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Introduction

The infusion of artificial intelligence (AI) into the entrepreneurial landscape marks a transformative era (Robledo et al., 2023) where value creation through innovation is not just an aspiration but a tangible reality. This special issue is devoted to uncovering the multifaceted role of AI in empowering entrepreneurial firms to transition from ideation to value creation. The omnipresence of AI in contemporary entrepreneurial practices has redefined the essence of business operations, strategy formulation, and decision-making processes (Lévesque, Obschonka, & Nambisan, 2022). Its potential in entrepreneurship extends beyond mere automation. Because it promises to revolutionize how entrepreneurs think, conceptualize, strategize, and operationalize business ventures (Nambisan, Wright, & Feldman, 2019). This technological leap presents an intriguing inquiry into how AI can act in practice as a catalyst for transforming creative ideas into profitable ventures. 

While AI’s integration into business operations is common, the current research landscape reveals a significant gap in our understanding of the role of AI in tangible entrepreneurial value creation (Chalmers, MacKenzie, & Carter, 2021; Giuggioli & Pellegrini, 2022; Gupta et al., 2023; Lévesque et al., 2022; Shepherd & Majchrzak, 2022; Short & Short, 2023). First, there is a notable deficiency in comprehensive theoretical frameworks that specifically address the mechanisms through which AI facilitates the transformation of creative ideas into profitable business ventures in entrepreneurial firms. This gap is further widened by the scarcity of empirical studies providing concrete insights into the practical values of AI on entrepreneurial decision-making, strategy development, and overall business growth. Additionally, after integrating AI into the decision-making process, the ethical implications of AI in entrepreneurship are not adequately explored, leaving questions about navigating ethical dilemmas, such as data privacy and algorithmic bias, largely unanswered. 

This special issue aims to bridge several gaps by fostering a multidisciplinary discourse on AI’s role in entrepreneurial value creation. We invite scholars to contribute insights that expand our theoretical understanding of AI in entrepreneurship and offer practical implications for entrepreneurs, investors, and policymakers.

 

List of topic areas

This special issue encourages works from across disciplines and cross-disciplinary collaborations, for example, among information systems and entrepreneurship and technology scholars, as but some examples. Matters of interest include:

1. AI-driven decision support systems have emerged as an essential tool for entrepreneurs, helping them with various decision-making tasks, such as opportunity identification, resource allocation, and risk management (Battisti, Agarwal, & Brem, 2022). However, the effectiveness of AI-driven decision support systems depends on the quality and comprehensiveness of the data used, the appropriateness of the underlying mechanism (Song et al., 2022), and the analytical capability available to entrepreneurs to create values. 
2. AI technologies can potentially transform how entrepreneurs craft strategies and implement them locally and globally. Some studies suggest that AI can facilitate innovation by automating routine tasks, enabling entrepreneurs to focus on creative problem-solving and strategic thinking (Garbuio & Lin, 2021; Nambisan et al., 2019). However, concerns have been raised about the possible displacement of human intuition and creativity in entrepreneurial decision-making due to the over-reliance on AI (Townsend & Hunt, 2019). Redistribution of power and obstruction to knowledge, creativity, and learning could also be observed (Simeonova, 2022).
3. AI applications in entrepreneurship raise ethical concerns, including privacy, data security, and algorithmic bias (Obschonka & Audretsch, 2020). For example, using AI in decision-making can lead to biased outcomes if the underlying algorithms are based on partial data or assumptions, potentially perpetuating existing inequalities (Kleinberg et al., 2018). Moreover, increasing reliance on AI might reduce human agency and accountability in entrepreneurial decision-making (Shrestha, Ben-Menahem, & Von Krogh, 2019). The importance of the decision-making context, tacit knowledge, and the use of AI needs consideration (Simeonova, 2022).
4. The speed of AI’s commercialization far outpaces our conceptual and theoretical development and empirical understanding. There are enormous ramifications. First, how does AI affect the completeness, functioning, and predictions of time-honoured theories of entrepreneurship, strategy, and management? Second, does AI change the boundaries of businesses in ways that affect the theories of the firm? Third, what should a mid-range theory of AI in the entrepreneurial organization consist of?

Several research gaps and opportunities for future exploration exist. For this Special Issue, we strongly encourage authors to think expansively and creatively about their research questions. However, as a primer, topics of interest include, but are not limited to: 

1. The role of AI in the opportunity recognition process: Investigating how AI technologies can facilitate identifying and evaluating novel entrepreneurial opportunities and exploitation for wealth generation at home and abroad. Exploring the balance between the reliance on AI-driven decision-making tools and preserving human intuition, creativity, and judgment in recognizing and creating wealth from new and novel opportunities is counterbalanced by how AI might help individuals act on their creativity in ways previously not thought possible (e.g., encouraging more entrepreneurship). 
2. AI-driven decision support systems: Examining the development, implementation, and effectiveness of AI-driven decision support systems in various entrepreneurial tasks, such as resource allocation and deployment, for achieving competitiveness. Exploring how AI technologies can influence strategic decision-making processes, enhance innovation, and transform the competitive landscape for entrepreneurs. Assessing the values that AI technologies bring in creating and deploying business models.
3. Interconnectedness: Examining the influence of AI on the formation, structure, and dynamics of entrepreneurial ecosystems and networks, including the role of AI in fostering collaboration and cooperation among ecosystem actors. Investigating the influence of AI technologies on team formation, communication and collective decision-making within the entrepreneurial ecosystem to enhance ecosystem performance and cohesion.
4. Ethical value creation: Addressing the ethical concerns, privacy issues, data security, and potential biases in AI algorithms that may arise in entrepreneurial decision-making processes and discussing possible solutions and best practices for responsible AI use. Exploring the potential of AI technologies to support social entrepreneurship, including developing AI-driven solutions to address pressing grand challenges and the implications for social entrepreneurs and stakeholders.
5. Entrepreneurial resilience during uncertainty and risk assessment: Investigating the potential of AI technologies to support entrepreneurs in developing resilience and adaptability when enduring challenges, uncertainties, and changing market conditions, such as economic downturns, noncooperative space, natural calamities, or global pandemics. The potential for AI-driven solutions for risk management, such as AI-driven tools and models for risk identification, evaluation, and mitigation, including the development of AI-driven metrics, benchmarks, and evaluation frameworks for assessing the effectiveness of risk management practices. 

The special issue encourages researchers to use multidisciplinary approaches and explore novel theoretical perspectives and empirical studies to advance the knowledge surrounding AI in entrepreneurship and contribute to developing strategies and best practices for value creation in entrepreneurial venturing.

 

Guest Editors

Dr Md Imtiaz Mostafiz, 
Associate Professor in Strategy and International Business, University of Leicester, UK,
[email protected]
 

Professor Mathew Hughes, 
Schulze Distinguished Professor and Professor of Innovation and Entrepreneurship, University of Leicester, UK,
[email protected] 

Dr Farhad Uddin Ahmed, 
Assistant Professor in Strategy and International Business, School of Business, Maynooth University, Ireland,
[email protected] 

Dr Nazha Gali, 
Assistant Professor of Strategy and Entrepreneurship, Odette School of Business, University of Windsor, Canada.
[email protected] 

Dr Boyka Simeonova, 
Associate Professor of Innovation, School of Business, University of Leicester, UK, 
[email protected]

 

Submissions Information 

Submissions are made using ScholarOne Manuscripts. Registration and access are available by clicking the button below.
Submit your paper here! 
Author guidelines must be strictly followed. 
Authors should select (from the drop-down menu) the special issue title at the appropriate step in the submission process, i.e. in response to “Please select the issue you are submitting to”. 
Submitted articles must not have been previously published, nor should they be under consideration for publication anywhere else, while under review for this journal. 

 

Key Deadlines

Opening date for manuscript submissions: 1 March 2024
Closing date for manuscript submissions: 31 December 2024 
Email for submission queries: [email protected]

 

References 

Battisti, S., Agarwal, N., & Brem, A. (2022). Creating new tech entrepreneurs with digital platforms: Meta-organizations for shared value in data-driven retail ecosystems. Technological Forecasting and Social Change, 175, 121392. 
Chalmers, D., MacKenzie, N. G., & Carter, S. (2021). Artificial intelligence and entrepreneurship: Implications for venture creation in the fourth industrial revolution. Entrepreneurship Theory and Practice, 45(5), 1028-1053. 
Garbuio, M., & Lin, N. (2021). Innovative idea generation in problem finding: Abductive reasoning, cognitive impediments, and the promise of artificial intelligence. Journal of Product Innovation Management, 38(6), 701-725. 
Giuggioli, G., & Pellegrini, M. M. (2022). Artificial intelligence as an enabler for entrepreneurs: a systematic literature review and an agenda for future research. International Journal of Entrepreneurial Behavior & Research. 
Gupta, B. B., Gaurav, A., Panigrahi, P. K., & Arya, V. (2023). Analysis of artificial intelligence-based technologies and approaches on sustainable entrepreneurship. Technological Forecasting and Social Change, 186(2), 122-152. 
Kleinberg, J., Lakkaraju, H., Leskovec, J., Ludwig, J., & Mullainathan, S. (2018). Human decisions and machine predictions. The Quarterly Journal of Economics, 133(1), 237-293. 
Lévesque, M., Obschonka, M., & Nambisan, S. (2022). Pursuing impactful entrepreneurship research using artificial intelligence. Entrepreneurship Theory and Practice, 46(4), 803-832. 
Nambisan, S., Wright, M., & Feldman, M. (2019). The digital transformation of innovation and entrepreneurship: Progress, challenges and key themes. Research Policy, 48(8), 103773. 
Obschonka, M., & Audretsch, D. B. (2020). Artificial intelligence and big data in entrepreneurship: a new era has begun. Small Business Economics, 55(2), 529-539. 
Robledo, S., Grisales Aguirre, A. M., Hughes, M., & Eggers, F. (2023). “Hasta la vista, baby”–will machine learning terminate human literature reviews in entrepreneurship? Journal of Small Business Management, 61(3), 1314-1343. 
Shepherd, D. A., & Majchrzak, A. (2022). Machines augmenting entrepreneurs: Opportunities (and threats) at the Nexus of artificial intelligence and entrepreneurship. Journal of Business Venturing, 37(4), 106227. 
Short, C. E., & Short, J. C. (2023). The artificially intelligent entrepreneur: ChatGPT, prompt engineering, and entrepreneurial rhetoric creation. Journal of Business Venturing Insights, 19, e00388. 
Shrestha, Y. R., Ben-Menahem, S. M., & Von Krogh, G. (2019). Organizational decision-making structures in the age of artificial intelligence. California Management Review, 61(4), 66-83. 
Song, Y., Sahut, J. M., Zhang, Z., Tian, Y., & Hikkerova, L. (2022). The effects of government subsidies on the sustainable innovation of university-industry collaboration. Technological Forecasting and Social Change, 174, 121233. 
Townsend, D. M., & Hunt, R. A. (2019). Entrepreneurial action, creativity, & judgment in the age of artificial intelligence. Journal of Business Venturing Insights, 11, e00126