| Summary: | In an era where artificial intelligence (AI) and robotics are transforming business landscapes, this study investigates their impact on firm-level productivity and employment growth, across various industries. We examined the nuanced interplay between automation and key organizational outcomes by employing a combination of text mining and empirical analysis on data spanning 2015 to 2022 from US-listed firms.
The results reveal that while automation adoption is on the rise, its impact on labour productivity and Return on Assets (ROA) does not materialize immediately. This reflects Solow's 'Productivity Paradox' — an initial decline in efficiency post-adoption. Interestingly, automation leads to an initial negative effect on employment growth, suggesting potential labour displacement which may stabilize over time, highlighting the transition towards a workforce that adapts to technological advancements.
Furthermore, our industry-specific analysis shows that the impact of automation is contingent upon each industry's characteristics. Industries characterized by heavy machinery illustrate a clearer pathway towards productivity gains and labour displacement. In contrast to this, others like the tobacco industry encounter decreased productivity alongside increased employment growth, emphasizing the heterogeneity of automation effects.
This paper contributes to the understanding of technological revolution in the 21st century, advocating for strategies that balance technological progress with labour market health. It underscores the importance of long-term planning and adaptability in the face of automation, providing insights for stakeholders and policymakers navigating the complexities of the digital age.
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