After integrating generative AI into their work, the number of customer problems solved by customer service per hour increased by 13.8%, and the time spent on each chat decreased by about 9%. By learning from the experience of excellent employees through AI, "rookie" employees have benefited more.
"The AI era" may have just begun to disrupt various industries.
According to the latest report released by the National Bureau of Economic Research (NBER) in the United States, the emergence of generative AI has greatly improved customer service productivity by 14%, and has been more helpful to "rookies" in the workplace, shortening the time for new employees to get started from 6 months to 2 months.
In the report, NBER pointed out that from November 2020 to February 2021, they tracked 5,000 customer service representatives from a global top 500 software company, analyzed the duration, quality, and results of interactions between customer service and customers after the company introduced generative AI.
Researchers found that with the help of artificial intelligence, customer service representatives can handle more calls per hour and the problem resolution rate has also been further improved.
The measure used in the report is the number of customer problems that customer service representatives can solve per hour. The results show that after integrating generative AI into their work, customer service representatives can solve 13.8% more customer problems per hour.
The report pointed out that the significant increase in productivity can be seen from three different perspectives: 1. Customer service representatives can participate in multiple chats at the same time, reducing the time spent on each chat by about 9%; 2. The number of chats processed per hour has increased by about 14%; 3. The number of successfully resolved chats has increased by about 1.3%.
At the same time, the customer satisfaction index did not show a significant change, indicating that the improvement in productivity did not come at the expense of quality.
The report emphasized that although the communication methods between all employees and customers have changed after using AI, the changes are more significant for poorly performing employees:
This may be because AI to some extent conveys the behavior patterns of excellent employees to new and "rookie" employees. The developers of AI tools found that high-performing employees can identify potential problems twice as fast as low-performing employees based on customer descriptions.
AI tools are trained by learning the best practices and linking specific query phrases with problems and potential solutions.
AI tools can also obtain feedback more frequently than human customer service representatives. This gives new and poorly performing employees the opportunity to improve their own problems faster, and AI can be updated and iterated after each call.
Writer, an AI platform, also recently released a survey report on generative AI tools. The survey results show that more than half of the respondents said that the use of generative AI tools will increase productivity by at least 50%.
Among them, 85% of the respondents said that generative AI can increase productivity by at least 25%; 56% of the respondents said that it will increase by at least 50% or more; and about 26% of the respondents believe that it will increase by 75% or more. The core driving force of enterprise AI software is to reduce costs and increase efficiency:
23% of respondents said that the biggest advantage of generative AI is to improve productivity; 22% said that the biggest advantage is higher quality output; 20% said that it saves costs. Only 6% of respondents said that there are no benefits.
Survey shows that in terms of improving output quality, marketing and technology industries are the biggest beneficiaries. This is mainly because the frequency, attribute fit, and application scope of ChatGPT and other generative AI in these two industries are higher than in other fields.
Goldman Sachs previously pointed out in a report that the AI wave will become an important driver of global productivity, and global productivity will increase by more than 1.5% per year in the next 10 years, driving $7 trillion in economic growth: Knowledge workers' value creation today is closely related to their ability to use computers, including desktops, tablets, and smartphones. With the help of generative AI, knowledge workers can more easily use these platforms and simplify the user experience.
The advent of computers and software automation marked the first opportunity for a significant increase in productivity. However, the output of any analyst 20 years ago was vastly different from today's delivery level. This difference is driven by advances in software and hardware technology, which allow us to save more time and access information more easily.
Goldman Sachs' macro team estimates that generative AI can become a booster for US labor productivity growth, with productivity expected to increase by 1.5% per year over the next 10 years of generative AI development.
