“Enterprises try to hurry to determine easy methods to implement or incorporate generative AI into their enterprise to realize efficiencies,” says Will Fritcher, deputy chief shopper officer at TP. “However as an alternative of viewing AI as a option to cut back bills, they need to actually be taking a look at it by way of the lens of enhancing the client 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 targets? Placing the appropriate steadiness between technological innovation and human judgment.
A key position in buyer assist
Generative AI’s potential affect on buyer assist is twofold: Prospects stand to profit from quicker, extra constant service for easy requests, whereas
additionally receiving undivided human consideration for advanced, emotionally charged conditions. For workers, eliminating repetitive duties boosts job satisfaction and reduces burnout.The tech can be used to streamline buyer assist workflows and improve service high quality in numerous methods, together with:
Automated routine inquiries: AI programs deal with simple 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 illustration, AI-powered teaching marries AI-driven metrics with human experience to supply suggestions on 100% of buyer interactions, moderately than the standard 2%
to 4% that was monitored pre-generative AI.
Name summaries: By mechanically documenting buyer interactions, AI saves reside brokers worthwhile time that may be reinvested in buyer care.
This content material was produced by Insights, the customized content material arm of MIT Expertise Evaluate. It was not written by MIT Expertise Evaluate’s editorial employees.