Corresponding Manager: Davide Liberato Lo Conte (davideliberato.loconte@uniroma1.it)
Track Manager(s): Davide Liberato Lo Conte
Description
Digital transformation has reached a new stage where Artificial Intelligence systems act as autonomous, agentic entities shaping decisions, strategies, and public policies. This track explores how Agentic AI—AI systems capable of goal-directed, adaptive, and context-aware behavior—transforms governance, risk management, and organizational decision-making in both private and public sectors.
We invite contributions that examine the ethical, managerial, and regulatory implications of AI-driven transformation, focusing on how algorithmic decision-making influences accountability, transparency, and human oversight. The track welcomes both conceptual and empirical papers addressing challenges such as algorithmic governance, digital trust, and AI literacy, as well as opportunities for innovation, resilience, and sustainable competitiveness.
By integrating perspectives from management, public administration, data ethics, and information systems, this track aims to foster a multidisciplinary dialogue on how to design and implement responsible, explainable, and human-centered digital transformation frameworks for the algorithmic society.
Keywords
Agentic AI; Digital Transformation; Risk Governance; Explainable AI; Ethical Decision-Making
Key References
Brynjolfsson, E., & McAfee, A. (2017). Machine, Platform, Crowd: Harnessing Our Digital Future. Norton.
Schuett, J. (2024). Risk Management in the Artificial Intelligence Act. European Journal of Risk Regulation, 15(2), 367–385.
Silic, M., Silic, D., & Kind-Trüller, K. (2025). From Shadow IT to Shadow AI: Threats, Risks and Opportunities for Organizations. Strategic Change, 34(1), 1–16.
Stein, V., & Wiedemann, A. (2016). Risk Governance: Conceptualization, Tasks, and Research Agenda. Journal of Business Economics, 86(8), 813–836.
van der Heijden, K. (1996). Scenarios: The Art of Strategic Conversation. Wiley.
Research Partnerships and Promotion Channels
Sapienza University of Rome – Department of Management