Retail AI's voice agent can adapt during a conversation, learning from user input, which enhances the interaction but still has room for improvement in handling interruptions.

During the deployment process, we work closely with customers to define how their AI agent should respond, including tone and response structure, to meet their specific needs and preferences.

Despite being ambient and operating continuously in the background, responding to events rather than direct human prompts, these agents are not fully autonomous; human interaction is still necessary for approving or rejecting certain actions they take, which sets them apart from traditional chatbots.

Ambient agents have less strict latency requirements compared to chat agents, as they can run for longer periods before needing a response.

The future of AI interactions will likely involve seamless communication throughout daily life, with users engaging with AI for various tasks, including personal conversations and assistance in messaging apps.

Ambient agents can handle more complex operations than chat agents due to their relaxed latency requirements, allowing them to call multiple tools and perform intricate tasks.

AI can adapt its communication style to different audiences, demonstrating empathy and effectively engaging with users of various ages and backgrounds.

The asynchronous nature of AI interactions can significantly improve user experience, especially when models are readily accessible.

Unlike traditional chat agents that require human prompts, ambient agents are triggered by background events, allowing for more simultaneous operations.