In October 2026, a report published by RT attributed a warning about the effects of artificial intelligence on the labor market to Kristalina Georgieva, Managing Director of the IMF. According to the article, Georgieva described the phenomenon as a \u201cslow-moving tsunami\u201d and highlighted the importance of paying attention to young people entering the workforce. The comparison should be understood as a metaphor for a gradual transformation that can accumulate significant effects while companies, workers, and institutions attempt to adapt. The central concern is that technological changes may advance faster than societies' ability to respond to them.<\/p>\n\n\n\n The debate surrounding artificial intelligence has evolved in recent years. In addition to asking which professions might disappear, specialists are examining the pace of technological adoption, the distribution of its benefits, and the ability of education systems to train the professionals the economy will need. Therefore, the challenge is not simply to calculate how many jobs might be lost, but also to understand which tasks will change and which skills will become necessary. Public policies and business decisions will influence workers' ability to adapt.<\/p>\n\n\n\n The IMF's warning is not an infallible prediction of the future. The effects of artificial intelligence depend on factors such as implementation costs, technological infrastructure, regulations, and the characteristics of each economic activity. A company may automate certain administrative tasks while simultaneously requiring specialized personnel to supervise its systems or develop new services. The most reasonable approach is to recognize that the labor market may undergo uneven changes and that some people will need more support than others to adapt.<\/p>\n\n\n\n One of the most relevant aspects of the artificial intelligence debate is the situation of young people seeking their first professional opportunity. Traditionally, many graduates begin their careers with relatively simple responsibilities, such as organizing documents, preparing preliminary reports, gathering information, or responding to inquiries. These functions allow them to understand how an organization operates and gain experience before taking on more complex responsibilities. If companies automate some of these activities, the number of vacancies that previously served as entry points into the labor market could decline.<\/p>\n\n\n\n This does not mean that companies will stop hiring young people altogether. However, artificial intelligence could change the requirements for entry-level positions and increase the importance of certain technological skills. Employers may expect new workers to know how to use digital tools, interpret results, and identify errors from the outset. This situation could benefit those who receive adequate training while disadvantaging those who lack access to education or technological resources.<\/p>\n\n\n\n The problem is significant because work experience is often a requirement for obtaining new opportunities. If entry-level positions decline, some young people may struggle to demonstrate their abilities, even after completing a university degree or technical qualification. This could prolong the transition from education to stable employment, although the extent of this effect must be verified through statistics on hiring, youth unemployment, and job vacancies. It would be incorrect to automatically attribute all difficulties faced by young people to artificial intelligence, since economic growth, educational quality, and the conditions of each labor market also play a role.<\/p>\n\n\n\n IMF analyses help explain the potential scale of artificial intelligence's impact on the labor market. In an analysis published in 2024, the organization estimated that approximately 40% of global employment was exposed to the effects of this technology, with a proportion close to 60% in advanced economies and approximately 26% in emerging markets. These figures describe the potential exposure of jobs, not the number of positions that will necessarily disappear. Therefore, they should be interpreted in light of the date, methodology, and categories used in each study.<\/p>\n\n\n\n The expression \u201cexposed jobs\u201d is essential to understanding these estimates. An occupation may be exposed to artificial intelligence because some of its tasks can be automated, but that does not mean the occupation will disappear. In some cases, the technology replaces specific activities; in others, it complements human work, accelerates processes, or allows people to perform higher-value tasks. For example, a professional may use an intelligent system to organize information and spend more time interpreting results and making decisions.<\/p>\n\n\n\n Exposure also varies between countries because of differences in their productive structures. Advanced economies tend to have a higher proportion of administrative, professional, and specialized jobs involving activities that artificial intelligence can perform or support. In many low-income countries, a significant share of the population works in activities requiring physical presence, such as agriculture, construction, and certain personal services. However, lower exposure to some technological applications does not guarantee greater job security, particularly where access to training, connectivity, and investment is limited.<\/p>\n\n\n\n It is also necessary to distinguish between technological exposure and economic vulnerability. A worker may hold a position highly exposed to artificial intelligence and benefit from it if they have the training and opportunities needed to take on complementary responsibilities. Conversely, someone whose occupation has lower exposure may continue to face low wages, informality, or limited professional opportunities. Assessing actual risks requires considering automatable tasks, alternative employment opportunities, and workers' ability to adapt.<\/p>\n\n\n\n Generative artificial intelligence has expanded automation possibilities because it can perform activities requiring certain cognitive skills. Its applications include drafting documents, classifying records, translating texts, conducting preliminary data analysis, and generating code. These tools can be useful in administration, commerce, finance, communications, and software development. However, their effectiveness depends on the complexity of each task, the quality of the available information, and the need to verify results.<\/p>\n\n\n\n Routine tasks may be particularly susceptible to automation when they follow standardized procedures and rely on digital information. This does not mean that all repetitive activities will disappear or that creative professions are entirely protected. In many occupations, artificial intelligence can automate part of the work without eliminating the need for human supervision, experience, and accountability. The transformation will depend on how organizations combine these tools with their employees' capabilities.<\/p>\n\n\n\n In administration, intelligent systems can summarize documents, prepare communications, and organize information. In customer service, virtual assistants can handle frequent inquiries, although exceptional cases may still require human intervention. In programming, artificial intelligence can suggest code snippets and help identify errors, but its outputs require testing and review. These examples demonstrate that automating tasks does not necessarily mean eliminating entire occupations.<\/p>\n\n\n\n Technological expansion can also create new professional needs. Companies may require specialists in data, cybersecurity, systems integration, and automated process supervision. Coordination, communication, and personalized customer service skills may also become more important. However, there is no guarantee that new positions will compensate for all displaced jobs or emerge in the same sectors or regions affected by automation.<\/p>\n\n\n\n One of the main arguments in favor of artificial intelligence is its ability to increase productivity. If a company can produce more goods or provide more services using the same resources, it can reduce costs, improve processes, or devote time to higher-value activities. Under certain conditions, these advances can encourage investment, expand product offerings, and create economic opportunities. However, the results will depend on how productivity gains are used and whether sufficient demand exists for additional services.<\/p>\n\n\n\n The benefits of artificial intelligence are not necessarily distributed evenly. Companies with infrastructure, data, capital, and specialized personnel can adopt these tools more easily than organizations lacking those resources. Similarly, workers with skills that complement the technology may access better opportunities, while those performing easily automated tasks could face greater difficulties. These differences may widen income gaps if educational, labor, and social policies do not promote a more equitable distribution of the benefits.<\/p>\n\n\n\n An IMF staff analysis published in January 2026, titled Bridging Skill Gaps for the Future: New Jobs Creation in the AI Age, examines the relationship between new skills, hiring, and labor market outcomes. The document discusses how demand for certain skills may be associated with better wages and opportunities, while also contributing to potential labor market polarization. This means that some workers may benefit from the transformation while others face obstacles to maintaining their opportunities. These findings do not prove that inequality will inevitably increase, but they highlight the importance of preparing workers.<\/p>\n\n\n\n Differences may also emerge between regions and generations. Cities with stronger universities, connectivity, and digital infrastructure may attract a larger share of technological investment. In contrast, areas with fewer resources may struggle to benefit from artificial intelligence opportunities. Young people with access to better equipment and training programs may also be better positioned than those without such resources. Technological adaptation is therefore also a challenge involving equal access to opportunities.<\/p>\n\n\n\n Developing countries face the challenge of benefiting from artificial intelligence without deepening existing inequalities. Access to the internet, suitable devices, reliable electricity, and technical training influences companies' and workers' ability to adopt these tools. When these conditions are limited, technological adoption may progress more slowly, making its benefits harder to access. Consequently, lower immediate exposure to automation should not be interpreted as a permanent advantage.<\/p>\n\n\n\n In Latin America, the debate has an additional dimension because of the importance of informal employment, educational disparities, and income inequality in many countries. Artificial intelligence could help small businesses organize their operations, improve customer service, and access tools that were previously expensive. At the same time, workers who depend on repetitive administrative activities or digitalizable services could experience changes in their working conditions. The outcome will depend on the pace of adoption, the characteristics of each economy, and institutional capacity to support workers.<\/p>\n\n\n\n Professional training will be essential to reducing the risks associated with technological transformation. Knowledge acquired through initial education remains important, but specific skills may change as new applications emerge. Education systems therefore need to combine a solid foundation of knowledge with opportunities for continuous learning. The objective should not be limited to teaching people how to use a particular tool, but should also involve developing the skills needed to understand it, evaluate it, and adapt to subsequent technologies.<\/p>\n\n\n\n Relevant skills include digital literacy, data interpretation, communication, collaboration, and critical thinking. Understanding the limitations of artificial intelligence is also necessary because these systems can produce incorrect information or incomplete answers. A well-prepared worker must know when a tool can save time and when its results need to be checked against reliable sources. These skills are useful even in occupations that do not require programming or developing technological systems.<\/p>\n\n\n\n In its January 2026 analysis, the IMF reported that approximately one in ten vacancies examined in advanced economies required at least one new skill, compared with close to one in twenty in emerging markets. These figures refer to the vacancies analyzed and do not represent the entire global labor market. Nevertheless, they illustrate the importance of narrowing the gap between the skills companies seek and those candidates possess. Training can facilitate this adaptation, provided it responds to actual needs and offers effective employment opportunities.<\/p>\n\n\n\n Responsibility cannot fall exclusively on workers. Companies can contribute through internal training, professional placements, and mentoring programs that allow employees to learn how to use new tools without excluding those who need time to adapt. Governments can fund reskilling programs and expand access to courses for unemployed people or those in vulnerable jobs. Universities and technical training centers can also strengthen their relationships with businesses while maintaining a broad educational approach that develops both technical knowledge and human skills.<\/p>\n\n\n\n Governments can help ensure that the benefits of artificial intelligence do not depend exclusively on each worker's economic position. One priority is improving labor market information systems to identify changing sectors, in-demand skills, and emerging hiring difficulties. Reliable data can help authorities guide educational programs and design targeted measures for vulnerable groups. Policymakers should also evaluate the results of these initiatives regularly and adjust them when they fail to achieve their intended outcomes.<\/p>\n\n\n\n Another priority is facilitating transitions between jobs. Displaced workers may need career guidance, accessible training, and temporary financial support while searching for new opportunities. For young people, paid internships, apprenticeship programs, and initial work experiences are important because they allow candidates to demonstrate their abilities without requiring years of professional experience. These measures cannot eliminate every risk associated with automation, but they can reduce barriers to entering the labor market.<\/p>\n\n\n\n Regulation will likewise play an important role. Personal data protection, system security, and accountability for automated decisions require attention. When an algorithm participates in candidate selection, for example, it is necessary to examine whether it reproduces biases or unfairly disadvantages certain groups. The challenge is to establish safeguards that protect people without unnecessarily restricting innovation, adapting regulations to the characteristics of each country and industry.<\/p>\n\n\n\n The IMF's warning about artificial intelligence and the labor market highlights a significant challenge, particularly because of its potential consequences for young people seeking their first professional opportunity. Automation can reduce certain routine tasks, change hiring requirements, and put pressure on some wages and occupations. However, estimates of technological exposure are not equivalent to unemployment forecasts, and there is insufficient evidence to present the widespread disappearance of human work as an inevitable outcome. The impact will depend on business decisions, technological developments, and societies' ability to manage the transition.<\/p>\n\n\n\n The main risk is not simply that artificial intelligence may perform tasks previously carried out by people, but that the opportunities and benefits of change may be distributed unequally. If young people lose entry points into employment, workers lack training, and small businesses fall behind, the transformation could widen existing economic gaps. Conversely, a combination of education, investment, social protection, and opportunity creation can help turn technological advances into productivity improvements and new professional activities. The difference between these scenarios will depend largely on the policies and decisions adopted.<\/p>\n\n\n\n Ultimately, addressing this change requires avoiding both the optimism that presents artificial intelligence as an automatic solution to every economic problem and the alarmism that predicts an inevitable employment catastrophe. Institutions must monitor actual data, businesses must take responsibility for training their teams, and education systems must prepare people to learn throughout their professional lives. For young people, the goal should not be to compete with machines in speed, but to develop the skills needed to use and supervise them while contributing human judgment to complex situations. Artificial intelligence will transform many ways of working, but its social consequences will depend on how this transformation is managed and whether the resulting opportunities are accessible to a broad share of the population.<\/p>\n\n\n\n Is your company ready to harness artificial intelligence? At ITD Consulting, we can help you explore technology solutions aligned with your organization's needs, optimize processes, and evaluate digital transformation opportunities. If you would like to learn more about our services and discuss how artificial intelligence can contribute to your company's goals, contact us at<\/strong> info@itdconsulting.com<\/strong><\/a> to request further information.<\/strong><\/p>","protected":false},"excerpt":{"rendered":" Inteligencia artificial y empleo: El desaf\u00edo mundial que amenaza las oportunidades de los j\u00f3venes. ITD Consulting te informa de la situaci\u00f3n.<\/p>","protected":false},"author":5,"featured_media":37569,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[16],"tags":[459,418,576,89,68],"class_list":["post-37565","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-noticias","tag-459","tag-empleo","tag-fmi","tag-ia","tag-seguridad"],"_links":{"self":[{"href":"https:\/\/itdconsulting.com\/en\/wp-json\/wp\/v2\/posts\/37565","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/itdconsulting.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/itdconsulting.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/itdconsulting.com\/en\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"https:\/\/itdconsulting.com\/en\/wp-json\/wp\/v2\/comments?post=37565"}],"version-history":[{"count":1,"href":"https:\/\/itdconsulting.com\/en\/wp-json\/wp\/v2\/posts\/37565\/revisions"}],"predecessor-version":[{"id":37570,"href":"https:\/\/itdconsulting.com\/en\/wp-json\/wp\/v2\/posts\/37565\/revisions\/37570"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/itdconsulting.com\/en\/wp-json\/wp\/v2\/media\/37569"}],"wp:attachment":[{"href":"https:\/\/itdconsulting.com\/en\/wp-json\/wp\/v2\/media?parent=37565"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/itdconsulting.com\/en\/wp-json\/wp\/v2\/categories?post=37565"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/itdconsulting.com\/en\/wp-json\/wp\/v2\/tags?post=37565"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}![\"ITD](\"https:\/\/itdconsulting.com\/wp-content\/uploads\/2026\/10\/itd-consulting-backup-acronis-vds-vps-ciberseguridad-microsoft-365-IA-FMI-1-1024x683.webp\")
<\/figure>\n\n\n\nWhy Young People Could Face Greater Difficulties?<\/strong><\/h2>\n\n\n\n
What Estimates of Labor Market Exposure Mean?<\/strong><\/h2>\n\n\n\n
Professions That Could Experience the Greatest Changes<\/strong><\/h2>\n\n\n\n
![\"Inteligencia](\"https:\/\/itdconsulting.com\/wp-content\/uploads\/2026\/10\/itd-consulting-backup-acronis-vds-vps-ciberseguridad-microsoft-365-IA-FMI-2-1024x572.webp\")
<\/figure>\n\n\n\nProductivity, Wages, and Economic Inequality<\/strong><\/h2>\n\n\n\n
Latin America and the Challenges Facing Peru <\/strong><\/h2>\n\n\n\n
Education and Training for Adapting to Artificial Intelligence<\/strong><\/h2>\n\n\n\n
The Role of Governments and Businesses<\/strong><\/h2>\n\n\n\n
![\"ITD](\"https:\/\/itdconsulting.com\/wp-content\/uploads\/2026\/10\/itd-consulting-backup-acronis-vds-vps-ciberseguridad-microsoft-365-IA-FMI-3-1024x574.webp\")
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