Customers are three times more likely to use a third-party generative AI tool than a brand-owned chatbot when they need customer service, according to a Gartner survey of more than 3,500 B2B and B2C customers. The findings signal that many companies' investments in AI-powered support channels may be out of step with actual customer behavior.
Use of third-party generative AI tools has doubled in the past year alone, said Eric Keller, senior director analyst in Gartner's customer service and support practice. In contrast, the number of customers using company-provided chatbots has not increased statistically since 2022. "So a doubling of third-party AI, no increase in customer service chatbots - it definitely should give pause to leaders who are thinking that the future of customer service is in these company-owned AI chatbots," Keller said.
Why customers reach for third-party tools
Two-thirds of consumers now use generative AI in their personal life, work, or both. Most of that usage happens on third-party platforms like ChatGPT and Claude. Keller attributed the preference to both comfort and quality. "They use these tools in every aspect of their life, and they increasingly trust those tools and trust the responses that they get," he said. "So it makes a lot of sense that when they experience a customer service issue, they turn to this tool that they use every day rather than going to a chatbot on a company's website that they don't use often."
Simply adding AI to an existing chatbot won't drive engagement if customers aren't already using it, Keller warned. "If customers are already using your chatbot and engaging with it, then enhancing that chatbot with AI and helping it resolve more issues, that's a good thing," he said. "If customers are not already engaging with your chatbot, simply putting AI in that chatbot is probably not going to drive more engagement. So you really need to drive intentional adoption strategies."
Two areas where brands miss the mark
Gartner's research highlights two specific gaps: the ability to take action and the overall design of the chatbot experience. Well over half of customers (58%) have used generative AI to complete a task, and nearly three-quarters of B2B customers have done so. Brand chatbots, however, often stop at answering questions. If a customer wants to make a change or complete a transaction, the bot typically hands off a link and sends them elsewhere on the site.
"That's where the brand's chatbot is uniquely positioned right now because you can't do that through ChatGPT," Keller said. "But often the brand's chatbot will just simply answer questions. … That's a missed opportunity."
Presentation also needs a rethink. The small chat widget in the corner of the screen "is starting to feel a little outdated," Keller said. Leading organizations are moving toward a model where the entire digital experience becomes an AI-powered conversational interface - a single intelligent front door. Instead of a homepage full of headers and links, the site might open with a search box that asks, "What are you trying to do with us today?"
Why this matters for customer support professionals
For customer support teams, the data challenges the assumption that deploying a branded AI chatbot automatically improves service or reduces workload. The real work lies in aligning tools with how customers actually behave. That means investing in chatbots that can complete transactions - not just answer questions - and rethinking the interface so it feels less like an add-on and more like the primary way to interact. Training resources on AI for Customer Support can help teams build the skills to design and manage these more effective, action-oriented experiences. Without intentional adoption strategies and a design that matches user expectations, even the most advanced chatbot is likely to sit unused.
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