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“Businesses are trying to rush to figure out how to implement or embed generative AI into their business to drive efficiencies,” says Will Fritcher, deputy chief client officer at TP. “But instead of looking at AI as a way to cut costs, they should really be looking at it through the lens of improving the customer experience and increasing value.”
This requires solving two intertwined challenges: empowering living agents by automating routine tasks, and ensuring that AI outputs remain accurate, reliable and precise. And the key to both of these goals? Striking the right balance between technological innovation and human judgement.
Key role in customer support
The potential impact of generative AI on customer service is twofold: customers will benefit from faster, more consistent service for simple requests, while
it also receives undivided human attention for complex, emotionally charged situations. For employees, eliminating repetitive tasks increases job satisfaction and reduces burnout. Technology can also be used to streamline customer support workflows and improve service quality in a variety of ways, including:
Automated routine queries: Artificial intelligence systems handle simple user requests, such as resetting passwords or checking account balances.
Real-time help: During interactions, AI extracts contextually relevant resources, suggests responses, and guides active agents to solutions faster.
Fritcher notes that TP relies on many of these capabilities in its customer service solutions. For example, AI-based coaching combines AI-driven metrics with human expertise to provide feedback on 100% of customer interactions, rather than the traditional 2%.
up to 4% that followed before generative AI.
Call summaries: By automatically documenting customer interactions, AI saves active agents valuable time that can be reinvested in customer care.
This content was created by Insights, the custom content arm of MIT Technology Review. It was not written by the MIT Technology Review editorial staff.
