Generative AI has threatened, or promised, to disrupt every industry out there, and customer service is no exception. In fact, the tech has already found its way into customer care centers. According to an IBM report last August, customer service has become the number one space where executives are looking to implement generative AI, with 85% of executives believing generative AI will be interacting directly with customers over the next two years.
But AI isn’t new to the field.
“We’ve been using AI for quite a long time in our service solutions,” says Jennifer Quinlan, global managing partner and customer transformation consulting services leader at IBM iX.
Of course, chatbots have been available for decades, and anyone who interacted with any corporate “virtual assistant” chat options before 2023 will have encountered some form of AI output. Never mind the back-end systems where AI is used to improve operational efficiency.
Companies typically use chatbots as a first line of customer resolution because they are cheaper than having staff field phone calls. If an automated prompt-and-response bot can point a dissatisfied customer toward a self-service resolution (“fill in this form” or “follow these steps”), it saves valuable man-hours. At least on the corporate side.
From a customer’s perspective (specifically, mine), chatbots are often frustrating tools with a toddler’s capacity for communication. The fact that the end result of successfully prompting one is being told to fix the issue yourself is less than satisfying. Generative AI, at least, might even the scales between customer experience and company expense.
Anyone who’s experimented with the likes of ChatGPT understands its enhanced competence, which would make chatbots more personable and effective. However, there are still kinks waiting to be ironed out.
“We’re working with our clients on how to build trust and transparency [with generative AI] as well as how to monitor and audit those bot-based responses,” Quinlan says. Generative AI is still prone to “hallucinate” and spit out false answers, so letting a bot run unmonitored in place of a real customer service agent could do lasting damage to a brand’s reputation. Quinlan says companies are still “testing and learning” how to deploy generative AI to the frontlines.
But generative AI has a potentially more powerful role to play on the back end of customer service. The tech can summarize customer issues, keeping different tiers of customer service agents informed, and saving the customers from having to repeat themselves.
Generative AI can also help agents scan through reams of policy information to find the best solutions for customer complaints. And, in an example Quinlan provides, it can be used to auto-email customers summaries of their interaction with customer service, so that there’s a record of what action is being taken.
“Generative AI is not meant to replace people,” Quinlan says. “It’s meant to provide information that actually can help [customer service agents] meet the needs of that customer faster, better, and smarter.”
Hopefully that day will come soon.
That’s all from me on the Trust Factor. The newsletter will continue on its regular schedule under the stewardship of a new writer, Nick Rockel.
Thanks for reading,
Eamon Barrett
eamon.barrett@fortune.com
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TRUST EXERCISE
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So concludes Bill Novelli, professor emeritus at the McDonough School of Business at Georgetown University, in an op-ed for Fortune that begins with a look at how the high level of COVID deaths in America can be laid at the feet of distrust. That distrust is fueled by misinformation, which is promulgated by social media, and we still appear to be lacking the tools to parse through it.
