Jul 2026· Journal of Emerging Perspectives· 0 citations· 3 references
TL;DR
An interdisciplinary perspective is adopted to examine the paradigm of agentic AI, tracing its evolution from earlier forms of automation and outlining its defining characteristics, architectures and application domains, and addressing the ethical, legal and governance challenges raised by autonomous agents.
Abstract
The evolution of artificial intelligence is redefining the relationship between humans and machines, shifting from traditional automation toward systems endowed with agency. Unlike conventional AI, which primarily supports or executes predefined tasks, agentic AI systems are capable of autonomous decision-making, proactive goal generation, learning from experience and coordinated action within complex environments. This shift represents not only a technological advancement but an ontological transformation, as machines increasingly operate as cognitive agents rather than passive tools. This article adopts an interdisciplinary perspective to examine the paradigm of agentic AI, tracing its evolution from earlier forms of automation and outlining its defining characteristics, architectures and application domains. It then analyses the implications for work and organisational structures, highlighting how agentic systems reconfigure roles, redistribute cognitive labour and enable new forms of human–machine co-agency. Finally, the paper addresses the ethical, legal and governance challenges raised by autonomous agents, arguing for responsible adoption frameworks that preserve human centrality, accountability and social justice in emerging socio-technical systems.
By reframing control as the management of acceptable behavioral space rather than deterministic instruction, this work contributes to the emerging field of agentic software systems and proposes a scalable foundation for trustworthy autonomous computing.
Ilker Kanatli· International Journal of Res...· 0 citations
A comprehensive framework for the design, evaluation, and responsible deployment of Agentic AI is proposed, emphasizing safety, explainability, human-in-the-loop supervision, and ethical compliance and aims to maximize the benefits of Agentic AI while minimizing potential risks.
Nitin S. Shrirao, Dnyaneshwar S. Jadhav, Sarita B. Patil· Recent Trends in Mathematics· 0 citations
A unified, taxonomy-driven, and deployment-oriented survey of agentic AI systems, synthesizing recent advances through a modular reference architecture and a four-dimensional taxonomy that characterizes agents along the axes of autonomy, tool use, collaboration, and safety–governance is presented.
Sparsh Bajoria, Shreyanshu Ranjan, Adhitya M et al.· Cognitive Computation· 0 citations
Artificial Intelligence (AI) enables powerful capabilities that are transforming almost all sectors. However, the economic growth driven by AI comes at a cost, and its sociotechnical impacts are fraught with contradictions and paradoxes. As a result, several legal initiatives and risk management frameworks have been introduced to mitigate the various risks associated with AI systems. Agentic AI systems require even closer attention than traditional AI. While traditional AI has a narrow focus and responds to direct commands, Agentic AI emerges from combining multiple types of AI capable of planning, tool use, and multi-step execution. These systems can behave and interact autonomously, making decisions and performing tasks to achieve system objectives with minimal human oversight. Recognizing that Agentic AI represents a paradigm shift, this paper addresses its challenges from a Human-AI Interaction perspective. It examines the root causes and impacts of risks arising from the transition from Task Automation to Intentionality Automation, where the user manages outcomes and constraints rather than individual task steps. Key issues include the Open-Loop Control Gap and the Metacognitive Gap, whose relationship is fundamental to understanding the collapse of human oversight, as they represent two sides of the same coin in the loss of control. By analysing scenarios such as cybersecurity and healthcare, this paper identifies dimensions of user demand and identifies Ecological Interface Design as an ergonomic approach to ensure that as AI gains agency, the human retains authority and situational awareness.
M. Simões-Marques· AHFE International· 0 citations
This work synthesizes perspectives from philosophy, cognitive science, and AI to define agency, outline its key properties, and situate it in relation to existing paradigms such as reinforcement learning, symbolic reasoning, Belief–Desire–Intention (BDI) architectures, and embodied cognition.
This paper examines the phase transition from deterministic algorithmic execution (DevOps) to probabilistic socio-technical orchestration (AgentOps) and synthesizes evolutionary biology and Hellenistic philosophy to reframe human-agent teaming as the integration of a synthetic symbiote.
Svetlana Meissner· TH Wildau Engineering and Na...· 0 citations
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