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Artificial Intelligence and System Dynamics in Business and Management

by | Apr 5, 2024

The recent webinar, titled “The Dynamic Interplay Between Artificial Intelligence (AI) and System Dynamics (SD) in Business and Management,” provided deep insights into the evolving relationship between AI and SD. This session was part of the System Dynamics Society’s ongoing Seminar Series. It aimed to dissect the convergence of AI and SD within the business and management landscapes.

Key Takeaways from the Webinar:

  1. In-Depth Bibliometric Analysis: The session kicked off with a comprehensive bibliometric analysis, highlighting how academic discussions on System Dynamics and AI intersect, charting their evolution and emerging patterns. This approach provided a solid base for understanding the convergence trajectory of these fields.
  2. Advanced Topic Modeling Discoveries: The webinar delved into the intricacies of AI and SD integration through cutting-edge topic modeling techniques. This analysis offered a detailed perspective on how these fields are blending, adding depth to our understanding.
  3. Dual Convergence Pathways: The discussion highlighted two main convergence pathways: ‘soft convergence’ and ‘hard convergence.’ Soft convergence looks at how AI augments SD with a focus on social dynamics, while hard convergence explores AI’s role in reengineering system design and interdependencies.
  4. Emerging Trends and Strategic Implications: An interesting aspect of the session was the exploration of current trends. It was noted that soft convergence is more prevalent in today’s business landscape, but hard convergence is gaining momentum and could revolutionize SD research and application.
  5. Practical Applications of AI and SD: The session also covered how AI technologies are being used across various domains like healthcare, risk management, and customer service, providing real-world examples of their impact.
  6. Theoretical Framework Necessity: A crucial point raised was the need for a convincing theoretical framework to effectively combine AI’s data-based approaches with SD’s organizational strategies.

In closing, this seminar not only presented an analysis of AI and SD convergence but also invited scholars, researchers, and industry practitioners to further explore this synergy. The insights gained from this webinar are invaluable for anyone interested in the intersection of these two fields.

Watch the recording below

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About the Speakers

Francesca Iandolo, PhD: A Tenure-track Assistant Professor in Management at Sapienza University of Rome, Francesca Iandolo specializes in corporate sustainability and technology in digital platforms. With a master’s in accounting and a PhD focusing on the Viable Systems Approach, she actively contributes to academic coordination and research, and consults for private companies.

Giuliano Maielli: Researcher in business history and organization studies, focuses on technological and organizational innovation. His work, emphasizing design hierarchies, path-dependence, and socio-organizational phenomena, delves into platform innovation dynamics and the Internet of Things, contributing significantly to peer-reviewed academic publications.

Stefano Armenia: Tenure-track Lecturer at the Università Telematica degli Studi in Florence, specializes in Business Organizations and Dynamical Systems. With a background in Computer Engineering and Business Engineering, he contributes to System Dynamics societies, edits scientific journals, and researches in fields ranging from cybersecurity to sustainable transportation.

Pietro Vito, PhD: A researcher in Economics and Business Management at Sapienza University of Rome, Pietro Vito’s research spans systemic and vital perspectives in business management. His interests include sustainability, environmental protection, intellectual capital, and artificial intelligence, contributing to a broader understanding of management methodologies.

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