Although AI has rapidly advanced and transformed the startup ecosystem, its inherent complexity and opacity continue to present significant fundraising challenges for startups. This study examines how AI startups signal their value to investors to achieve substantial fundraising outcomes. Adopting a configurational approach and applying Qualitative Comparative Analysis, the research investigates how AI startups leverage various signals to secure investment, with a focus on the context of Initial Coin Offerings (ICOs). Drawing on signalling theory, we differentiate between substantive signals – AI complexity, founding team, and context professionalization – and rhetorical signals, including content complexity, persuasive language, and display of document. By analysing data from 215 ICOs, the study identifies three distinct pathways leading to substantial fundraising amount. These configurations underscore the principle of equifinality, illustrating that both technologically intensive and communication-driven strategies can yield favourable results. Our study contributes to entrepreneurial and signalling research by emphasizing the complementary role of rhetorical signals in reinforcing or substituting substantive signals as well as expanding the application of signalling theory to AI-driven ventures. We also challenge the notion that AI sophistication alone guarantees investor interest, demonstrating that effective leadership and communication can serve as powerful substitutes or complements to advanced technology.
