48
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AUTOMATION AND THE EMPLOYMENT PARADOX: OECD
EXPERIENCE
Shokirova Gulrukhbonu Bekhzod kizi
Master's student, Department of World Economy
University of World Economy and Diplomacy, Tashkent
e-mail: gulruhshokirova2003@gmail.com
+998330630290
Scientific supervisor: Dr. Umida Sharipova
Head of the International Finance and Investments Faculty
University of World Economy and Diplomacy, Tashkent
e-mail: usharipova@uwed.uz
https://doi.org/
10.5281/zenodo.16964915
ARTICLE INFO
ABSTRACT
Qabul qilindi: 5-avgust 2025 yil
Ma’qullandi: 12-avgust 2025 yil
Nashr qilindi:27-avgust 2025 yil
This article explores the paradox of automation
in OECD countries: while technological transformation
significantly enhances productivity, its employment
effects remain uncertain and uneven. Automation,
artificial intelligence (AI), and robotics create efficiency
gains and new opportunities in digital sectors but
simultaneously displace routine and middle-skill jobs.
This duality reflects the “employment paradox,” where
economic growth does not necessarily translate into
inclusive job creation. Drawing on recent OECD reports
and international studies, the article analyzes how
automation drives productivity, alters labor demand, and
reshapes employment structures. The findings emphasize
the importance of digital skills, lifelong learning, and
institutional adaptability to ensure that automation
contributes not only to efficiency but also to inclusive
labor market development.
KEY WORDS
Automation; employment
paradox; OECD; productivity; labor
market polarization; digital skills
Introduction
Automation has become one of the defining features of modern economies. In OECD countries,
investments in robotics, artificial intelligence, and digital platforms are reshaping production
processes and redefining competitiveness. On the one hand, these technologies drive
efficiency, lower costs, and expand innovation (Brynjolfsson & McAfee, 2014). On the other
hand, they raise concerns about job losses, social inequality, and the future of work (OECD,
2023).
This paradoxical dynamic — rising productivity alongside uncertain employment outcomes
— has sparked wide academic and policy debates. The question is not whether automation
will affect jobs, but how societies can manage its uneven consequences. For OECD countries,
which are global leaders in digital adoption, the issue is particularly pressing.
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Literature Review
Scholars have long debated the relationship between technology and employment. Joseph
Schumpeter described technological progress as a process of “creative destruction,” where
new innovations replace older industries. More recently, Autor, Levy, and Murnane (2003)
argued that digital technologies substitute for routine tasks but complement non-routine,
cognitive skills, producing shifts in labor demand.
OECD (2023) estimates that over one-quarter of jobs in its member states are at high risk of
automation, with many more facing task transformation. Yet, automation does not always
reduce overall employment. Acemoglu and Restrepo (2020) show that industrial robots can
displace certain workers but also generate demand for complementary occupations. The
International Labour Organization (ILO, 2021) adds that digital labor platforms expand access
to flexible work, though often with precarious conditions.
Thus, the paradox is clear: automation boosts productivity but generates both opportunities
and risks for workers.
Automation, Productivity, and Job Displacement
In OECD economies, automation has already reshaped entire industries by significantly
improving productivity, particularly in manufacturing, logistics, and information services. In
manufacturing, industrial robots have reduced the need for repetitive, routine manual tasks
while dramatically increasing precision and efficiency. For instance, the automotive industry
in countries such as Germany, Japan, and South Korea has been transformed by robotic
assembly lines, where automation not only reduces production time but also minimizes errors
and wastage. In logistics, automation has introduced innovations such as automated
warehouses, predictive supply chain management, and the widespread use of robotics in
packaging and delivery systems. Companies like Amazon have used these technologies to set
new global standards in speed and efficiency. In the service sector, digital technologies and AI-
based decision-making tools have streamlined information management, client services, and
data-driven strategies in finance, healthcare, and retail (Brynjolfsson & McAfee, 2014).
The productivity gains from automation are essential for long-term growth and
competitiveness. They allow firms to scale quickly, optimize resource allocation, and reduce
transaction costs. For governments, the adoption of digital technologies is not merely a
technological choice but a strategic necessity, as countries that lag in automation risk losing
competitiveness in global value chains. However, these benefits are not evenly distributed
across the labor market.
Routine-intensive occupations — clerical work, machine operation, and administrative
support — remain the most exposed to automation. These tasks are structured, codifiable,
and therefore easier to replace with machines or software (Autor et al., 2003). Workers who
previously held secure, middle-income positions in these fields now face job insecurity or
displacement. Middle-skill workers, once the backbone of industrial economies, are
increasingly vulnerable, while high-skill and digital professions expand rapidly. This creates
what economists call “labor market polarization” (OECD, 2023).
At the top of the spectrum, high-skill jobs in digital design, software engineering, and data
analysis are booming, supported by strong demand for technical expertise in AI, cloud
computing, and cybersecurity. At the bottom, low-skill service jobs such as care work,
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hospitality, and delivery remain resilient because they require human interaction, empathy,
or physical presence. Yet, these roles often come with low wages, limited benefits, and poor
working conditions (ILO, 2021). Thus, automation deepens inequalities by strengthening the
demand for high-skill workers while pushing many displaced workers into precarious
employment.
The Employment Paradox in OECD Countries
The paradox emerges in the coexistence of rising output and shrinking opportunities for
specific groups of workers. Productivity continues to rise thanks to digitalization, but the
gains are not distributed equally. Instead of generating mass unemployment — as many
feared in earlier automation debates — OECD countries face structural change: high-skill jobs
thrive, low-skill services persist, and middle-skill jobs erode (Acemoglu & Restrepo, 2020).
This structural transformation leads to widening income inequality. High-skilled
professionals, often concentrated in technology hubs and large urban centers, enjoy wage
premiums and job security. In contrast, middle-class workers in traditional manufacturing
towns face declining opportunities, while those moving into low-skill services often
experience downward mobility. This threatens social cohesion and weakens traditional paths
of upward social mobility.
Different OECD countries illustrate the paradox in distinct ways. In the United States,
automation has hollowed out many routine manufacturing jobs, particularly in the Midwest,
while digital services, e-commerce, and logistics networks have expanded rapidly (WEF,
2023). This shift has created regional divides between declining industrial areas and thriving
tech-driven economies. In Germany, the paradox has been managed more inclusively. The
country’s strong vocational training and apprenticeship systems allow workers to retrain and
move into higher-value positions, mitigating the negative impacts of automation (OECD,
2020). Nordic countries provide perhaps the clearest example of how institutional
frameworks can cushion disruptions. With robust welfare systems, universal education, and
continuous reskilling opportunities, they have managed to transform automation into an
opportunity, ensuring that productivity growth translates into more equitable employment
outcomes (Van Ark, 2016).
In short, the paradox of automation is not a uniform outcome but a reflection of how each
country’s institutions, policies, and labor systems respond to technological disruption. OECD
experiences show that automation can coexist with both widening inequality and inclusive
employment — depending on the capacity of societies to adapt.
Policy Responses: Turning Paradox into Opportunity
The OECD experience suggests that automation’s employment paradox is not inevitable. Its
impact depends on how governments, firms, and societies respond. Three policy areas are
particularly important:
1.
Digital skills and lifelong learning.
Workers must adapt to changing labor demand
through continuous reskilling and upskilling (OECD, 2022). Without such investment,
productivity gains will bypass large segments of the workforce.
2.
Inclusive labor institutions.
Strong social protections, flexible labor markets, and
active employment policies can help manage transitions and reduce inequality (ILO, 2021).
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YANGI O'ZBEKISTON ILMIY
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2-JILD,8-SON, (YOʻITJ)
3.
Innovation with equity.
Encouraging the diffusion of digital technologies across small
and medium-sized enterprises (SMEs) and rural areas can prevent the concentration of
productivity benefits in a few large firms or regions (OECD, 2020).
Conclusion
Automation in OECD countries demonstrates the dual nature of technological progress.
Productivity rises sharply, but employment outcomes remain polarized. The paradox lies not
in the technology itself but in the institutional and policy frameworks that shape its adoption.
Countries that invest in digital skills, education, and inclusive labor systems are better able to
transform automation into an opportunity rather than a threat.
For developing economies such as Uzbekistan, the OECD experience offers valuable lessons:
digital transformation must go hand in hand with human capital development and social
protection to ensure that productivity gains translate into inclusive and sustainable
employment growth.
References:
1.
Acemoglu, D., & Restrepo, P. (2020).
Robots and Jobs: Evidence from US Labor
Markets.
Journal of Political Economy, 128(6), 2188–2244.
2.
Autor, D., Levy, F., & Murnane, R. (2003).
The Skill Content of Recent Technological
Change.
Quarterly Journal of Economics, 118(4), 1279–1333.
3.
Brynjolfsson, E., & McAfee, A. (2014).
The Second Machine Age.
W. W. Norton &
Company.
4.
International Labour Organization (ILO). (2021).
World Employment and Social Outlook:
The Role of Digital Labour Platforms.
Geneva: ILO.
5.
OECD. (2020).
Digital Economy Outlook 2020.
Paris: OECD Publishing.
6.
OECD. (2022).
Skills Outlook 2022: Skills for a Resilient Green and Digital
Transition.
Paris: OECD Publishing.
7.
OECD. (2023).
Employment Outlook 2023: Artificial Intelligence and the Labour
Market.
Paris: OECD Publishing.
8.
Van Ark, B. (2016).
The Productivity Paradox of the New Digital Economy.
International
Productivity Monitor, 31, 3–18.
9.
World Economic Forum. (2023).
The Future of Jobs Report 2023.
Geneva: WEF.
