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Research . 2023
License: CC BY
Data sources: Datacite
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Research . 2023
License: CC BY
Data sources: Datacite
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Other literature type . 2023
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What drives UK firms to adopt AI and robotics, and what are the consequences for jobs?

Authors: Hayton, James; Rohenkohl, Bertha; Pissarides, Christopher; Liu, Hong Yu;

What drives UK firms to adopt AI and robotics, and what are the consequences for jobs?

Abstract

Many studies emphasise the potential for widespread job displacement from exposure to AI. Fewer studies also examine the actual impact on job creation, as well as skills demand and the quality of jobs. Since AI may have multiple positive and negative consequences, it is important to know what drives outcomes, and which factors moderate its impact. Drawing upon theories of technology adoption, we present an empirical study of factors influencing decision-maker perceptions of AI, which we hypothesise mediate organisation and environmental factors and adoption. We theorise two moderators for the impact of AI on net job creation, skills demand, and job quality. First, Regional Innovation Readiness reflects the availability of enabling resources in the local environment, in the form of an educated workforce and the connectivity infrastructure. Second, High Involvement HRM is an investment orientation which includes employees in the process of adoption. We test our hypotheses using primary data collected from 1012 organisations across all sectors of the UK economy. We find both Regional Innovation Readiness and High Involvement HRM play a significant role in influencing positive and negative outcomes from AI adoption. We discuss the significant implications for policymakers as well as managers.

Keywords

Artificial Intelligence, Technology Adoption, Innovation Readiness, Human Resource Management

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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