How Gen AI Robots Are Reshaping Services

If you’ve had the chance to ride in a Waymo, you’ve likely emerged from the vehicle amazed by its abilities.  

Waymo is a specific use case of a technology that’s maturing rapidly and set for significant deployment: robots powered by generative AI. Many companies are already using gen AI chatbots, agents, and related technologies to automate and scale up customer service, but in most of these cases customers interact with the technology on screens. Embedding gen AI into robots gives companies the chance to reinvent their interactions with customers in physical settings—restaurants, hotels, hospitals, retail stores, and other brick-and-mortar locations—where service has remained stubbornly human. Using large language models (LLMs), large behavioral models (LBMs), and agentic AI, this new generation of robots can better understand context, make inferences, and provide personalized experiences. They can converse like competent employees—following logic across conversational turns, clarifying ambiguity, and explaining complex ideas simply.

How to Deploy Gen AI Robots.  Bringing a robot into a workplace is more complicated than just unboxing a gadget, because many workplaces are unpredictable—waiters carry trays, doctors and nurses hustle from room to room, and so on. To convert potential into performance, leaders must carefully select use cases, communicate to customers and employees why and how they’re using robots, and set up guardrails. Four critical steps, based on the authors’ observations in the field, can guide them.  Start with use cases that address labor constraints.  Design robot interactions for customer acceptance.  Position robots as service enhancers, not workforce replacements.  And continually update responsible-use guidelines.

Gen-AI-enabled robots provide a practical path toward achieving cost-effective service in the physical world. They can deliver consistency and personalization at scale, which has long been the Achilles’ heel of physical service. But gen AI robots require a complex and lengthy implementation—and because it must take place in real-world settings, the stakes are higher, failures are public, and physical safety becomes a major concern.