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<p>Agentic Artificial Intelligence (AI) is poised to fundamentally reshape entrepreneurship by introducing autonomous systems that perceive context, set goals, orchestrate actions, and learn over time with minimal human oversight. This perspective paper examines how agentic AI reconfigures core entrepreneurial processes and introduces the concept of entrepreneur-co-agency, wherein externalized memory, planning, and inference augment human decision-making. We then analyze the shift from intuition-driven to data-driven mindsets, redefining creativity, risk, and responsibility. Illustrative case studies demonstrate how multi-agent architectures, powered by large language models, streamline ideation and strategic planning. Specifically, the paper (i) maps opportunities for innovation, inclusivity, and venture automation; (ii) identifies ethical, cognitive, and regulatory challenges; and (iii) proposes a nine-theme research agenda calling for interdisciplinary inquiry and proactive policy. We conclude by urging stakeholders to prepare for an entrepreneurial era shaped by increasingly autonomous and intelligent agents.</p>

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Agentic AI systems and the future of entrepreneurship: a perspective on co-agency, innovation, and ecosystem transformation

  • 期刊论文

  • 发表日期：

    2026年1月13日

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  • Mousa Ahmad Al-Bashrawi,
  • Mohammed A. Al-Sharafi,
  • Ibrahim A. Elgendy,
  • Mohamed Y. I. Helal,
  • Madhan Karthikeyan Anbalagan,
  • Inyoung Chae,
  • Yogesh K. Dwivedi

摘要

Agentic Artificial Intelligence (AI) is poised to fundamentally reshape entrepreneurship by introducing autonomous systems that perceive context, set goals, orchestrate actions, and learn over time with minimal human oversight. This perspective paper examines how agentic AI reconfigures core entrepreneurial processes and introduces the concept of entrepreneur-co-agency, wherein externalized memory, planning, and inference augment human decision-making. We then analyze the shift from intuition-driven to data-driven mindsets, redefining creativity, risk, and responsibility. Illustrative case studies demonstrate how multi-agent architectures, powered by large language models, streamline ideation and strategic planning. Specifically, the paper (i) maps opportunities for innovation, inclusivity, and venture automation; (ii) identifies ethical, cognitive, and regulatory challenges; and (iii) proposes a nine-theme research agenda calling for interdisciplinary inquiry and proactive policy. We conclude by urging stakeholders to prepare for an entrepreneurial era shaped by increasingly autonomous and intelligent agents.