“Businesses are trying to quickly figure out how to implement or incorporate generative AI into their business to drive agent efficiency,” says Will Fritcher, Chief Client Officer at TP. “Instead of looking at AI as a way to reduce costs, they should really look at it through the lens of improving the customer experience and increasing value.”
This requires solving two interrelated challenges: empowering live agents by automating routine tasks, and ensuring that AI outputs remain accurate, reliable and precise. And the key to both of these goals? Finding the right balance between technological innovation and human judgment.
Key role in customer support
The potential impact of generative AI on customer support is twofold: Customers can benefit from faster and more consistent service for simple requests, while
also receiving undivided human attention for complex, emotionally charged situations. For employees, eliminating repetitive tasks increases job satisfaction and reduces burnout. This technology can also be used to streamline customer support workflows and improve service quality in a variety of ways, including:
Automated routine queries: AI systems handle simple customer requests, such as resetting passwords or checking account balances.
Real-time support: During interactions, AI retrieves contextually relevant resources, suggests responses, and guides live agents to solutions faster.
Fritcher notes that TP relies on many of these capabilities in its customer support solutions. For example, AI-powered coaching combines AI-driven metrics with human expertise to provide feedback on 100% of customer interactions instead of the traditional 2%.
to 4% that was monitored by pregenerative AI.
Call Summary: By automatically documenting customer interactions, AI saves live agents valuable time that can be reinvested in customer care.
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