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The impact of the integration of Big Data and Artificial Intelligence in Management Control: Systematic Literature Review
[L'impact de l'intégration du Big Data et de l'Intelligence Artificielle dans le ‎Contrôle de Gestion : Revue Systématique de Littérature]

Author

Listed:
  • Mariem Amedjar

    (BIGOFE - Laboratoire Business Intelligence, Gouvernance des Organisations, Finance et Politiques Economiques - Faculté des sciences juridiques économiques et sociales Ain Chock Université HASSAN II – Maroc)

  • Leila El Gnaoui

    (BIGOFE - Laboratoire Business Intelligence, Gouvernance des Organisations, Finance et Politiques Economiques - Faculté des sciences juridiques économiques et sociales Ain Chock Université HASSAN II – Maroc)

Abstract

In a context marked by digitalization and the emergence of Data Science, this research examines the future of management control in light of advancements in Big Data and Artificial Intelligence (AI). Through a systematic literature review conducted according to the PRISMA protocol, covering 62 articles, the study explores three main axes. First, it analyzes the specificities of Big Data, characterized by the 7 Vs (Volume, Velocity, Variety, Variability, Veracity, Value, and Visualization), which fundamentally transform the nature and scale of the data that organizations must process. Next, it examines the contributions of Data Science and Artificial Intelligence to Big Data processing, particularly through the four dimensions of Business Analytics (descriptive, diagnostic, predictive, and prescriptive). Finally, it assesses the implications of these technologies for the management control function. The results show that the integration of Big Data and AI does not render the management controller obsolete; rather, it encourages a reinvention of the role toward a "Strong Controller", capable of managing multidimensional and overall performance through real-time analyses, more reliable forecasts, and better integration of ESG criteria. However, this transformation faces several major challenges: resistance to change, insufficient technical skills, data quality issues, and legal constraints. Collaboration between the management controller, managers, employees, and data specialists thus becomes essential to overcoming these challenges. This research demonstrates that, by mastering these innovative technologies while maintaining strategic vision and professional expertise, the management controller can not only ensure their own sustainability but also enhance their contribution to corporate governance and sustainable organizational performance.

Suggested Citation

  • Mariem Amedjar & Leila El Gnaoui, 2026. "The impact of the integration of Big Data and Artificial Intelligence in Management Control: Systematic Literature Review [L'impact de l'intégration du Big Data et de l'Intelligence Artificielle dans le ‎Contrôle de Gestion : Revue Systématique de," Post-Print hal-05504260, HAL.
    • Handle: RePEc:hal:journl:hal-05504260
    DOI: 10.5281/zenodo.18500372
    Note: View the original document on HAL open archive server: https://hal.science/hal-05504260v1
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    References listed on IDEAS

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    1. Wang, Gang & Gunasekaran, Angappa & Ngai, Eric W.T. & Papadopoulos, Thanos, 2016. "Big data analytics in logistics and supply chain management: Certain investigations for research and applications," International Journal of Production Economics, Elsevier, vol. 176(C), pages 98-110.
    2. Sara Marques & Rui Gonçalves & Renato Lopes da Costa & Leandro Ferreira Pereira & Alvaro Lopes Dias, 2023. "The Impact of Intelligent Systems on Management Accounting," International Journal of Intelligent Information Technologies (IJIIT), IGI Global Scientific Publishing, vol. 19(1), pages 1-32, January.
    3. Rautiainen, Antti & Scapens, Robert W. & Järvenpää, Marko & Auvinen, Tommi & Sajasalo, Pasi, 2024. "Towards fluid role identity of management accountants: A case study of a Finnish bank," The British Accounting Review, Elsevier, vol. 56(4).
    4. Jensen, Michael C. & Meckling, William H., 2008. "Theory of the firm: managerial behavior, agency costs and ownership structure," RAE - Revista de Administração de Empresas, FGV-EAESP Escola de Administração de Empresas de São Paulo (Brazil), vol. 48(2), April.
    5. Alnoor Bhimani, 2020. "Digital data and management accounting: why we need to rethink research methods," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 31(1), pages 9-23, April.
    6. Rikhardsson, Pall & Yigitbasioglu, Ogan, 2018. "Business intelligence & analytics in management accounting research: Status and future focus," International Journal of Accounting Information Systems, Elsevier, vol. 29(C), pages 37-58.
    7. Velibor V. Mišić & Georgia Perakis, 2020. "Data Analytics in Operations Management: A Review," Manufacturing & Service Operations Management, INFORMS, vol. 22(1), pages 158-169, January.
    8. Appelbaum, Deniz & Kogan, Alexander & Vasarhelyi, Miklos & Yan, Zhaokai, 2017. "Impact of business analytics and enterprise systems on managerial accounting," International Journal of Accounting Information Systems, Elsevier, vol. 25(C), pages 29-44.
    9. Chatterjee, Sheshadri & Chaudhuri, Ranjan & Gupta, Shivam & Sivarajah, Uthayasankar & Bag, Surajit, 2023. "Assessing the impact of big data analytics on decision-making processes, forecasting, and performance of a firm," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    10. Olga Pilipczuk, 2020. "Toward Cognitive Management Accounting," Sustainability, MDPI, vol. 12(12), pages 1-22, June.
    11. Gianluca Vitale & Sebastiano Cupertino & Angelo Riccaboni, 2020. "Big data and management control systems change: the case of an agricultural SME," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 31(1), pages 123-152, April.
    12. Roy-Ivar Andreassen, 2020. "Digital technology and changing roles: a management accountant’s dream or nightmare?," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 31(3), pages 209-238, September.
    13. Simone Bevilacqua & Jana Masárová & Francesco Antonio Perotti & Alberto Ferraris, 2025. "Enhancing top managers' leadership with artificial intelligence: insights from a systematic literature review," Review of Managerial Science, Springer, vol. 19(9), pages 2899-2935, September.
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