AI Watch: Adoption of Autonomous Machines

Bruno Carballa Smichowski, Sarah de Nigris (), Néstor Duch Brown and Adrián Moreno María
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Sarah de Nigris: European Commission - JRC, https://joint-research-centre.ec.europa.eu/index_en

No JRC132723, JRC Research Reports from Joint Research Centre

Abstract: This report provides an empirical analysis of the drivers of and barriers to adoption of autonomous machines (AM) technologies by European companies. It also analyses the impact of adopting this technology on firm productivity. Using 2020 survey data from 9 640 firms located in EU27, Norway, Iceland and the UK, we show that AM adoption is driven by several factors and has heterogeneous effects on companies depending on their characteristics. Regarding the drivers of adoption, we find that firm size, employee knowledge of artificial intelligence (AI) and the joint adoption of AM with complementary technologies increase a firm’s probability of adopting AM. Concerning barriers to adoption, we make three main findings. First, the most relevant barriers (cost of adoption and, to a lesser extent, lack of skills and data access) are different for large firms. For the latter, liability and reputation risks, as well as data access, are the most important obstacles. Second, certain types of obstacles (namely liability and reputation risks, data access and lack of funding) are more likely to be present in certain sectors of activity. Third, the more complementary technologies a firm adopts, the lower its probability of facing obstacles to AM adoption. Finally, we find that AM adoption boosts firm productivity. This effect is higher for firms that start out with lower productivity, which suggests that there is a decreasing marginal return to AM adoption in terms of productivity.

Date: 2023-08
New Economics Papers: this item is included in nep-ain, nep-bec, nep-eec, nep-sbm and nep-tid
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