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Track 23 – Agentic and Generative AI: Pathways to Sustainable Operational Efficiency

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Corresponding Manager: Slimane Ed-Dafali (ed-dafali.s@ucd.ac.ma)

Track Manager(s): Slimane Ed-Dafali, Samuel Fosso Wamba

Description
In recent years, artificial intelligence (AI) has become a primary concern for institutions, companies, and policymakers. It has attracted significant attention due to its various applications in the business world. AI is now transforming how companies execute their operations, and its role is crucial to achieving operational efficiency. At the same time, in the current era of sustainability, AI platforms provide companies with tools and systems to manage environmental challenges, helping them gain a competitive advantage. Among its many forms, two rapidly emerging types, agentic AI and generative AI, are considered essential systems within companies due to their significant potential to influence how businesses function and the pursuit of their sustainable development goals.
Moreover, the existing literature reveals no prior research specifically addressing the effects of generative and agentic AI on operational efficiency in the context of sustainability.We invite academics and researchers to contribute studies and practical insights that (though not exclusively) address the following topics and questions:
• The impact of agentic and generative AI on operational efficiency;
• Agentic and generative AI adoption and operational sustainability performance;
• Data governance and Human-AI collaboration on sustainable operations;
• Agentic and generative AI and sustainability reporting frameworks;
• The impact of agentic and generative AI on sustainable business model innovation.

Keywords
Artificial intelligence; Agentic artificial intelligence; Generative artificial intelligence; Operational efficiency; Sustainability

Key References
Key References:
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Alkaraan, F., Albitar, K., Hussainey, K., & Venkatesh, V. G. (2022). Corporate transformation toward Industry 4.0 and financial performance: The influence of environmental, social, and governance (ESG). Technological Forecasting and Social Change, 175, 121423.
Al-Okaily, M., Alsmadi, A. A., Alrawashdeh, N., Al-Okaily, A., Oroud, Y., & Al-Gasaymeh, A. S. (2024). The role of digital accounting transformation in the banking industry sector : An integrated model. Journal of Financial Reporting and Accounting, 22(2), 308‑326. https://doi.org/10.1108/JFRA-04-2023-0214
Alshurideh, M. T., Kurdi, A. A., Yasin, S., Damra, Y., Al-Gasaymeh, A., Alzoubi, H. M., Hamadneh, S., Alzboun, N., & Alquqa, E. K. (2024). Exploring the impact of metaverse adoption on supply chain effectiveness : A pathway to competitive advantage. Uncertain Supply Chain Management, 12(2), 883‑892. https://doi.org/10.5267/j.uscm.2023.12.017
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Ed-Dafali, S., Hussainey, K., Adardour, Z., Derj, A., & WAMBA, S. F. (2025). Metaverse in ESG practices–A Game Changer or a Buzzword? A Methodological Framework and Research Agenda from a Systematic Review. Journal of Economic Surveys. https://doi.org/10.1111/joes.70036
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Gunay, S., Sraieb, M. M., Kaskaloglu, K., & Yıldız, M. E. (2023). Cryptocurrencies and global sustainability : Do blockchained sectors have distinctive effects? Journal of Cleaner Production, 425, 138943. https://doi.org/10.1016/j.jclepro.2023.138943
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Wamba, S. F., Queiroz, M. M., Randhawa, K., & Gupta, G. (2025). Generative artificial intelligence and the challe