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AI Agents and Agentic Systems: Redefining Global it Management

Research output: Contribution to journalEditorial

33 Scopus citations

Abstract

Artificial Intelligence (AI) agents represent a transformative advancement in global Information Technology (IT) management, introducing autonomous, goal-driven systems capable of reasoning, adapting, and executing decisions across distributed IT ecosystems. By leveraging Large Language Models (LLMs) and advanced AI frameworks, they enhance operational efficiency, decision-making, and cross-border IT collaboration. Their impact spans finance, healthcare, supply chain management, and enterprise IT services, where they act as virtual team members, automating infrastructure management, optimizing workflows, and ensuring 24/7 global system continuity. Despite these benefits, challenges persist in trust management, ethical accountability, and legacy system integration. As AI agents take on complex roles, concerns over safety, security, transparency, bias, and decision-making accountability become critical for many organizations. This study examines these complexities from a global IT perspective. We review the recent research and propose a research agenda that explores the ethical, operational, and strategic implications of AI agents in modern IT ecosystems.

Original languageEnglish
Pages (from-to)175-185
Number of pages11
JournalJournal of Global Information Technology Management
Volume28
Issue number3
DOIs
StatePublished - 2025

Bibliographical note

Publisher Copyright:
© 2025 The Author(s). Published with license by Taylor & Francis Group, LLC.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

Keywords

  • AI Agents
  • Agentic AI
  • Artificial Intelligence
  • IT governance
  • cybersecurity
  • global IT management
  • project management
  • threat intelligence

ASJC Scopus subject areas

  • Information Systems
  • Information Systems and Management

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