Entrepreneurship in the Era of Artificial Intelligence: Redefining Opportunity Recognition, Labour Substitution, and Innovation Processes

Authors

  • Muhammad Sarfraz Latif PhD Scholar HRM, University Institute of Management Sciences, PMAS-AAUR, Rawalpindi
  • Mansoor Ahmed Soomro Assistant Professor, Department of Business Administration, Shah Abdul Latif University, Khairpur, Shahdadkot Campus, Sindh, Pakistan. https://orcid.org/0000-0002-7117-1187
  • Asif Ahmad Student, Departamento de Informática, da Escola de Ciências e Tecnologia, Universidade de Évora, Portugal https://orcid.org/0009-0009-5538-1633
  • Muhammad Irfan Syed Department of Public Administration (DPA), University of Karachi, Karachi

DOI:

https://doi.org/10.63544/ijss.v5i1.229

Keywords:

Artificial Intelligence, Entrepreneurship, Innovation Processes, Labor Substitution, Opportunity Recognition, SMEs

Abstract

This study examined the transformative role of artificial intelligence (AI) in entrepreneurship, focusing on opportunity recognition, labour substitution, and innovation processes. Rapid advancements in AI technologies altered traditional entrepreneurial practices by enabling data-driven decision-making, predictive analytics, and automation of routine tasks. Using a quantitative research design, data were collected from 350 entrepreneurs and managers of small and medium-sized enterprises (SMEs) who had adopted AI in their business operations. Descriptive statistics, reliability tests, regression analysis, and structural equation modelling (SEM) were employed to analyse the relationships between AI adoption and entrepreneurial outcomes. The results revealed that AI adoption significantly enhanced opportunity recognition by enabling entrepreneurs to identify emerging market trends, assess risks, and make informed strategic decisions. AI also facilitated labour substitution by automating repetitive tasks, allowing human resources to focus on creative and analytical roles. Moreover, AI-driven innovation processes accelerated product development, improved operational efficiency, and supported experimentation, thereby strengthening entrepreneurial performance. Despite these positive outcomes, challenges such as workforce displacement, ethical concerns, and limited access to AI technologies were identified as barriers to full adoption. The study concluded that AI functions as a strategic enabler that reshapes entrepreneurial practices, labour dynamics, and innovation strategies. The findings provide valuable insights for entrepreneurs, policymakers, and academic institutions to implement adaptive strategies for sustainable and inclusive entrepreneurial growth in the era of artificial intelligence.

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Author Biographies

Muhammad Sarfraz Latif, PhD Scholar HRM, University Institute of Management Sciences, PMAS-AAUR, Rawalpindi

PhD Scholar HRM,

University Institute of Management Sciences,

PMAS-AAUR, Rawalpindi

Email: msarfrazlatifpmas@gmail.com

Mansoor Ahmed Soomro, Assistant Professor, Department of Business Administration, Shah Abdul Latif University, Khairpur, Shahdadkot Campus, Sindh, Pakistan.

Assistant Professor,

Department of Business Administration,

Shah Abdul Latif University, Khairpur, Shahdadkot Campus, Sindh, Pakistan.

Email: mansoor.soomro@salu.edu.pk

https://orcid.org/0000-0002-7117-1187

Asif Ahmad, Student, Departamento de Informática, da Escola de Ciências e Tecnologia, Universidade de Évora, Portugal

Student, Departamento de Informática,

da Escola de Ciências e Tecnologia,

Universidade de Évora, Portugal

Email: asifahmad36@gmail.com

https://orcid.org/0009-0009-5538-1633

Muhammad Irfan Syed, Department of Public Administration (DPA), University of Karachi, Karachi

Department of Public Administration (DPA),

University of Karachi, Karachi

Email: misyed@hotmail.com

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Published

29-01-2026

How to Cite

Latif, M. S., Soomro, M. A., Ahmad, A., & Syed, M. I. (2026). Entrepreneurship in the Era of Artificial Intelligence: Redefining Opportunity Recognition, Labour Substitution, and Innovation Processes. Inverge Journal of Social Sciences, 5(1), 173–186. https://doi.org/10.63544/ijss.v5i1.229

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