The Future of Work in the Age of Artificial Intelligence

Are We Moving Toward a Society That Will Need Fewer Workers?

In 2026, the future of employment occupies an increasingly prominent place in public debates about artificial intelligence. One question is raising concerns among professionals across different fields: are machines about to replace human workers? For some, we are witnessing a technological revolution capable of bringing about profound transformations in the labor market. For others, artificial intelligence represents another stage in economic evolution, similar to the changes that accompanied the mechanization of factories and the computerization of offices. Between these interpretations lies an even more important question: what will happen to society if a growing share of the activities that justify hiring people can be performed by artificial intelligence systems?

Concerns about the replacement of human labor did not begin with computers. Since the earliest major technological transformations, societies have faced fears that new inventions would make certain professions unnecessary. During the Industrial Revolution, which began in the second half of the eighteenth century, the mechanization of textile production profoundly changed the organization of work. Machines began performing operations previously carried out by artisans, while factories brought together activities that had once taken place in workshops and homes. For many workers, technological progress also represented a threat to economic stability and to the value of the knowledge they had acquired throughout their lives.

Mechanization did not eliminate human labor, but it transformed its nature. Some occupations disappeared or lost importance, while others emerged to meet the needs of an industrial economy. The growth of factories created demand for operators, mechanics, engineers, managers, and skilled workers. Later, electrification, the expansion of transportation, mass production, and the development of telecommunications brought about further reorganizations of professional activities. History therefore shows that technological progress can eliminate certain activities while creating others. However, it does not guarantee that this compensation will occur automatically, at the same pace, or for the benefit of those who have lost their occupations.

Another important aspect of this historical trajectory was the transformation of working hours. During the early stages of industrialization, long workdays were a reality for many workers. Over the following decades, technological development, economic changes, social movements, and the evolution of labor legislation contributed to the gradual reduction of working hours in various industrialized societies. What had once required long hours of physical effort could, in many activities, be accomplished more efficiently through machines and organized processes. This transformation did not occur uniformly, but it revealed an important possibility: increased productivity could allow some of the time previously devoted to work to be allocated to other human activities.

This evolution illustrates a fundamental characteristic of economic progress: producing more does not necessarily require working more. A society capable of producing food, clothing, equipment, and services with less human effort can, in principle, convert part of those productivity gains into free time. However, this possibility depends on economic, social, and political decisions. Technology expands what a society is capable of producing; it does not, by itself, determine how the benefits will be distributed among workers, consumers, and the owners of the means of production.

At the end of the twentieth century, the expansion of computers introduced another transformation. Administrative processes became computerized, banks automated operations, offices replaced physical documents with digital records, and information systems took over repetitive tasks. Occupations related to data entry, manual data processing, and certain bureaucratic operations underwent profound changes. At the same time, new occupations emerged in software development, cybersecurity, data analysis, and systems administration. Technology continued to replace human activities, but it also increased demand for professionals capable of designing, operating, and supervising these new resources.

In the twenty-first century, however, this trajectory takes on a different characteristic. Artificial intelligence is beginning to perform tasks that depend precisely on abilities traditionally associated with human intelligence. For much of history, tools enhanced our physical strength, our speed of movement, and our ability to transform materials. Now, computer systems can analyze information, recognize patterns, produce texts, interpret documents, write software, and propose solutions to different problems. A technology with relatively broad applications is beginning to reach a substantial range of activities associated with intellectual work.

This difference deserves attention. When an industrial machine replaces physical effort, a worker can still rely on cognitive abilities to perform another function. When a computerized system automates a repetitive operation, new responsibilities may emerge in analysis, management, and decision-making. But what happens when analysis itself becomes partially automated? If artificial intelligence can prepare reports, examine documents, interpret financial information, produce content, and assist in developing computer systems, what economic space will remain for professionals whose primary contribution consists precisely of performing these activities?

This does not mean that artificial intelligence possesses all human capabilities, nor has it been demonstrated that it has consciousness or subjective understanding equivalent to that of a person. It means that certain results that once depended on human intellectual labor can now be produced, entirely or partially, through computational processes. For the labor market, this distinction is decisive. An organization does not need to demonstrate that a system thinks or feels like a human being to consider it economically useful. It is enough for the system to perform a particular task with sufficient quality, meet the necessary requirements, and do so at a competitive cost.

This transformation also does not mean that every profession can be fully automated. An occupation generally encompasses different responsibilities, some more easily performed by computer systems and others dependent on human interaction, practical experience, contextual judgment, or professional responsibility. Artificial intelligence can assist a physician in analyzing clinical information without necessarily replacing the full range of responsibilities involved in caring for a patient. It can support a teacher in preparing educational materials without reproducing the full complexity of the human relationships involved in education. Similarly, it can facilitate legal, administrative, and technical activities without automatically eliminating the need for qualified professionals.

However, replacing an entire profession is not the only form of economic transformation. An organization may retain a particular occupation while still reducing the number of professionals needed to perform its associated activities. Imagine a team responsible for analyzing thousands of documents. With artificial intelligence tools, part of the work could be automated, allowing professionals to focus on validating results, investigating exceptions, and making more complex decisions. Depending on the circumstances, the organization could use this capability to expand its services or reduce operating costs. These are different possibilities, and neither can be considered inevitable.

This example reveals an important distinction between productivity and employment. Increased productivity means that a given amount of resources can produce more output, or achieve the same results with fewer resources. This does not necessarily mean a reduction in the number of workers. If demand for services increases, the organization may continue hiring professionals. However, if output remains relatively stable and a growing share of tasks can be automated, the need for new hires may decrease. The impact will depend on economic activity, demand, costs, and the decisions made by organizations.

Another possibility deserves consideration: the transformation of employment may begin not necessarily with the dismissal of experienced professionals, but with a gradual reduction in opportunities to enter the labor market. In many professions, entry-level workers develop their skills through relatively simple tasks before taking on more complex responsibilities. If these activities are progressively automated, organizations will need to reconsider how they train new specialists. In this scenario, a contradiction emerges: how can people gain professional experience if some of the opportunities traditionally used to develop it cease to exist?

Imagine a young person entering university in 2026 who intends to build a career over the next three or four decades. They choose a profession, devote years to academic education, and develop skills considered important by the labor market. However, upon completing their studies, they may encounter a professional environment different from the one that existed when they began their education. Some activities may have been transformed by artificial intelligence systems, while others may require knowledge that was still being developed during their years of study. How can we prepare an entire generation for professions whose responsibilities may change significantly throughout their working lives?

This question does not diminish the importance of education. On the contrary, it increases its responsibility. For generations, academic education has been presented as one of the main instruments of professional development and social mobility. Studying, acquiring specialized knowledge, and developing analytical skills remain important activities. However, in an environment of accelerated technological transformation, professional preparation may increasingly need to emphasize the ability to learn continuously, understand complex problems, adapt knowledge, and exercise critical judgment when facing new situations.

The speed of these transformations also deserves attention. In the past, many industrial changes depended on the construction of factories, the acquisition of equipment, and the reorganization of large production structures. Today, certain artificial intelligence capabilities can be incorporated into professional activities through digital tools. This does not eliminate challenges related to security, reliability, technological integration, and accountability for decisions, but it makes it possible to envision relatively rapid organizational changes in some areas. Society may therefore face adaptation challenges that depend not only on technological evolution, but also on the ability of its institutions to keep pace with these transformations.

It would be premature, however, to conclude that artificial intelligence will cause the widespread disappearance of employment in the near future. Technological evolution does not occur in isolation. It interacts with economic, cultural, demographic, legal, and political factors. Even if an activity can be technically automated, its replacement will depend on costs, reliability, regulation, social acceptance, and human decisions. The ability to perform a task does not necessarily mean that automating it will be practical, desirable, or permitted in every context.

Even so, uncertainty about the future does not diminish the importance of examining possible scenarios. We can imagine an economy in which artificial intelligence continues to expand its capabilities and progressively takes over administrative, technical, creative, and analytical activities. If this process reaches a substantial share of economic production, the question will no longer be simply how many jobs might disappear, but whether it will still be necessary to hire people to perform certain activities. A society may increase its capacity to produce wealth while part of its population struggles to find paid employment.

This scenario requires distinguishing between two ideas that are often confused: work and employment. Work means performing an activity that requires effort, knowledge, or dedication and that may produce some benefit. Employment means participating in an economic relationship in which a particular activity is compensated. Caring for family members, educating children, participating in community initiatives, creating works of art, and developing knowledge are forms of work or social contribution that do not always correspond to formal employment. Therefore, even if the need for paid work were to decline significantly, human activities would not necessarily lose their meaning.

The problem is that the contemporary economic system depends heavily on income derived from work. For millions of people, wages are the primary means of accessing housing, food, transportation, education, and essential services. If artificial intelligence makes it possible to produce more wealth with less human participation, a contradiction may emerge: an economy can expand its productive capacity while simultaneously reducing opportunities for part of the population to earn an income. Increased productivity alone does not guarantee that its benefits will be distributed equitably.

This possibility leads to a fundamental economic question: if human labor is no longer indispensable for producing certain goods and services, how will people gain access to the wealth produced? For a long time, participation in the labor market has been one of the main mechanisms for distributing income. People offer their skills and time in exchange for compensation, using those resources to purchase the products and services they need. A potential structural reduction in the demand for human labor could require a reconsideration of this model.

It is in this context that proposals such as universal basic income deserve consideration. Broadly speaking, the idea is to provide every person with a periodic cash payment, regardless of their employment status and without making it conditional on an obligation to work. Supporters believe that this mechanism could help reduce economic insecurity and expand individual freedom. Critics question its financing, its effects on economic activity, and the ability of a uniform benefit to address the population's diverse needs. This is a complex debate for which no universally accepted solution exists.

In a hypothetical society in which automated systems took over a substantial share of productive activities, alternative mechanisms for distributing income could become more important. However, the feasibility of these proposals would depend on factors such as the economy's productive capacity, sources of financing, the organization of public services, and collective choices. Artificial intelligence, by itself, does not resolve these questions. It may change the economic conditions under which such decisions are made, but it will not automatically determine which social model should prevail.

Another possibility is to use some of the productivity gains to reduce working hours. Rather than employing artificial intelligence exclusively to increase production or lower costs, organizations and societies could consider ways to distribute some of the benefits by reducing the time devoted to professional activities. A shorter workweek, for example, could represent an important change in the relationship between personal life and economic responsibilities, provided that its implementation were compatible with the characteristics of each activity.

This reflection revisits a question that has arisen at different moments in economic history. If technological development has helped reduce the amount of human effort required for production, why could future progress not once again increase the time available for personal life? The answer involves much more than the capabilities of machines. It depends on how society understands productivity, distributes responsibilities, and establishes its economic priorities.

Artificial intelligence may also influence the distribution of wealth among different social groups. Professionals capable of using these technologies to enhance their skills may find new opportunities. On the other hand, people whose activities are easily automated may face difficulties adapting. There is also the possibility that economic benefits will become concentrated among those who control technological resources, infrastructure, and production systems. These hypotheses do not represent inevitable outcomes, but they demonstrate why the evolution of artificial intelligence must also be examined from a social perspective.

To understand the scope of this transformation, consider a personal reflection. Imagine that a significant portion of the activities you perform professionally could be carried out by artificial intelligence. Perhaps a system could analyze documents, identify inconsistencies, produce reports, and offer recommendations in just a few minutes. Initially, this capability could serve as a support tool, allowing you to focus on more complex responsibilities. Over time, however, the same technology could change the number of professionals needed to perform certain tasks. What, then, would be the economic value of your experience?

The answer would depend on numerous factors, including what continued to require human judgment, responsibility, social interaction, contextual knowledge, and other abilities that automated systems could not provide satisfactorily. However, the question reveals an essential distinction: a person's value cannot be reduced to the commercial value of the activities they perform. A professional may accumulate decades of experience, demonstrate responsibility, and contribute significantly to society. Even so, certain tasks performed by that professional may lose economic value when they become automatable.

There is also a psychological and cultural dimension that deserves attention. In contemporary societies, a profession often constitutes an important part of personal identity. When we meet someone, one of the first questions we tend to ask concerns their occupation. Employment structures schedules, establishes social relationships, provides recognition, and influences how each person understands their contribution to the world. A potential structural reduction in the need for paid work would not represent merely an economic transformation. It could profoundly change our perception of personal fulfillment, social usefulness, and belonging.

For a long time, the idea of success has been associated with building a career, achieving financial stability, and gaining professional recognition. For many people, work has become not only a means of survival but also a source of identity. In this context, the possibility of a society that needs fewer workers raises a philosophical question: if a person no longer needs to pursue a profession to ensure their survival, where will they find meaning in their contribution to society?

One possible answer is that the meaning of human existence has never been limited to professional activity. Family relationships, friendship, artistic creation, knowledge, contemplation of nature, and participation in collective life possess values that do not necessarily depend on financial compensation. A society with a greater capacity to produce goods and services using less human effort could, under certain conditions, expand opportunities to devote time to these dimensions of existence.

However, this possibility should not be confused with the idea that a reduction in employment would automatically produce greater freedom. For someone who enjoys economic security, working less may represent an opportunity for personal development. For someone who depends entirely on wages, losing a job may mean insecurity, suffering, and difficulties accessing basic necessities. The difference between these scenarios demonstrates that the social value of a technological transformation depends not only on what it makes possible, but also on the conditions under which its effects are experienced.

The evolution of artificial intelligence may therefore lead to very different outcomes. In certain contexts, it may enhance professional capabilities, help improve services, and reduce the effort required to perform complex tasks. In others, it may create adaptation challenges and change economic opportunities. The consequences will depend on the technologies developed, the decisions made by organizations, and the responses developed by societies.

The debate about the future of employment should not be limited to a confrontation between technological enthusiasm and fear of unemployment. The issue requires understanding both the potential benefits of automation and the challenges that may accompany its expansion. It is not a matter of rejecting progress, but of reflecting on the purpose of that progress and the conditions necessary for its benefits to contribute to collective well-being.

Perhaps employment, as we know it today, will continue to exist for many decades, although profoundly transformed. Perhaps new occupations will emerge to meet needs we cannot yet anticipate. It is also possible to imagine a future in which technological evolution substantially reduces human participation in certain production processes. There is no way to determine with certainty which of these paths will prevail, or how quickly the transformations may occur.

What we can recognize is that the relationship between intelligence, work, and economic survival is undergoing a period of significant change. For thousands of years, human intelligence has enabled us to develop tools, organize societies, and transform our environment. Now, that same intelligence has made it possible to create systems capable of performing a growing share of the intellectual activities that sustain the modern economy. We are facing a transformation that goes beyond replacing tools or modernizing processes and that may change the very foundations of human participation in the production of wealth.

Perhaps the most important question is not whether artificial intelligence will eliminate all jobs, but whether we will be able to build a society in which people's dignity, economic security, and worth do not depend exclusively on how much of their labor the market still needs.

If human intelligence has enabled us to create technologies capable of progressively reducing the need for our own labor, perhaps the greatest challenge of the twenty-first century will be learning to turn this achievement into freedom and shared prosperity, rather than allowing it to become a source of insecurity and exclusion.