A live agent spends hours each week manually documenting routine interactions. Another combs through multiple knowledge bases to find the right solution, scrambling to piece it together while the customer waits on hold. A third types out the same response they’ve written dozens of times before.

These repetitive tasks can be draining, leaving less time for meaningful customer interactions—but generative AI is changing this reality. By automating routine workflows, AI augments the efforts of live agents, freeing them to do what they do best: solving complex problems and applying human understanding and empathy to help customers during critical situations.

“Enterprises are trying to rush to figure out how to implement or incorporate generative AI into their business to gain efficiencies,” says Will Fritcher, deputy chief client officer at TP. “But instead of viewing AI as a way to reduce expenses, they should really be looking at it through the lens of enhancing the customer experience and driving value.”

Doing this requires solving two intertwined challenges: empowering live agents by automating routine tasks and ensuring AI outputs remain accurate, reliable, and precise. And the key to both these goals? Striking the right balance between technological innovation and human judgment.

A key role in customer support

Generative AI’s potential impact on customer support is twofold: Customers stand to benefit from faster, more consistent service for simple requests, while
also receiving undivided human attention for complex, emotionally charged situations. For employees, eliminating repetitive tasks boosts job satisfaction and reduces burnout.The tech can also be used to streamline customer support workflows and enhance service quality in various ways, including:

Automated routine inquiries: AI systems handle straightforward customer requests, like resetting passwords or checking account balances.

Real-time assistance: During interactions, AI pulls up contextually relevant resources, suggests responses, and guides live agents to solutions faster.

Fritcher notes that TP is relying on many of these capabilities in its customer support solutions. For instance, AI-powered coaching marries AI-driven metrics with human expertise to provide feedback on 100% of customer interactions, rather than the traditional 2%
to 4% that was monitored pre-generative AI.

Call summaries: By automatically documenting customer interactions, AI saves live agents valuable time that can be reinvested in customer care.

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This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff.

It’s a stormy holiday weekend, and you’ve just received the last notification you want in the busiest travel week of the year: The first leg of your flight is significantly delayed.

You might expect this means you’ll be sitting on hold with airline customer service for half an hour. But this time, the process looks a little different: You have a brief text exchange with the airline’s AI chatbot, which quickly assesses your situation and places you in a priority queue. Shortly after, a human agent takes over, confirms the details, and gets you rebooked on an earlier flight so you can make your connection. You’ll be home in time to enjoy mom’s pot roast.

Generative AI is becoming a key component of business operations and customer service interactions today. According to Salesforce research, three out of five workers (61%) either currently use or plan to use generative AI in their roles. A full 68% of these employees are confident that the technology—which can churn out text, video, image, and audio content almost instantaneously—will enable them to provide more enriching customer experiences.

But the technology isn’t a complete solution—or a replacement for human workers. Sixty percent of the surveyed employees believe that human oversight is indispensable for effective and trustworthy generative AI.

Generative AI enables people and increases efficiencies in business operations, but using it to empower employees will make all the difference. Its full business value will only be achieved when it is used thoughtfully to blend with human empathy, ingenuity, and emotional intelligence.

Generative AI pilots across industries

Though the technology is still nascent, many generative AI use cases are starting to emerge.

In sales and marketing, generative AI can assist with creating targeted ad content, identifying leads, upselling, cross-selling, and providing real-time sales analytics. When used for internal functions like IT, HR, and finance, generative AI can improve help-desk services, simplify recruitment processes, generate job descriptions, assist with onboarding and exit processes, and even write code.

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This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff.