• artificial intelligence
• empirical analysis
• venture capital

This thesis studies the adoption of AI tools in venture capital operations. A previous analysis of the literature suggests those that are the research questions, which concern the raise in adoption of AI tools in the last years, the screening phase as the one in which AI is useful the most, the factors that predict the adoption of AI tools and the raise in operational efficiency of AI-adopters. Results are based on a questionnaire submitted to European venture capitalists. A qualitative analysis confirmed the results suggested by the literature. Then, an econometric analysis was conducted to see if statistically significant improvement of efficiency could be observed in AI-adopters. Lastly, a prediction model was developed in order to see which factors represent good predictors of the adoption of Artificial Intelligence tools. Results generally support thesis of this work.