The rise of artificial intelligence in the workplace in Latin America
The adoption of artificial intelligence (AI) in the workplace is increasing significantly in Latin America. Although the region has historically lagged behind in the adoption of new technologies, recent studies show accelerated growth in the use of AI by workers and companies. Countries such as Chile and Argentina present revealing figures: Chile stands out among the regional leaders in AI readiness, while Argentina, despite lagging further behind, shows a steady increase in interest in these tools. Below, we examine current adoption data, the most impacted sectors, key benefits, practical examples, as well as the opinions of different stakeholders and the challenges that accompany this trend.
Recent adoption figures in Latin America
Various reports confirm that AI penetration in the workplace is on the rise in the region, albeit with significant variations by country. A regional study by the employment portal Bumeran reported that Peru leads the way in adoption: 49% of people surveyed in Peru use AI in their daily work tasks, followed by Chile and Ecuador with 36%, Panama with 32%, and Argentina at the bottom with 31%. This places Argentina as the Latin American country with the lowest use of AI in the workplace, while Chile is in the medium-high group, very close to Ecuador and above Panama.
Other surveys show somewhat different figures when measuring the regular use of these tools. Randstad Employer Brand Research 2024, for example, indicates that only 13% of Argentine workers regularly use AI in their jobs, compared to a global average of 29% and a regional average of 26% in Latin America. In Chile, regular use reaches 15% of employees, a percentage similar to that of Europe (17%) and distant from that of North America (31%). These differences suggest that, while almost a third of workers reported having tried or incorporated AI at work, daily and sustained use is still low in many cases.
However, trends indicate accelerated growth. A HelloSafe report highlighted that the use of AI technologies in Latin American companies grew 250% between 2017 and 2022. Furthermore, it is estimated that revenue generated by AI applications in the region could reach $31.2 billion by 2025, reflecting growing business investment and interest. In fact, the Latin American Artificial Intelligence Index (ILIA) published by ECLAC in 2024 places Chile, Brazil, and Uruguay as the leading countries in the implementation of AI in companies, thanks to favorable environments for its development and incorporation. These data confirm that, although adoption is uneven, Latin America is embracing AI and moving toward greater integration of this technology into the world of work.
Sectors leading the use of AI
The impact of AI is not limited to a single industry; it extends to multiple sectors and functional areas within organizations. Initially, disciplines such as marketing and communications were pioneers in adopting these tools—around 16% of marketing professionals in the region already use AI in their work. However, AI has rapidly expanded to other areas. In the field of Human Resources, for example, Argentina reports a 31% adoption rate, while Peru reaches 44%, Ecuador 43%, and Chile 35% of HR professionals are using AI to streamline selection processes, training, or other tasks. This indicates that HR departments are also incorporating AI to improve efficiency in personnel management.
By industry type, a study in Chile identified the information technology, financial services, business services, and commerce sectors as those with the highest adoption of AI in companies. In these industries, AI is used in everything from big data analysis to customer service automation. Within companies, data management, customer service, IT, and marketing are among those that have implemented AI solutions the most. This is consistent with the general perception of workers: more than half consider the IT/Technology sector to be the main beneficiary of AI, followed by management roles (leadership and decision-making). Likewise, customer service and support, administration, market analysis, marketing/advertising, and finance/accounting are mentioned as areas where AI is already playing an important role.
In terms of individual adoption by work area, Marketing and Communications, Sales/Commercial, and Technology/Systems professionals are the most common users of AI in their daily tasks, representing 16%, 14%, and 13% of AI users, respectively, according to Bumeran. In contrast, among those who do not use AI, workers in production, supply, and logistics (17% of non-users) and traditional commercial areas (14%) predominate, suggesting that AI has been slower to adopt in operational sectors. Even so, experts point out that sooner or later AI will penetrate all economic sectors, adapting better to some activities than others depending on the automation possibilities of each task.
Main benefits of AI in the workplace
Organizations and workers already using AI report several key benefits that explain the appeal of these tools. The main contribution noted is increased productivity through more agile and faster tasks. According to the Bumeran regional survey, 47% of workers perceive that AI streamlines tasks, and 46% highlight the time savings its use entails at work. By automating certain repetitive or low-value functions, employees can focus on more strategic tasks, thus increasing overall efficiency.
Related to the above, 41% highlight that AI allows quick access to relevant information, serving as an immediate reference assistant. For example, generative AI tools can summarize long documents or answer specific questions in seconds, saving time-consuming data searches. Similarly, the automation of repetitive tasks—such as data processing, routine report generation, or content classification—is mentioned by 35% of respondents as a tangible benefit. This automation reduces manual workload and decreases human error in routine activities.
Other important benefits include process optimization and increased operational efficiency (reported by approximately one in four workers), along with a reduction in human error thanks to the accuracy of the algorithms. Furthermore, AI makes it possible to analyze complex data at high speed (e.g., for business intelligence), something that 24% particularly valued. Regarding indirect effects, some users noted that AI tools boost innovation (e.g., in content creation), reduce operating costs by automating costly processes, and facilitate the personalization of services for customers. In summary, the most notable benefits revolve around saving time, automating tedious tasks, and improving productivity and informed decision-making, in line with the initial expectations of these technologies.
Concrete examples of AI applications at work
In practice, AI has been incorporated into specific tasks in different types of jobs, offering illustrative examples of its usefulness. According to the Bumeran study, the most common way workers use AI is as an assistant for daily queries: 44% use it to resolve doubts or search for everyday information. This ranges from asking for explanations on a technical topic, obtaining suggestions for a project, to consulting translations or definitions—tasks in which tools such as chatbots or language models are of great help.
Another widespread application is the creation of generative content. 38% of users indicate that they use AI to generate texts, images, videos, or other creative content. For example, marketing professionals can rely on AI to draft articles, advertising slogans, or social media posts; designers can generate reference images; and media outlets are experimenting with automated writing of newsletters or summaries. Similarly, the automation of repetitive tasks (also mentioned by 38%) covers activities such as updating databases, sending scheduled emails, or sorting documents—processes where AI quickly executes tasks that previously required many man-hours.
Thirty-five percent of those who use AI report using it to solve everyday problems at work. This can mean using algorithms to diagnose production line failures, sales predictions to adjust business strategies, or recommenders that help with decision-making (for example, suggesting optimal distribution routes). In fact, in the logistics sector, the Latin American delivery company Rappi implemented AI to optimize delivery routes, reduce wait times, and improve operational efficiency, allowing delivery drivers to complete more orders in less time.
Examples can also be seen in the financial and services sectors. In banking, the deployment of virtual assistants or AI chatbots for customer service is common, answering frequent inquiries 24 hours a day. A notable case is that of Banco Covalto in Mexico, which incorporated generative AI to streamline its credit evaluation processes, reducing loan approval response times by more than 90%. Tasks that previously took days are now completed in minutes, improving the customer experience and internal efficiency. In the consumer services sector, companies across a range of industries (from telecommunications to e-commerce) use intelligent chatbots that personalize user interactions and resolve problems without direct human intervention, except in complex cases.
Other fields are leveraging AI in innovative ways: in fishing and agriculture, predictive models are used to optimize harvests and detect pests early; in healthcare, there are pilot projects where algorithms analyze medical images to assist with diagnoses or manage appointment scheduling; in education, AI-powered platforms adapt content to the student’s learning pace. In short, from factories applying predictive maintenance to machinery to creative teams generating prototypes with AI, concrete examples demonstrate that AI is adding value to specific tasks throughout the Latin American labor market.
Opinions of workers, companies and experts
The rise of AI in the workplace is accompanied by diverse reactions from employees, employers, and specialists. In general, most perceive this trend positively as long as it is managed appropriately. A striking finding is that, even in countries with still low adoption, the assessment of AI tends to be very favorable. For example, 97% of Argentine workers consider the incorporation of AI into their daily tasks “useful or very useful,” despite only 31% actually using it currently. This attitude is echoed in the rest of the region: there is a latent enthusiasm for the possibilities of AI to improve work.
Younger and more highly educated workers stand out as the most enthusiastic and involved with these new tools. According to Andrea Ávila, CEO of Randstad for Argentina, Chile, and Uruguay, the data show that “younger people and those with a higher level of education are the main drivers of this adoption. These groups not only show notable enthusiasm for the benefits that AI offers, but also maintain a more optimistic view of its impact on the workplace.” This suggests a generation that sees AI as an ally and trusts in its potential to open opportunities: in Chile, for example, almost half of workers (49%) believe that learning to use AI will open doors to promotion and professional growth, and an overwhelming 82% feel the need to receive more AI training to improve their future prospects and salaries.
However, concerns and reservations also persist. Some workers fear the effects of AI on job stability or work quality. Recent surveys reveal that around 7% of Chilean workers fear that AI could negatively affect their employment, and in Argentina, 3% openly express that they believe they could lose their jobs due to AI. These figures, although a minority, reflect the presence of anxiety about automation. On the other hand, a segment of employees admits to feeling unprepared: some say they “can’t get used to” using AI or simply “I don’t get along with the technology,” reasons cited by 16% and 12% respectively among those who have not yet used AI in their work. Likewise, 23% say they simply prefer to perform their tasks without AI assistance, which points to personal or cultural preferences at play.
From a business perspective, many leaders recognize the benefits but emphasize the importance of training and strategy. Human Resources specialists surveyed in five Latin American countries point out that the transition to integrating AI “is not always easy,” but they are already seeing positive results in efficiency and work quality. Indeed, companies that have adopted AI highlight competitive advantages: improvements in productivity, cost reduction, and optimization of data-based decision-making. An ECLAC executive, Javier Medina Vázquez, summed up the optimistic sentiment with a note of caution: “The new technological revolution, driven by AI, has the potential to become a key driver of development… AI can drive innovation… but it can also deepen pre-existing socioeconomic gaps if we don’t act quickly, especially in investment, infrastructure, education, and regulation.” In other words, experts see AI as a positive driver as long as it’s accompanied by appropriate policies to avoid unintended impacts.
Ethical, social and labor challenges of AI
Along with the enthusiasm, the rise of AI in the workplace poses significant ethical, social, and labor challenges. One of the biggest fears expressed is the potential loss of jobs due to automation. Forty-three percent of workers surveyed in the region identified job elimination as the main potential disadvantage of AI. This fear of machines replacing people has partly slowed adoption in some companies, especially where there is unclear how to relocate or retrain displaced workers. However, international studies suggest that, at least with current AI capabilities, this risk may be more limited than previously thought: the ILO recently estimated that only between 2% and 5% of jobs in Latin America could be fully automated by generative AI, while between 26% and 38% of jobs are “exposed” to AI to some degree. In most cases, AI will augment or transform tasks within a job rather than eliminate the entire position, potentially improving productivity in up to 14% of jobs. Still, concerns about technological unemployment are real and underscore the need to manage the transition responsibly.
Another critical consideration is overdependence on these technologies. Thirty-five percent of people see it as problematic to become too reliant on AI and lose human skills in the process. Linked to this is the fear of a lack of empathy, understanding, or human intuition in tasks delegated to machines (noted by 31%), as well as the depersonalization of customer service (20%) when we interact with chatbots instead of humans. These are reminders that AI, no matter how efficient, lacks the emotional qualities and human judgment that are vital in many work contexts, from negotiation to caregiving.
Errors and data quality are another aspect: 29% emphasize that AI systems can make mistakes or generate inaccurate results if the data is incomplete or biased. This connects to the issue of algorithmic biases: 14% mentioned the possibility that automated decisions could reproduce pre-existing discrimination or injustice. AI learns from historical data, and if that data contains biases (for example, in recruitment, performance evaluations, credit granting), AI could perpetuate them. Therefore, the ethical challenge of ensuring algorithmic fairness and transparency in workplace environments arises.
Additionally, companies point to practical challenges such as safeguarding data security (26% cited this among the main challenges) and the need for financial and technical resources to implement AI (24%).
Implementing AI solutions requires investment in software, infrastructure, and integration with existing systems, which can be costly, especially for SMEs. It is also crucial to maintain human judgment in decision-making: ensuring that, even if AI provides input or automates parts of the work, final decisions (e.g., hiring someone, approving a loan, diagnosing a patient) are subject to human evaluation when appropriate. Preserving staff creativity and critical thinking is essential to prevent innovation loss or errors in judgment from blindly following AI recommendations.
Faced with these challenges, both specialists and authorities advocate for responsible adoption of AI. This includes training workers to use it effectively (20% of respondents believe that one obstacle is that teams do not yet know how to use AI), updating labor and data protection regulations, and fostering social dialogue on how to distribute productivity gains. From the political sphere, there is an emphasis on the need for clear regulatory frameworks: ensuring ethical use that respects workers’ rights, preventing unjustified mass layoffs, and managing the social impacts of automation. As ECLAC notes, AI can be a catalyst for development, but “it can also deepen gaps… if we don’t act quickly and decisively” on complementary public policies.
In conclusion, artificial intelligence is no longer a distant novelty but an everyday reality in Latin American workplaces, with multiple examples of success across the region. Its benefits in terms of time savings, automation, and productivity are evident and highly valued by both workers and companies. At the same time, there is awareness of the importance of integrating it in a balanced way, without losing sight of the human factor and addressing the legitimate concerns that arise. The challenge going forward will be to harness the transformative potential of AI to drive growth and innovation in Latin America, without neglecting the training of human talent or equity in the workplace. In this way, AI can establish itself as an ally for regional development, rather than a threat, on the path toward the future of work.