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While the disruptive potential of artificial intelligence (AI) has been receiving growing consensus with regards to its positive influence on entrepreneurship, there is a clear lack of systematization in academic literature pertaining to this correlation. The current research seeks to explore the impact of AI on entrepreneurship as an enabler for entrepreneurs, taking into account the crucial application of AI within all Industry 4.0 technological paradigms, such as smart factory, the Internet of things (IoT), augmented reality (AR) and blockchain.

A systematic literature review was used to analyze all relevant studies forging connections between AI and entrepreneurship. The cluster interpretation follows a structure that we called the “AI-enabled entrepreneurial process.”

This study proves that AI has profound implications when it comes to entrepreneurship and, in particular, positively impacts entrepreneurs in four ways: through opportunity, decision-making, performance, and education and research.

The framework's practical value is linked to its applications for researchers, entrepreneurs and aspiring entrepreneurs (as well as those acting entrepreneurially within established organizations) who want to unleash the power of AI in an entrepreneurial setting.

This research offers a model through which to interpret the impact of AI on entrepreneurship, systematizing disconnected studies on the topic and arranging contributions into paradigms of entrepreneurial and managerial literature.

For the supply chain to be responsive in the age of globalization, the firm needs to adopt strategies to enable them to meet the changing market needs. Thus, it is essential to adopt automatic replenishment programmes such as vendor-managed inventory (VMI). This study sought to examine the relationship between VMI and operational performance (OP) and the moderation roles of leadership and digitization in the mining sector.

A quantitative approach was used, including primary data collected from industry players in the mining sector in Ghana. A total of 97 industry players were included in the study. Data gathered was analysed using SPSS and LISREL (8.5).

The results indicate that VMI significantly affects OP. However, both digitization and leadership failed to moderate the relationship between VMI and OP.

The study offers mining companies an understanding of VMI applications in their industry. The knowledge will stimulate and improve inventory management practices in the mining industry.

This study is among the first few attempts to understand VMI in the mining industry, especially in the Sub-Saharan Africa context. It presents a detailed understanding of VMI and opportunities for future research.