Digital technologies, hiring, training, and firm outcomes: Evidence from AI and ICT adoption in Indian firms - Sneha Marydas; Nanditha Mathew; Giordano De Marzo; Carlo Pietrobelli (United Nations University (UNU), Maastricht Economic and Social Research Institute on Innovation and Technology (UNU-MERIT), 2025)
In this study, using a novel dataset that matches firm-level data with online job vacancy data, we investigate the effects of firms' digital technology adoption on future hiring and the dynamics of hiring and training, focusing on different types of technologies and categories of occupations. First, we examine the impact of adopting different types of digital technologies, namely AI, Advanced ICT, and Basic ICT, on future firm hiring. Our findings reveal that less advanced digital jobs (eg. Basic ICT, Advanced ICT) are substituted by more advanced digital jobs (eg. AI), while the advanced technology adoption by firms leads to increased overall hiring of non-digital roles. Second, we show that there is a positive relationship between training and new hiring only for one occupational category, namely, managers, with no significant relationship for other occupations. Third, we investigate the joint effect of training and technology adoption for firm performance. Our findings reveal that digital technology adoption enhances a firm's financial performance only when combined with internal staff training. The sole exception is AI, which yields positive performance benefits even in the absence of training.
Keywords: O33; O12; L20; D22; 330; Digital Technology Adoption; AI; Hiring; Training; Online Job Vacancy Data; Firm Performance