Buyers Are Pushing Back Against AI

As artificial intelligence continues to transform B2B sales, companies are navigating a delicate balance between leveraging cutting-edge technology and maintaining the authentic human connections that buyers increasingly value, according to new research from Gartner.

While AI-driven solutions offer speed, efficiency, and convenience, especially in the early stages of the sales process, recent analysis suggests that the demand for genuine human engagement is far from diminishing.

In fact, by 2030, three-quarters of B2B buyers will prefer sales experiences that prioritize human interaction over artificial intelligence, Gartner predicts.

“Recent trends in B2B buyer preferences indicate a notable move away from the growing demand for rep-free, digital-only buying experiences. After several years of increasing interest in self-serve and AI-driven sales, we’re now beginning to see a reversal, with more buyers expressing a desire for authentic human engagement, especially in complex or high-stakes transactions,” says Colleen Giblin, a research principal in the Gartner Sales Practice.

“While AI will continue to play a role in streamlining information gathering and presales activities, the enduring value of human interaction is becoming more pronounced,” she says.

Companies have turned to AI, including agentic AI, AI assistants, generative AI, and more, to meet rising buyer expectations while managing or reducing the cost of sales, according to Elizabeth Jones, a senior director analyst in the Gartner Sales Practice.

For buyers, there are benefits, Jones adds, noting that “AI-powered tools can quickly deliver relevant product information, answer common questions, and guide prospects through complex offerings without the need to wait for a human representative. Additionally, AI can personalize recommendations and surface insights based on buyer behavior, making the experience feel more tailored even before a human gets involved.”

And while buyers might appreciate this at first, “as they engage more deeply and the stakes of the transaction rise, the limitations of AI become more apparent,” Giblin says. “The lack of genuine empathy, nuanced understanding, and the subtle cues that characterize human interaction can create a sense of discomfort or mistrust. As a result, buyers may begin to crave the reassurance and personalized touch that only a real human can provide.”

To respond, organizations will likely need to restructure their sales teams, re-emphasizing human roles at critical touchpoints in the buyer journey, Gartner suggests.

This, the firm adds, could mean fewer but more specialized sales roles, with greater investment in training and interpersonal skills, as well as the integration of hybrid models where AI supports but does not replace human expertise.

Gartner also recommends that companies use AI-driven tools for routine, repetitive tasks and early-stage buyer interactions, where speed and access to information are paramount. At the same time, companies should identify key moments in the buyer journey, such as solution customization, negotiations, or deal closure, where human expertise and empathy are most valued, it says further.

“Placing skilled human sellers at these touchpoints ensures that buyers receive the personalized guidance and reassurance they seek,” Jones states.

Gartner also says that companies can offer tiered engagement options, allowing buyers to choose between AI-led or human-led experiences. Additionally, premium pricing for high-touch, human-centric service can be paired with discounts for AI-only engagements, creating flexibility and clear value propositions for customers, the firm says.

“Organizations that recognize and respond to this [shift away from AI] will be better positioned to build trust, foster loyalty, and close more deals,” Giblin concludes.

Self-Service and Live Chat to Be Top Service Tech by 2027

Phone and email will sharply decline in value in favor of digital channels, Gartner finds.

Technologies that support digital-first service will overtake traditional channels like phone and email as the most valuable technologies for customer service and support leaders in the next two years, according to Gartner.

And while artificial intelligence agents are rising in value, they remain outside the top 10 customer service technologies, Gartner found.

“Live chat, self-service portals, and knowledge management systems are solidifying their place as essential tools for fast, scalable support,” says J.J. Moncus, research principal in the Gartner Customer Service & Support Practice. “To stay ahead, customer service leaders must focus on leveraging enhanced analytics, optimizing knowledge management, and using agent assist techniques to enhance the assisted-
service experience.”

Gartner predicts that by the end of this year, 73 percent of customer service organizations will have implemented agent assist solutions for their workforces. With many simple customer service cases now resolved in self-service, the remaining assisted-service interactions are more complex. Agent assist can offer real-time customer insights and prompts, helping agents resolve more complex cases more efficiently and focus on delivering high-quality experiences, the firm says.

“Agent assist can offer both valuable efficiency gains and customer experience benefits,” Moncus states. “There are a wide variety of customer context and guidance use cases that can empower agents to resolve complex issues more easily.”

Gartner also found that while customer service leaders are excited about AI agents, the technology remains outside of the top 10 most valuable technologies and will continue to be for at least the next two years.

“AI agents offer the potential for customer-facing chatbots to take actions on the customer’s behalf, expanding self-service resolution to include a wider variety of issue types,” Moncus says. “Despite this, many customer service leaders remain unconvinced. The technology is still developing, and some leaders are concerned about ‘agent-washing,’ where products are marketed as ‘agentic’ when they are in fact just rule-based.”