“Enterprises are attempting to hurry to determine the best way to implement or incorporate generative AI into their enterprise to realize efficiencies,” says Will Fritcher, deputy chief shopper officer at TP. “However as a substitute of viewing AI as a method to scale back bills, they need to actually be taking a look at it by way of the lens of enhancing the shopper expertise and driving worth.”
Doing this requires fixing two intertwined challenges: empowering reside brokers by automating routine duties and making certain AI outputs stay correct, dependable, and exact. And the important thing to each these objectives? Placing the correct stability between technological innovation and human judgment.
A key position in buyer assist
Generative AI’s potential influence on buyer assist is twofold: Prospects stand to learn from quicker, extra constant service for easy requests, whereas
additionally receiving undivided human consideration for complicated, emotionally charged conditions. For workers, eliminating repetitive duties boosts job satisfaction and reduces burnout.The tech may also be used to streamline buyer assist workflows and improve service high quality in numerous methods, together with:
Automated routine inquiries: AI programs deal with easy buyer requests, like resetting passwords or checking account balances.
Actual-time help: Throughout interactions, AI pulls up contextually related assets, suggests responses, and guides reside brokers to options quicker.
Fritcher notes that TP is counting on many of those capabilities in its buyer assist options. As an example, AI-powered teaching marries AI-driven metrics with human experience to offer suggestions on 100% of buyer interactions, somewhat than the standard 2%
to 4% that was monitored pre-generative AI.
Name summaries: By mechanically documenting buyer interactions, AI saves reside brokers useful time that may be reinvested in buyer care.
This content material was produced by Insights, the customized content material arm of MIT Know-how Assessment. It was not written by MIT Know-how Assessment’s editorial workers.