increase in robot density in developed economies is associated with a 6-percentage point increase in imports from developing economies, and a 12-percentage point increase in exports to these countries. Exploiting differences across countries and industries, Hallward-Driemeier and Nayyar (2019) find that, past a threshold level, the increasing number of robots per 1,000 employees in high-income countries (HICs) is negatively associated with the growth rate of the stock of outbound foreign direct investment (FDI) from HICs to lower-middle-income countries. However, Freund, Mulabdic, and Ruta (2022) find that 3D printing is, on average, supportive of existing trade patterns.

Systematic documentation of how the use of AI affects productivity is still limited, even for advanced economies. AI usage positively contributes to firm productivity in studies using data from Germany and Denmark (Czarnitzki, Fernández, and Rammer 2022; Warzynski forthcoming). There is evidence of a positive correlation between wages and exposure to AI language modeling in the United States (Felten, Raj, and Seamans 2023). At the sector level, machine learning has been found to enhance judicial output and labor productivity (Kleinberg et al. 2018), and to improve doctors’ prediction capacity (Mullainathan and Obermeyer 2022). AI-based digital technologies may allow larger segments of the labor market to improve their productivity if policies support the necessary shift in occupational demand (Ernst, Merola, and Samaan 2018).

As the use of AI is still very limited in most developing economies, empirical work on the productivity impacts of the second wave of digitalization on productivity has hardly begun. One recent study of customer service agents, working predominantly in the Philippines, finds that the use of an AI-based conversational assistant increased the number of customer issues resolved per hour by an average of 14 percent (Brynjolfsson, Li, and Raymond 2023).

# **_2.3. Does digitalization increase capital accumulation?_**

The literature identifies ICT investment as a key factor behind productivity growth in the United States (Jorgenson, Ho, and Stiroh 2002; Oliner and Sichel 2000). Further work highlights the dominance of IT-oriented sectors in driving the pickup in TFP growth observed in the United States during the 1990s (Jorgenson et al. 2007; Jorgenson, Ho, and Stiroh 2008; Stiroh 2002). A series of studies following similar analytical approaches have found similar results for other advanced economies (Vu 2011). The productivity effects of ICT investments have been linked to the investments in intangible capital that comprises computer-related software and data, R&D, design and other properties of innovation, and company competencies such as marketing, firmspecific training, and organization practices (Corrado, Hulten, and Sichel 2005).<sup>8</sup> In their review of the firm-level econometric evidence from the United States, Brynjolfsson and Hitt (2003) argue that the surge in the aggregate productivity statistics during the 2000s reflect the contributions of intangible capital accumulated in the past. This includes complementary “organizational” investment in business process design, job training, customer service, and the like. In another review, Draca, Sadun, and Van Reenen (2009) find that there is a much larger

> 8 There are several economy-wide and industry-level studies on advanced economies, primarily using a growth-accounting approach, that find a positive impact of intangible capital on productivity growth, such as in the United States (Corrado, Hulten, and Sichel 2009); Japan (Fukao et al. 2009); and the Republic of Korea (Chun and Nadiri 2016). Firm-level studies provide additional supporting evidence (Bontempi and Mairesse 2015; Marrocu. Paci, and Pontis 2012; and Di Ubaldo and Siedschlag 2021).

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