Third-party generative AI in customer service is beating brand chatbots: Gartner

Consumers are increasingly turning to third-party generative AI tools like ChatGPT, Claude, and Copilot for customer service, leaving brand-provided chatbots behind. According to a Gartner survey, use of third-party GenAI tools has doubled in the past year, while company-provided chatbot usage has not statistically increased since 2022 Retail Dive. Customers are three times more likely to use a third-party GenAI tool than a brand-owned chatbot to resolve customer service issues Customer Experience Dive.

What happened

Gartner’s survey of more than 3,500 B2B and B2C customers found that two-thirds of consumers now use generative AI in their personal life, work, or both Retail Dive. This usage skews heavily toward third-party tools rather than brand chatbots. Well over half of customers (58%) have used generative AI to complete a task, and nearly three-quarters of B2B buyers have done so. The survey also found that brand chatbots often fail to align with customer behavior: they answer questions but then redirect users to external links for transactions, creating a missed opportunity.

Forward-looking brands are redesigning their digital experiences to function as a single AI-powered front door rather than a standalone chatbot. Instead of a homepage with headers and links, the entire interface becomes a conversational experience. According to the Gartner analyst, leading organizations are replacing navigational layouts with a search box that asks, “What are you trying to do with us today?” Retail Dive.

Why AI builders should care

For AI builders, this shift means the customer service interface is no longer a separate widget but the primary entry point for the entire digital experience. The modern AI front door must handle not just Q&A but also transactions, account updates, and complex workflows within the same conversation. If your chatbot or agent can only answer questions and then link out to a website, you are building a dead end.

There is also a growing tension between the convenience of third-party platforms and the need for data control and direct shopper interaction. As retailers expand onto external AI platforms, they risk losing ownership of customer data and the direct relationship that comes with it Retail Dive. This makes architecture decisions around data governance, model hosting, and platform choice critical for long-term ROI.

Practical implications

To build a competitive AI customer service experience, you need to think beyond the chatbot widget. Design an action-oriented, AI-driven front door that can resolve customer needs within the interface. This means integrating conversational interfaces across all digital touchpoints and enabling tasks like purchases, returns, or account changes without redirecting users to external pages.

A simple but effective pattern is to replace static navigation with an intent-driven prompt. For example, a search box that asks “What are you trying to do with us today?” can guide users to the right action without requiring them to navigate a menu. This approach reduces friction and aligns with how customers already use third-party tools like ChatGPT and Claude.

Caveats

The Gartner findings are based on a survey of customer behavior and industry trends; specific implementations vary by brand and tool. Not all brands have moved to third-party GenAI across the entire customer journey, and the ROI of such a shift depends on adoption rates, task completion, and the quality of the integrated experience. Data security and platform lock-in remain open concerns that require careful architecture planning.