TY - JOUR
T1 - AI Agents and Agentic Systems
T2 - A Multi-Expert Analysis
AU - Hughes, Laurie
AU - Dwivedi, Yogesh K.
AU - Malik, Tegwen
AU - Shawosh, Mazen
AU - Albashrawi, Mousa Ahmed
AU - Jeon, Il
AU - Dutot, Vincent
AU - Appanderanda, Mandanna
AU - Crick, Tom
AU - De’, Rahul
AU - Fenwick, Mark
AU - Gunaratnege, Senali Madugoda
AU - Jurcys, Paulius
AU - Kar, Arpan Kumar
AU - Kshetri, Nir
AU - Li, Keyao
AU - Mutasa, Sashah
AU - Samothrakis, Spyridon
AU - Wade, Michael
AU - Walton, Paul
N1 - Publisher Copyright:
© 2025 International Association for Computer Information Systems.
PY - 2025
Y1 - 2025
N2 - The emergence of AI agents and agentic systems represents a significant milestone in artificial intelligence, enabling autonomous systems to operate, learn, and collaborate in complex environments with minimal human intervention. This paper, drawing on multi-expert perspectives, examines the potential of AI agents and agentic systems to reshape industries by decentralizing decision-making, redefining organizational structures, and enhancing cross-functional collaboration. Specific applications include healthcare systems capable of creating adaptive treatment plans, supply chain agents that predict and address disruptions in real-time, and business process automation that reallocates tasks from humans to AI, improving efficiency and innovation. However, the integration of these systems raises critical challenges, including issues of attribution and shared accountability in decision-making, compatibility with legacy systems, and addressing biases in AI-driven processes. The paper concludes that while agentic systems hold immense promise, robust governance frameworks, cross-industry collaboration, and interdisciplinary research into ethical design are essential. Future research should explore adaptive workforce reskilling strategies, transparent accountability mechanisms, and energy-efficient deployment models to ensure ethical and scalable implementation.
AB - The emergence of AI agents and agentic systems represents a significant milestone in artificial intelligence, enabling autonomous systems to operate, learn, and collaborate in complex environments with minimal human intervention. This paper, drawing on multi-expert perspectives, examines the potential of AI agents and agentic systems to reshape industries by decentralizing decision-making, redefining organizational structures, and enhancing cross-functional collaboration. Specific applications include healthcare systems capable of creating adaptive treatment plans, supply chain agents that predict and address disruptions in real-time, and business process automation that reallocates tasks from humans to AI, improving efficiency and innovation. However, the integration of these systems raises critical challenges, including issues of attribution and shared accountability in decision-making, compatibility with legacy systems, and addressing biases in AI-driven processes. The paper concludes that while agentic systems hold immense promise, robust governance frameworks, cross-industry collaboration, and interdisciplinary research into ethical design are essential. Future research should explore adaptive workforce reskilling strategies, transparent accountability mechanisms, and energy-efficient deployment models to ensure ethical and scalable implementation.
KW - AI agents
KW - OpenAI operator
KW - agentic AI
KW - agentic system
KW - autonomous agent
KW - cognitive agent
KW - intelligent agent
KW - smart agent
KW - virtual assistant
UR - http://www.scopus.com/inward/record.url?scp=105003188833&partnerID=8YFLogxK
U2 - 10.1080/08874417.2025.2483832
DO - 10.1080/08874417.2025.2483832
M3 - Article
AN - SCOPUS:105003188833
SN - 0887-4417
JO - Journal of Computer Information Systems
JF - Journal of Computer Information Systems
ER -
