“Businesses are in a hurry to figure out how to use generative AI to improve their operations,” says Will Fritcher, Deputy Chief Client Officer at TP. “However, instead of seeing AI as merely a cost-cutting tool, they should focus on how it can enhance the customer experience and add value.”
To achieve this, companies need to address two related challenges: using AI to automate routine tasks for live agents and ensuring that AI outputs are accurate, reliable, and precise. The key to success is finding the right balance between technological innovation and human insight.
A Key Role in Customer Support
Generative AI can significantly impact customer support in two main ways. For customers, it means faster and more consistent service for simple requests, while allowing more personal human interaction for complex or sensitive issues. For employees, removing repetitive tasks increases job satisfaction and reduces burnout. Additionally, AI can streamline customer support operations and improve service quality through:
Automated Routine Inquiries: AI systems can manage simple customer requests, like resetting passwords or checking account balances.
Real-Time Assistance: During customer interactions, AI can provide relevant resources, suggest responses, and help agents find solutions more quickly.
Fritcher mentions that TP is leveraging many of these AI capabilities in its customer support strategies. For example, AI-powered coaching combines data-driven insights with human expertise to give feedback on all customer interactions, compared to the traditional 2% to 4% monitored before generative AI.
Call Summaries: AI can automatically document customer interactions, saving agents time that can be better spent on customer care.
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This content was produced by Insights, the custom content division of MIT Technology Review. It was not created by the editorial staff of MIT Technology Review.
