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GLOBAL TECH LAYOFFS IN THE ERA OF ARTIFICIAL INTELLIGENCE

Nguyen Dang Khoa* 1

1 University of Economics Ho Chi Minh City, Vietnam.
(*E-mail: khoand@ueh.edu.vn)

ABSTRACT
This study examines the global technology sector layoffs from March 2020 to April
2025, analyzing data from 2,863 companies affecting over 808,000 employees. Drawing
on publicly reported layoff events tracked through Bloomberg, TechCrunch, The New York
Times, and San Francisco Business Times, the research employs descriptive statistical
methods and Python-based machine learning visualization tools to identify critical
patterns in workforce reduction across industries, geographies, and company stages. The
findings reveal that the United States accounts for the dominant share of layoffs, with the
hardware industry experiencing the most severe impact. Temporal analysis demonstrates
pronounced spikes in 2023, correlating with macroeconomic shifts including rising
interest rates and post-pandemic normalization, consistent with the bullwhip effect in
labor markets. The study contributes to unemployment research and Sustainable
Development Goals 8 and 9 by providing empirical evidence of labor market disruptions
during economic transitions. The analysis reveals that post-IPO companies bear the
highest absolute layoff volumes, while early-stage startups face elevated vulnerability
during funding constraints. These insights offer valuable implications for workforce
planning, policy formulation, and understanding the relationship between technological
advancement and employment stability in the context of what Schumpeter (1942) termed
creative destruction. Furthermore, the analysis suggests that recent workforce reductions
are not merely cyclical corrections, but structural realignments as companies aggressively
reallocate capital and human resources toward generative AI infrastructure.
Keywords: Tech layoffs; workforce reduction; unemployment; sustainable
development; economic slowdown.

1. Introduction
The global technology sector has experienced unprecedented workforce volatility
between 2020 and 2025, marking a significant departure from the industry's traditional
growth trajectory (Brynjolfsson et al., 2020). What began as pandemic-driven expansion
rapidly transformed into widespread workforce reductions, affecting hundreds of
thousands of employees across multiple continents and industry segments. This
phenomenon presents a crucial case study for understanding modern labor market
dynamics, particularly within knowledge-intensive sectors that have historically
demonstrated resilience during economic downturns (Autor et al., 2003). The confluence
of slow consumer spending, aggressive interest rate increases by central banks, and
strong dollar valuations overseas has created conditions that many economists interpret
as precursors to potential recession, prompting technology firms to implement
substantial workforce reductions.
The magnitude of these layoffs extends beyond simple employment statistics,
touching upon broader questions of economic sustainability, technological disruption,

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