GenAI to Cost More Than Offshore Human Agents

Gartner predicts that by 2030, cost per resolution for generative artificial intelligence will exceed $3, higher than many B2C offshore human agents.

Rising data center costs, a pivot from subsidized growth to profitability for AI vendors, and increasingly complex use cases that consume more tokens and require expensive talent will lead to soaring AI costs for customer service organizations, the research firm says in a new report.

“Customer service leaders are determined to use AI to reduce costs, but return on those investments is far from guaranteed,” says Patrick Quinlan, senior director analyst in the Gartner Customer Service and Support practice. “Full automation will be prohibitively expensive for most organizations; instead, leading organizations will use AI to drive customer engagement rather than to cut costs.”

Further predictions include the following:

• By 2028, regulatory changes related to AI will increase assisted service volume by 30 percent.
• Regulatory pressure to ensure the right to talk to a human will result in a surge of assisted-volume interactions as customers exercise their right to opt out of AI. “Regulations mandating easy access to human agents will encourage customers to request a human by default, bypassing AI agents,” Quinlan said. “As a result, organizations will have to maintain or even rehire human agents, possibly at higher numbers or at a higher salary than they previously paid. Failure to maintain appropriate staffing levels could lead to deterioration of the customer experience, with customers waiting for long periods to speak to a human.”
• By 2030, 10 percent of Fortune 500 firms will double customer service spending to use AI for hyperpersonalized, proactive experiences and competitive advantage.

With the cost of genAI rising, most organizations will abandon efforts to cut costs through automation, instead pursuing other goals. A clear differentiation opportunity will emerge for those who leverage AI not just for issue resolution but to create value throughout the customer journey.

“Customer service leaders will turn to AI to improve the customer experience. They’ll look beyond cost optimization to other benefits, such as increasing customer lifetime value, repurchase rate, and brand loyalty,” Quinlan says. “To be successful, organizations must invest in data, technology, and talent. As proactive and personalized service becomes a customer expectation, early adopters will gain competitive advantage.”

Gartner’s prediction that genAI cost per resolution will exceed offshore human agents by 2030 arrives at the same time a different finding, from Qualtrics research, shows that AI customer service is failing at four times the rate of other AI applications, with customers seeing no benefits from it.

“Gartner is documenting the cost side of what we’ve seen on the experience side. Companies today are actively degrading their customer experience in exchange for short-term savings, using AI to cut costs rather than resolve problems,” says Isabelle Zdatny, head of thought leadership at Qualtrics XM Institute. “Our research shows nearly one in five customers see no benefit from AI in customer service, a failure rate four times higher than AI use in general. Organizations betting on AI to cut service costs are making a bad trade on both fronts.”

The real opportunity isn’t making existing processes cheaper, she adds, noting that those efficiency gains are available to everyone. “When AI commoditizes functional performance, human connection becomes the differentiator, not an expense to cut. Companies that use AI to solve customer problems while preserving moments of human connection will separate themselves from competitors still trying to make the old playbook cheaper.”