ai-pocalypse Recent research details how customer service reps at a Chinese utility’s call center often struggled when trying to use an AI assistant, and were forced to make manual fixes.
Researchers affiliated with a Chinese power utility and several Chinese universities recently conducted a study of how customer service representatives (CSRs) at the power utility’s call center use AI assistance during their interactions with customers. The study is based on 13 semi-structured interviews with service reps, including team leaders and shift supervisors, responsible for handling phone inquiries.
The preprint paper, accepted to the 28th ACM SIGCHI Conference on Computer-Supported Cooperative Work & Social Computing (CSCW) in October, attempts to provide an alternative to assessments of AI geared toward management and customer experience, focusing instead on the workers forced to use AI during customer calls.
One of the findings is that the AI often inaccurately transcribed customer call audio into text thanks to caller accents, pronunciation, and speech speed. The AI also had trouble rendering sequences of numbers accurately, like phone numbers.
“The AI assistant isn’t that smart in reality,” one survey respondent said. “It gives phone numbers in bits and pieces, so I have to manually enter them.”
Another said the AI had trouble transcribing homophones – words that sound the same but have different spellings or meanings.
And the AI’s emotion recognition system worked poorly – it would misclassify normal speech as a negative emotion, had too few categories for classification, and would treat volume level as a sign of poor attitude. As a result, reps mostly ignored the emotional tags created by the AI system and said they had no trouble understanding the caller’s tone.
While reducing basic typing labor, AI-generated outputs introduced structural inefficiencies in information processing
The customer service staffers also found that AI output created redundancies or required corrections. “While reducing basic typing labor, AI-generated outputs introduced structural inefficiencies in information processing because most AI-prefilled content required manual correction or deletion,” the report says.
Text summaries of calls could be useful, the report says, but they often require editing or rewording. What’s more, these transcriptions didn’t necessarily capture key information.
“While the AI enhances work efficiency, it simultaneously increases CSRs’ learning burdens due to the need for extra adaptation and correction,” the report concludes. “The mismatch between technological expectations and actual implementation reflects a common oversight among technology designers, who overestimate efficiency gains while underestimating the implicit learning burdens of adapting to new systems.”
Moreover, there’s an emotional factor that has to be considered, the researchers say. “The service sector presents unique challenges for AI integration due to its emphasis on direct customer engagement and emotional labor,” the study explains, citing potential barriers to AI integration like employee resistance, organizational culture, and the way that AI implementation can increase stress among customer service reps through productivity pressure and concerns about job loss.
In other words, don’t rush to replace those customer service reps quite yet.
This seems to be a growing consensus among the consultancy class as well. In 2023, IT consultancy Gartner predicted that by 2026, organizations would replace 20-30 percent of their customer support staff with generative AI.
Then last month, Gartner revised its forecast, noting that rehiring human agents to replace AI is the current trend: “By 2027, 50 percent of organizations that expected to significantly reduce their customer service workforce will abandon these plans.”
“The human touch remains irreplaceable in many interactions, and organizations must balance technology with human empathy and understanding,” said Kathy Ross, senior director analyst in the Gartner Customer Service & Support practice, in a statement. “A hybrid approach, where AI and human agents work in tandem, is the most effective strategy for delivering exceptional customer experiences.”®
