Artificial Intelligence (AI) is shaping marketing in an unprecedented way. Empowered by AI, voice assistants are increasingly capable of speaking and listening like humans, offering a great opportunity for a new marketing approach - voice marketing. This research examines how conversation attributes of voice assistants determine consumer trust and intention to engage in voice shopping. Using a sequential mixed-method design, three studies consistently show that consumers perceive the speaking attribute of voice assistants as more human-like than the listening attribute. We find that such incongruency between the two conversation attributes can undermine consumers' trust in voice assistants, leading to reduced willingness to accept product recommendations from voice assistants and shop via voice assistants, which would hamper the development of voice marketing. Accordingly, this research suggests that AI giants with strong technological strength and capital support should distribute more resources to advance the underlying technologies enabling human-like listening (e.g., natural language understanding and voice recognition). But for AI startups with limited financing ability and technical talents, they may consider appropriately reducing investments in the underlying technologies enabling human-like speaking (e.g., natural language generation and voice synthesis) to enhance the congruency level between the conversation attributes of voice assistants.

人工智能 (AI) 正在以前所未有的方式塑造营销。在 AI 的支持下，语音助手越来越能够像人类一样说话和倾听，为新的营销方式——语音营销——提供了绝佳的机会。本研究探讨了语音助手的对话属性如何决定消费者的信任和参与语音购物的意愿。使用顺序混合方法设计，三项研究一致表明，消费者认为语音助手的说话属性比听力属性更像人。我们发现，这两种对话属性之间的这种不一致会破坏消费者对语音助手的信任，导致他们接受语音助手的产品推荐和通过语音助手购物的意愿降低，这将阻碍语音营销的发展。因此，本研究建议拥有强大技术实力和资本支持的人工智能巨头应该分配更多资源来推进能够实现类人聆听的底层技术（例如，自然语言理解和语音识别）。但对于融资能力和技术人才有限的人工智能创业公司，可以考虑适当减少对类人说话的底层技术（如自然语言生成和语音合成）的投入，以增​​强语音助手对话属性之间的一致性。这项研究表明，拥有强大技术实力和资本支持的人工智能巨头应该分配更多资源来推进实现类人聆听的底层技术（例如，自然语言理解和语音识别）。但对于融资能力和技术人才有限的人工智能创业公司，可以考虑适当减少对类人说话的底层技术（如自然语言生成和语音合成）的投入，以增​​强语音助手对话属性之间的一致性。这项研究表明，拥有强大技术实力和资本支持的人工智能巨头应该分配更多资源来推进实现类人聆听的底层技术（例如，自然语言理解和语音识别）。但对于融资能力和技术人才有限的人工智能创业公司，可以考虑适当减少对类人说话的底层技术（如自然语言生成和语音合成）的投入，以增​​强语音助手对话属性之间的一致性。