AI accelerates cuts: 107 thousand jobs in one year

Global technology companies reduce workforce as AI adoption intensifies.

The wave of job cuts in large corporations does not stop. Between March 2025 and March 2026, at least 107,756 people lost their jobs in layoffs linked to artificial intelligence (AI), according to a count by EL UNIVERSAL.

Global cuts by AI

Siemens was the first: in March 2025 it announced 6,000 layoffs to automate code and engineering tasks. Then Amazon (30,000), Intel (48,900), Meta (1,300) and Microsoft (15,100) joined.

“It is very complicated to put numbers, but for the big companies, it seems to me that they are around 150 thousand,” commented Esteve Almirall, author of ‘When everything changes’.

The Layoffs.fyi site reports that since 2020, more than 450,000 cuts have accumulated in the technology sector globally. In 2026 alone, more than 95 thousand workers have been affected, with an average of 900 layoffs per day. Previously, the cuts were due to post-pandemic overhiring; Now AI is the main driver.

RelatedMass layoffs in Education affect essential services for students

The case of Mexico

In Mexico the impact is still limited. Fernando Senties, CEO of AMITAI, clarifies: “I have not seen many companies in Mexico that are replacing humans with bots… Turnover is reduced in highly administrative positions.” He warns that the loss of employment is not only due to automation, but also due to a broader deterioration of the labor ecosystem, such as the loss of 25 thousand employers in social security.

Ivete Sánchez Bravo points out that AI already has an impact, especially in global or transnational companies. “It is an inevitable trend,” but the challenge is digital literacy. Almirall estimates that the stable integration of AI will take between two and three decades, with tensions and reconfigurations of employment.

Specialists agree: not all layoffs are directly attributable to AI, but rather to a combination of structural and strategic factors.

Satellite Internet, the bet to close the digital divide in Mexico

Mexican geography limits fiber deployment, but low orbit satellites are emerging as an alternative.

Satellite internet as a solution to the digital divide in Mexico

Mountains, jungles and deserts make Mexico one of the countries with the most complex orography in Latin America. Bringing fiber optics to isolated communities implies an investment that is difficult to recover with few users. As a result, one in five households still lack internet access or receive poor service.

Faced with this scenario, low orbit (LEO) satellite internet is emerging as a strategic alternative. “Deploying physical infrastructure in Mexico is expensive due to geography. In many cases, satellite internet represents the most viable option to connect areas where fiber will not reach in the short term,” explains Ernesto Piedras, director of The CIU. Companies like Starlink, with more than 10,300 active satellites, already operate in the country. Since May 2021, it obtained a concession and closed 2024 with 160,631 subscriptions, making Mexico its second Latin American market, only behind Brazil. Starlink has signed contracts with CFE Telecomunicaciones for up to 1,556 million pesos to connect remote communities.

However, cost remains a barrier. While a fiber optic plan costs an average of 544 pesos per month, satellite internet starts at 899 pesos, plus equipment and installation. “Commercially it is still not as viable because it is still more expensive and requires purchasing an antenna whose price remains high,” says Fernando Esquivel, from The CIU. The service makes economic sense when it is shared between communities or companies, and with the support of public policies.

Experts agree that this technology will not replace fiber optics, but will complement it. “Terrestrial services are faster and have lower latency. Satellite communication reaches areas that fixed internet would not reach,” says Hugo Simg, from MediaTek. Deployment also requires regulation and coordination between governments and companies. The race to connect Mexico is no longer only being fought underground, but from space, where a new generation of satellites promises to reduce the digital divide that keeps millions out of the digital world.

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Banks prepare for biometric facial controls in October

Banks claim to be ready for facial biometrics in branches since October.

The main banking institutions in the country claim to be prepared for the new regulations on facial biometric controls when opening accounts, which will come into force next October.

What did the banks declare?

Marcos Ramírez, general director of Grupo Financiero Banorte, pointed out that the institution has made progress to reinforce the identification and security of its users. “We are in time and form with everything established by law and a little ahead, with the prudential limits of the law,” he indicated.

These measures will strengthen control over customer identification. Since 2018, by regulation, fingerprint biometrics are already required to open accounts.

Implementation details

On July 1, the National Banking and Securities Commission (CNBV) incorporated facial biometrics into the regulation for multiple banking in customer identification and authentication. Institutions that opt ​​for this mechanism must comply with technical, operational and security requirements.

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AI detects breast cancer with 90% accuracy

An autonomous model analyzes thermographs and classifies tissues without human intervention.

An artificial intelligence model developed by Raúl Castro Ortega, a researcher at the Polytechnic University of Tulancingo, manages to identify breast cancer with an accuracy of 90%. The results were presented during the SPIE Photonics Europe 2026 International Congress, in Strasbourg, France.

How the system works

The system uses convolutional neural networks with attention mechanisms to analyze breast thermographs. Unlike traditional methods, the model autonomously learns the patterns of healthy and diseased tissue, without a specialist previously defining the characteristics of the images. This reduces processing time and improves consistency of results.

The study, titled “Breast thermography analysis using convolutional neural networks with attention mechanisms,” uses an algorithm based on the heat diffusion equation. This approach focuses analysis on thermogram regions of interest and classifies tissues with high levels of sensitivity and specificity.

Impact on early detection

The accuracy achieved represents a significant advance for the early detection of breast cancer, which can improve survival rates and facilitate timely treatment. The researcher highlighted that the system does not replace the specialist, but rather works as a support tool for faster and more consistent diagnoses.

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