Operational Excellence (OPEX) Insight – Tuesday - February 03, 2026: Widespread Layoffs in the U.S.: Nearly 600,000 Jobs Cut in January 2026.
Góc Nhìn Vận Hành Xuất Sắc – Thứ Ba, Ngày 03/02/2026: Làn Sóng Sa Thải Lan Rộng Tại Mỹ: Gần 600.000 Việc Làm Bị Cắt Trong Tháng 1/2026.
Welcome To Operational Excellence (OPEX) Insight Article For The Paid Subscriber-Only Edition.
This is the bilingual post in English and Vietnamese. Vietnamese is below.
Đây là bài viết song ngữ Anh-Việt. Tiếng Việt ở bên dưới.
English
PART 1 – OFFICIAL INFORMATION
In January 2026, the U.S. labor market witnessed a very large-scale wave of layoffs, with nearly 600,000 jobs eliminated within a single month. This scale is considered the largest since the 2020–2021 period, the peak of the pandemic. However, the critical difference is that this time the drivers are not a traditional economic crisis, but rather operational restructuring, AI adoption, and corporate efficiency optimization strategies.
Aggregated data from corporate announcements, U.S. WARN filings, and global layoff tracking reports show that the layoffs spread across multiple industries, but were most heavily concentrated in technology, logistics, industrial manufacturing, and business services. These sectors are under intense pressure to increase productivity, reduce fixed costs, and redesign operating models as AI is being embedded more deeply into daily operations.
One of the most notable events was Amazon’s announcement of approximately 16,000 corporate job cuts, primarily affecting office-based roles, middle management, and support functions. This move is part of a broader strategy to streamline organizational structure, reduce management layers, and reallocate resources toward AI infrastructure. Amazon emphasized that this decision was aimed at long-term operational efficiency, rather than being a short-term reaction to revenue decline.
In the manufacturing sector, Dow Inc. also announced the elimination of around 4,500 jobs globally, representing more than 10% of its workforce. The company stated that the decision was directly linked to an operational transformation program focused on AI, automation, and value chain optimization, amid rising input costs and intensifying competitive pressure. A significant portion of the impact from these layoffs falls on the U.S. market.
Beyond major technology and industrial players, the logistics and retail sectors have also been clearly affected. UPS, Nike, and several other multinational corporations announced layoffs, hiring freezes, or organizational restructuring, with the objective of cost reduction, operational simplification, and adaptation to shifting market demand. Notably, many of these companies remain profitable, yet are choosing to proactively reduce headcount to enhance efficiency.
A defining characteristic of the early 2026 layoff wave is its proactive and strategic nature. Rather than waiting for an economic downturn, many companies are adjusting in advance, leveraging AI and automation to perform the same volume of work with fewer employees, particularly in repetitive roles, information aggregation functions, and middle-management positions.
Labor experts observe that AI is reshaping organizational structures, not merely by replacing jobs, but by thinning management layers and reducing demand for traditional support roles. As a result, the groups most heavily affected in this wave are white-collar workers, corporate roles, and indirect functions.
Although the official U.S. unemployment rate has not yet fully reflected these developments in the short term, the scale and speed of layoffs in January 2026 indicate that this is not an isolated phenomenon. Most restructuring plans were approved in late 2025 and are now being executed according to predefined roadmaps.
The disappearance of nearly 600,000 jobs in January 2026 reflects a deep and widespread operational adjustment. This is not merely a cyclical economic story, but a clear signal that AI, automation, and efficiency pressure are reshaping the U.S. labor market at a systemic level.
