Analyzing the Challenges and Opportunities of Artificial Intelligence on the Development of Entrepreneurship and the Growth of Start-Up Businesses

Autor: Hossein Rahimi Klour, Golsum AkbariArbatan
Jazyk: perština
Rok vydání: 2023
Předmět:
Zdroj: علوم و فنون مدیریت اطلاعات, Vol 9, Iss 4, Pp 205-232 (2023)
Druh dokumentu: article
ISSN: 2476-6658
2476-6534
DOI: 10.22091/stim.2023.9411.1952
Popis: Purpose: In recent years, we have witnessed the emergence of a large number of smart products and services, their commercial availability, and their socio-economic impacts on the world. The use of artificial intelligence can enhance the performance of start-up businesses. Considering the role and impact of artificial intelligence in accelerating entrepreneurship and the development of start-up businesses, the aim of this research is to analyze the challenges and opportunities of artificial intelligence on the development of entrepreneurship and the growth of start-up businesses. Method: This research employs a qualitative approach and a descriptive purpose. It utilizesin-depth semi-structured interviews to develop and validate a conceptual framework using thematic analysis method. The statistical population consists of experts and entrepreneurs in the field of start-up businesses. A total of 12 individuals were purposefully selected to participate in this study. The number of samples follows the principle of saturation. In order to ensure the validity of the research, the respondent method was utilized. A statistical sample of individuals with the necessary knowledge and expertise in the research field was selected to minimize researchers' intervention and to calculate the reliability of the double coding method. The symbol "%" has been used, which is equivalent to 79%. Considering that the reliability level is over 60%, the coding's reliability has been confirmed. It can be asserted that the reliability level of the current interview analysis is appropriate. This article offers some ideas on how to adapt opportunities and practices to emerging AI technologies, including: protecting employee data, ensuring data quality and volume, institutionalizing the appropriate training phase for learning, identifying and modifying patterns, and preventing the input of biased data. Findings: The current research explores the role of artificial intelligence in fostering entrepreneurship and the development of start-up businesses. It discusses the significant impact of artificial intelligence on the growth of entrepreneurship and start-up businesses. Based on the results of interviews with experts and activists, the role of artificial intelligence can be categorized into two main themes: opportunities and challenges. Additionally, there are ten organizing themes that can promote entrepreneurship and business development. The study identified the convergence of technology with entrepreneurial goals, global customer orientation, job value creation, and the resilience of start-up businesses as key factors. It also highlighted five organizing themes, including the talent gap, privacy and security of entrepreneurs, continuous maintenance, and lack of integrated capabilities. Construction and fixed applications are categorized and limited. Finally, after analyzing qualitative data, a paradigm model illustrating the role of artificial intelligence in the development of entrepreneurship and start-up businesses was presented. Conclusion: The world is advancing rapidly with new technologies, making it easy for organizations to make missteps. It is advisable to exercise caution when implementing artificial intelligence services. Adequate insight is necessary for the effective and efficient management of artificial intelligence systems. Today, organizations are grappling with evolving economic, technical, social, cultural, and political conditions. Their ability to survive in such competitive and complex environments depends on their agility and timely, appropriate response to these changes. In the realm of business and startups, artificial intelligence systems are designed to address these challenges and execute tasks effectively. However, their capabilities are limited. The final model of this research can be valuable for implementing and operationalizing artificial intelligence. This study minimized selection bias by employing two independent reviewers who were responsible for study selection and data extraction, and who demonstrated very high agreement in both processes. Considering the opportunities that this study presents, it will initiate an intriguing line of research through in-depth investigation, involving systematic or more targeted experimental studies.
Databáze: Directory of Open Access Journals
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