This study explores how Generative Artificial Intelligence (Gen AI) aids in crafting targeted messages for investors by modifying non-native entrepreneurs’ language behaviors in crowdfunding campaigns, specifically their accent and language. Drawing upon Language Expectancy Theory, we adopt an experimental vignette methodology across three studies, using Gen AI to tailor non-native entrepreneurs’ language and accents within the US investor market. Our results indicate that pitches with Gen AI-modified language and accents align more closely with the investor’s preferences attract greater investor interest. Specifically, we observe positive expectancy violations when both linguistic elements and accents were concurrently tailored. Our findings suggest that Gen AI can more effectively mitigate language-based behavioral biases encountered by non-native entrepreneurs, thereby helping to level the playing field in the crowdfunding market. Our research contributes to the nascent field of Gen AI in entrepreneurship, offering both theoretical and practical insights.
