Is Manufacturing Dead? AI's Role in Transforming Jobs and Revitalizing the Industry
Thierry Warin
Digital, Data, and Design (D^3) Institute at Harvard - Data Science for International Business (HEC Montreal) - Harvard Business Analytics Program
Thierry Warin, PhD
In recent years, the debate surrounding the future of manufacturing has intensified, with some arguing that the industry is in irreversible decline due to technological advancements and structural shifts in the global economy. Proponents of this view suggest that the rise of automation and artificial intelligence (AI) has made traditional manufacturing jobs obsolete, contributing to the industrys perceived stagnation (Brynjolfsson & McAfee, 2014). In contrast, others argue that manufacturing is far from dead, contending that AI and automation represent opportunities for transformation rather than demise. This more optimistic perspective highlights the potential of AI to not only enhance productivity but also create new, high-skilled jobs that will sustain the industry in the long term (Autor, 2015; Warin & Jablokov, 2024). Understanding the future of manufacturing requires a nuanced examination of these divergent perspectives.
Manufacturing as a Dying Industry
The argument that manufacturing is in decline is often supported by trends in deindustrialization, particularly in advanced economies. For instance, Brynjolfsson and McAfee (2014) argue that the rise of digital technologies, including automation and AI, has fundamentally altered the economic landscape. They suggest that the displacement of human labor by machines has contributed to a reduction in manufacturing jobs, as many tasks that were once performed by human workers can now be completed more efficiently by automated systems. This shift has led to what they term the "Great Decoupling," where economic productivity increases without a corresponding rise in employment or wage growth.
Similarly, Frey and Osborne (2017) have predicted that many manufacturing jobs are at high risk of automation. In their widely cited study, they estimate that nearly half of all jobs in the U.S. are susceptible to automation, with manufacturing being one of the most vulnerable sectors. As machines become more capable of handling complex tasks, the need for human labor in traditional manufacturing roles diminishes, leading to job displacement and a potential decline in the sector's overall importance. Warin and Jablokov (2024) further highlight that AI-driven automation could shift organizational strategies from "debriefing management," which is reactive, to "briefing management," a forward-looking approach that minimizes human intervention in routine tasks.
Manufacturing as a Transforming Industry
On the other hand, several scholars argue that manufacturing is not dying but evolving, with AI playing a critical role in this transformation. Autor (2015) posits that while automation may displace some jobs, it also creates new opportunities by augmenting human capabilities. Rather than eliminating jobs, AI can lead to the development of new roles that require a blend of technical and cognitive skills, which are essential in the increasingly complex manufacturing processes. In this view, the narrative of job destruction is incomplete without recognizing the complementary nature of AI and human labor in advanced manufacturing.
Furthermore, Jablokov and Warin (2022) argue that AI, particularly in the form of augmented intelligence, shifts the focus back onto human ingenuity by enhancing workers' abilities to analyze and act on complex data. This shift presents an opportunity for more meaningful human-machine collaboration, which could lead to innovations in production processes and the development of entirely new sectors within manufacturing. Moreover, Pratt, Bisson, and Warin (2023) emphasize that the integration of advanced technologies with decision-making frameworks, such as their Decision Intelligence/Data Science (DI/DS) Integration framework, enhances strategic planning in manufacturing, enabling companies to better adapt to shifting market demands.
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Additionally, Bessen (2019) highlights that automation can lead to productivity gains, which, in turn, can stimulate demand for new products and services, creating additional employment opportunities. While specific tasks may be automated, the overall demand for skilled labor in areas such as AI system maintenance, process optimization, and quality control will grow. This perspective suggests that manufacturing is undergoing a profound shift, moving away from labor-intensive production models toward more technology-driven operations. However, this shift does not imply the industry's demise but rather a transformation that requires investment in workforce retraining and new business models.
Conclusion
The question of whether manufacturing is dying remains contentious, with valid arguments on both sides. On the one hand, the rise of automation and AI poses significant challenges to traditional manufacturing jobs, leading to concerns about job displacement and the sector's decline. On the other hand, these same technological advancements offer the potential to reshape and revitalize manufacturing, creating new opportunities for high-skilled employment and greater productivity. As Warin and Jablokov (2024) suggest, this transformation may require a fundamental shift in organizational strategies and workforce development, but it holds promise for the future. Again, leadership and AI literacy are important features. In the context of geopolitical transformations, AI can even be an important risk mitigating technology. The fate of manufacturing will depend on how well industries, governments, and workers adapt to these changes, ensuring that AI and automation are leveraged to augment rather than replace human labor.
References
Autor, D. H. (2015). Why are there still so many jobs? The history and future of workplace automation. Journal of Economic Perspectives, 29(3), 3-30.
Bessen, J. (2019). AI and Jobs: The Role of Demand. NBER Working Paper No. 24235.
Brynjolfsson, E., & McAfee, A. (2014). The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. W.W. Norton & Company.
Frey, C. B., & Osborne, M. A. (2017). The future of employment: How susceptible are jobs to computerization? Technological Forecasting and Social Change, 114, 254-280.
Jablokov, I., & Warin, T. (2022). “How Augmented Intelligence is Bringing the Focus Back on the Human.” California Management Review Insights.
Pratt, L., Bisson, C., & Warin, T. (2023). Bringing advanced technology to strategic decision-making: The Decision Intelligence/Data Science (DI/DS) Integration framework. Futures, 152, 1-11. https://doi.org/10.1016/j.futures.2023.103217 .
Warin, T., & Jablokov, I. (2024). "From Debriefing Management to Briefing Management: Pioneering Future-Oriented Strategies in the Digital Age." California Management Review Insights.