As a general-purpose technology, artificial intelligence (AI) is expected to transform almost all industries and aspects of our society. Thus, it is important to understand the potential changes within the firms related to how AI applications change their labor force. Using a panel dataset with over 1,300 publicly-traded companies in China from 2007 to 2018, we examine the relationship between AI applications and firm labor structure with workers with or without formal college education. The study indicates that AI applications were positively associated with the overall employment as well as the employment of nonacademically- trained workers with no college degrees at the firm level. These associations were more significant in the service sector than in the manufacturing sector. Further causal analysis shows increasing AI applications have a positive effect on a firm’s employment of nonacademically-trained workers and its overall employment but a negative effect on academically-trained workers. We attribute the findings to the technology deskilling effect of AI. The findings suggest that, in response to the potential labor force transformation with increasing AI applications, information-systems research needs to focus on structural changes of labor forces and the implications for preparing human employees to work with AI side by side.

A number of studies have investigated the predictability of Chinese stock returns with economic variables. Given the newly emerged dataset from the Internet, this paper investigates whether the Baidu Index can be employed to predict Chinese stock returns. The empirical results show that 1) the Search Frequency of Baidu Index (SFBI) can predict next day’s price changes; 2) the stock prices go up when individual investors pay less attention to the stocks and go down when individual investors pay more attention to the stocks; 3) the trading strategy constructed by shorting on the most SFBI and longing on the least SFBI outperforms the corresponding market index returns without consideration of the transaction costs. These results complement the existing literature on the predictability of Chinese stock returns and have potential implications for asset pricing and risk management.