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While different attempts have been made to use artificial intelligence (AI) to codify communicative behaviors and analyze startups’ video presentations in relation to crowdfunding projects, less is known about other forms of access to entrepreneurial finance, such as video pitches for candidacies into startup accelerators and incubators. This research seeks to demonstrate how AI can enable the startup selection process for both entrepreneurs and investors in terms of video pitch evaluation.

An AI startup (Speechannel) was used to predict the outcomes of startup video presentations by analyzing text, audio, and video data from 294 video pitches sent to a leading European startup accelerator (LUISS EnLabs). 7 investors were also interviewed in Silicon Valley to establish the differences between humans and machines.

This research proves that AI has profound implications with regards to the decision-making process related to fundraising and, in particular, the video pitches of startup accelerators and incubators. Successful entrepreneurs are confident (but not overconfident), engaging in terms of speaking quickly (but also clearly), and emotional (but not overemotional).

This study not only fills the existing research gap but also provides a practical guide on AI-driven video pitch evaluation for entrepreneurs and investors, reshaping the landscape of entrepreneurial finance thanks to AI. On the one hand, entrepreneurs could use this knowledge to modify their behaviors, enabling them to increase their likelihood of being financially backed. On the other hand, investors could use these insights to better rationalize their funding decisions, enabling them to select the most promising startups.

This paper makes a significant contribution by bridging the gap between theoretical research and the practical application of AI in entrepreneurial finance, marking a notable advancement in this field. At a theoretical level, it contributes to research on managerial decision-making processes – particularly those related to the analysis of video presentations in a fundraising context. At a practical level, it offers a model that we called the “AI-enabled video pitch evaluation”, which is used to extract features from the video pitches of startup accelerators and incubators and predict an entrepreneurial project’s success.

The third sector is a producer of trust and positive social interactions, while the mafias destroy trust and social norms. Confiscation of assets and reusing confiscated assets are important tools from an economic and symbolic point of view for contrasting the mafias and promoting a sustainable and fair economy. The purpose of this paper is to analyze the role of the third sector for reusing confiscated assets.

The paper is based on a theoretical analysis of why a third sector role is utilized for reusing confiscated assets, thus focusing on the economic, social and cultural dimensions. Italian legislation and data are presented for showing the relevant and innovative role of the third sector for reusing confiscated assets. A case study of the city of Forlì, based in Northern Italy, is presented and is of particular interest because it is a part of Italy that does not have a historical presence of the mafias. The University of Bologna is now a partner of the project through the Observatory of Legality. Five hectares of confiscated, urban land have been given to two social cooperatives for organic agriculture and social gardening, which are managed by disadvantaged people working in the cooperatives.

The case study offers useful implications for other national and international situations. The results support that the third sector can be an effective partner in managing and restoring the goods to their community.

A suggested focus on a European framework toward a more integrated approach for reusing confiscated assets.

An opportunity for policy decisions to be made toward a stronger approach for reusing confiscated assets via the third sector and civil society actors, starting from positive cases, such as the Forlì case study.

Possibility of a stronger civic engagement for reusing confiscated assets previously owned by mafias.

Scaling up from a pioneering activity to a large-scale network of social enterprises and partnerships could make the difference.