Before ChatGPT revolutionized the world of AI, “chatbots” was a bit of a dirty word. For many consumers, a chatbot was a little box in the corner of the screen where a cheerful automated program offered to help – but then struggled to understand requests and provide the right information.
According to a November YouGov survey, 60% of consumers are at least somewhat confident in their ability to distinguish a human customer service agent from a robot. And over 80% of customers are willing to wait a certain amount of time — up to 11 minutes for some — to speak to a real person, even if an AI chatbot is immediately available, according to data from Callvu, a customer service platform provider.
However, newer AI programs are now better at understanding customer needs, finding the right information, and presenting it in a readable way. During a breakout session sponsored by Accenture on July 31 at Fortune Brainstorm AI Singapore, speakers presented some examples of how new AI programs could reinvigorate customer service. (Accenture is a founding partner of Brainstorm AI.)
Generative AI programs can provide better answers than official chatbots in customer service, claims Joon-Seong Lee, senior managing director at Accenture’s Center for Advanced AI. Lee said Google’s AI program Gemini helped him figure out how to navigate a bank’s system to link one account to another; the bank’s chatbot didn’t understand the question.
Lee argued that websites need to move away from a search model that relies on users to find answers themselves. “They’re not looking for answers. They want the answer,” he said.
Sami Mahmal, head of data at Zurich Insurance, cited a case in Indonesia where the company used AI to save customers time.
Under Indonesian law, insurers must inspect cars before they can sell the owner an insurance policy. These inspections are usually done in person, meaning the owner must wait until an appraiser is available.
“Can you imagine this? You just bought your car. It’s used. You have to wait a week for Zurich to come to you,” Mahmal said, noting that the wait time can be up to two weeks in some locations.
Zurich is now asking customers to submit photos of the cars themselves. An automated process can now assess the damage and either approve a policy or forward the damage to an appraiser for further assessment.
“We went from a process where we had to wait days and do a manual assessment to something that happens in a few minutes,” Mahmal said.
Will investing in AI chatbots pay off for companies?
Brainstorm AI participants were interested in what return they would get if they invested in expensive generative AI programs to improve their customer service.
While over 90% of chief information officers knew they had to make a decision about using AI, more than half of them had no idea how to make that decision, found Sinisa Nikolic, director of high performance computing and AI at Lenovo Asia Pacific.
That means Lenovo consultants have to help customers figure out how to make that decision. “What do you want to achieve? Is it efficiency? Is it less downtime in manufacturing? Is it an improvement in customer satisfaction NPS scores? What do you want to achieve?” Nikolic said.
Nikolic shared Lenovo’s own experience, noting that AI has increased supply chain efficiency by over 80%.
Mahmal suggested that using “proactive chatbots” – programs that listen in on calls and pull out important information for human agents without them having to search for it – could reduce operating costs by 30 to 50 percent and shorten call times from 15 to 10 minutes.
Lee offered a different approach, noting that generative AI could improve a company’s ability to reach customers.
“In the past, (digital marketing companies) only ran 400 to 500 campaigns a month,” he said. Thanks to generative AI and hyper-personalization, “they can run thousands of campaigns.”
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