul & Kaur, Sandeepa & Pereira, Vijay, 2023. "Identification and prioritization of the risks in the mass adoption of artificial intelligence-driven stable coins: The quest for optimal resource utilization," Resources Policy, Elsevier, vol. 81(C).
    19. Fronzetti Colladon, Andrea & Toschi, Laura & Ughetto, Elisa & Greco, Francesca, 2023. "The language and social behavior of innovators," Journal of Business Research, Elsevier, vol. 154(C).
    20. Ruiz-Meza, José & Montoya-Torres, Jairo R., 2022. "A systematic literature review for the tourist trip design problem: Extensions, solution techniques and future research lines," Operations Research Perspectives, Elsevier, vol. 9(C).
    21. Balakrishnan, Janarthanan & Abed, Salma S. & Jones, Paul, 2022. "The role of meta-UTAUT factors, perceived anthropomorphism, perceived intelligence, and social self-efficacy in chatbot-based services?," Technological Forecasting and Social Change, Elsevier, vol. 180(C).
    22. Mahmud, Hasan & Islam, A.K.M. Najmul & Ahmed, Syed Ishtiaque & Smolander, Kari, 2022. "What influences algorithmic decision-making? A systematic literature review on algorithm aversion," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    23. Vasiliki Koniakou, 2023. "From the “rush to ethics” to the “race for governance” in Artificial Intelligence," Information Systems Frontiers, Springer, vol. 25(1), pages 71-102, February.

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