What is it about?

------------------------ Research Focus ------------------------ This study is dedicated to delivering novel insights on how entrepreneurs can use AI and ML to assist with their central tasks during the opportunity recognition and exploitation phases of venturing. We review literature at the intersection of AI and entrepreneurship, develop an integrative framework that helps entrepreneurs leverage the analytic power of AI, and provide guidance for future research avenues on this fast-evolving phenomenon of the enabling role of AI for entrepreneurial decisions and actions in highly uncertain contexts.

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Why is it important?

------------------------------------------------------- Contribution to Academic Scholarship ------------------------------------------------------- We explore the potential of Artificial Intelligence (AI) as a general-purpose technology to enhance and augment entrepreneurial decision-making and activities during the venturing process. Entrepreneurship constitutes a vital activity for the dynamic economic evolution and creates and nurture multiple critical drivers for evolving business ecosystems. Despite its critical importance, the process of entrepreneurial venturing remains a highly uncertain activity. Nascent entrepreneurs face substantial risks and uncertainty levels, as their venturing decisions and action often occur in ill-structured and fast-changing information environments The recent rapid advancement of AI may help cope with uncertainty by alleviating the complexity of data analysis in entrepreneurial decision-making. AI comprises ML, which stands for the capability of algorithms to learn from large datasets during problem-solving tasks. AI provides a powerful way to automatize data interpretation, gain insights from this data, and achieve intended goals. However, to date, entrepreneurship scholars have paid only scant attention to the role and impact of AI on the entrepreneurial venturing process. AI can be understood as an encompassing label for emerging technologies that rely on exponentially growing machine capacities to mimic and reproduce human cognition for accomplishing specific routinized tasks. We define for this study AI as the set of technologies that seeks inspiration from human intelligence to perform tasks commonly associated with the human mind. Given the rapid evolution of AI-based technologies, this straightforward definition accommodates various possible future developments for algorithm-enhanced decision-making in entrepreneurship. In this article, we primarily focus on ML techniques that learn from structured data, that is, labelled inputs such as sales figures or unstructured data, that is, unlabeled inputs such as texts, to envision what AI may be able to do to assist entrepreneurs in their core routine tasks. n general terms, the entrepreneurial process consists of a discovery, exploitation phase (and entrepreneurial phases. We outline below several ways AI can assist entrepreneurs in their reasoning and decision-making across these three phases of the venturing process. Discovery phase: In the discovery phase, entrepreneurs intend to start a business but have yet to seek to do so actively. During the discovery phase, AI systems can help entrepreneurial decisions by enhancing opportunity-related search processes, given their ability to analyze large amounts of structured and unstructured data to see patterns imperceptible to human minds. Exploitation phase: Following the exploration phase, the exploitation phase concerns the entrepreneurial decisions and actions taken to pursue and seize identified economic opportunities effectively. Here again, AI can help speed up the processes linked to exploitation. At the funding stage, AI-based tools such as Smartwriter provide cost-efficient solutions for automating the creation of personalized emails to promote new products within target communities of users and attract attention from potential investors (Mileva, 2022). AI-based platforms can also help automate Customer Relationship Management. NLP and sentiment analysis tools can assist with managing the online reputation of the newly established entity. Entrepreneurial phase: The entrepreneurial phase involves organizing the daily routines of the newly established entity to ensure that the new product or service is delivered to customers and income flows in to cover costs. The rapid development of deep-learning approaches in ML opens opportunities to deploy AI solutions concerning these inherent tasks in the entrepreneurial phase. AI-based deep learning tools can automate many organizational processes across the primary functions. ------------------------------------------------------- Contribution to Management Practice ------------------------------------------------------- Our study offers practical recommendations by shedding light on the conceptual baseline and constituent dimensions of the topic of AI as an enabler for entrepreneurial venturing. It becomes clear that integrating AI into entrepreneuring is simultaneously promising and challenging, as it touches multiple aspects in the interrelated dimensions of process, structure, content, and model development. For example, exciting and important questions arise for AI-enhanced ventures regarding decision-making and judgement in entrepreneurial venturing. How can entrepreneurs effectively and responsibly balance the tensions between automation vs augmentation of entrepreneurial decision-making in the different phases of venture creation? How can they reasonably judge AI's various risks and benefits by involving stakeholders and creating strategic approaches to technology integration? We likewise see the topic of AI-enhanced business model design and strategy as critical to addressing further AI-driven entrepreneurship. How and to which degree can AI capacities help create unique value propositions by supporting inimitable interdependencies among value creation and value capture activities? To which extent are AI-enhanced business model configurations transferable across different business contexts and industries? The access to and use of AI resources in entrepreneurial ecosystems represents a third promising avenue for practical exploration. AI applications as a shared resource in a network of ventures lead to resource access and sharing questions amongst entrepreneurial actors. Moreover, how can entrepreneurs individually and collectively handle the power of prominent AI players influencing the dynamics of ventures in entrepreneurial ecosystems?


We provide an integrative perspective of essential dimensions and future research avenues for the topic of AI as an enabler for entrepreneurial venturing. Our study identifies and elaborates upon constituent dimensions and interrelations, which are crucial to theorize further the potentials and challenges determining the effective use of AI in entrepreneuring.

Full Professor Dirk Schneckenberg
ESC Rennes School of Business

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This page is a summary of: Guest editorial: Artificial intelligence as an enabler for entrepreneurs: an integrative perspective and future research directions, International Journal of Entrepreneurial Behaviour & Research, May 2023, Emerald, DOI: 10.1108/ijebr-04-2023-033.
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