Before ChatGPT revolutionized the world of artificial intelligence, “chatbot” was a bit of a dirty word. For many consumers, a chatbot is a little box in the corner of the screen where a pleasant automated program helps, but then struggles to understand the query and provide the right information.
A November YouGov survey showed that 60% of consumers are at least reasonably confident in their ability to tell the difference between a human customer service agent and a bot. According to data from customer service Callvu, more than 80% of customers are willing to wait for a while (some as long as 11 minutes) to talk to a real person, even though artificial intelligence chatbots are immediately available to platform providers.
But now, new artificial intelligence programs can better understand customers’ needs, search for the right information, and display it in a clear way. On July 31, at the “Wealth Brainstorm Artificial Intelligence Singapore” session sponsored by Accenture, speakers shared some examples of how new artificial intelligence programs can reinvigorate customer service. (Accenture is a founding partner of Brainstorm AI).
Joon-Seong Lee, senior managing director of Accenture’s Center for Advanced Artificial Intelligence, claims that generative AI programs can provide better answers than official customer service chatbots. Lee said Google’s Gemini AI program helped him figure out how to navigate the bank’s system to link one account to another; the bank’s chatbot couldn’t understand the problem.
Li believes that websites need to move away from search mode and users must dig for answers themselves. “You’re not looking for answers. You want answers,” he said.
Sami Mahmal, head of insurance data at Zurich, pointed out that in Indonesia, the company uses artificial intelligence to save customers time.
Indonesian law requires insurance companies to inspect cars before selling insurance to owners. These inspections are usually done in person, meaning the property owner must wait for the appraiser to arrive.
“Can you imagine? You just bought your car. It was second-hand. You had to wait a week for Zurich to arrive at your place.
Now, Zurich is asking customers to submit photos of the cars themselves. Now, automated processes can assess losses and approve the policy or submit it to an assessor for further evaluation.
“We went from a process where we had to wait days and perform manual assessments to a process that can be completed in minutes,” Mahmal said.
Will companies see returns from investing in AI chatbots?
Attendees at Brainstorm AI were interested in the returns they could gain by investing in expensive generative AI programs to improve customer service.
Sinisa Nikolic, Director of High Performance Computing and Artificial Intelligence for Lenovo Asia Pacific, pointed out that while more than 90% of CIOs know that they must make a decision on whether to use artificial intelligence, more than half of them do not know that they should What decision to make.
That means Lenovo’s consultants have to help customers figure out how to help them make decisions. “What are you trying to achieve? Is it efficiency? Is downtime on the production floor reduced? Is it an increase in NPS score to improve customer satisfaction? What exactly are you trying to achieve?” Nikolic said.
Nikolic shared Lenovo’s own experience and pointed out that artificial intelligence has improved Lenovo’s supply chain efficiency by more than 80%.
Mahmal suggested that using “proactive chatbots”—programs that listen to calls and extract important information for human agents without having to search for it—could reduce operating costs by 30% to 50% and reduce call times from 15 to 15 calls. Ten minutes.
Lee proposes a different approach, noting that generative AI can improve a company’s ability to reach customers.
“in the past, [digital marketing companies] There are only 400 to 500 events a month,” he said. Thanks to generative artificial intelligence and hyper-personalization, “they can run thousands of campaigns.”
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