Entrepreneurship in the Era of Artificial Intelligence: Redefining Opportunity Recognition, Labour Substitution, and Innovation Processes
Abstrak
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. References Ali, A., & Rafiq-uz-Zaman, M. (2025). 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Penulis (4)
Muhammad Sarfraz Latif
Mansoor Ahmed Soomro
Asif Ahmad
Muhammad Irfan Syed
Akses Cepat
- Tahun Terbit
- 2026
- Bahasa
- en
- Sumber Database
- Semantic Scholar
- DOI
- 10.63544/ijss.v5i1.229
- Akses
- Open Access ✓