3.27 Million Urban Workers in Colombia Are in Occupations Vulnerable to AI
48.1% of people with jobs in the 23 main cities and metropolitan areas of Colombia work in activities with high exposure to artificial intelligence, although that figure does not mean that those jobs are going to disappear.
That was the main conclusion of the early warning technical report “Artificial intelligence, adaptability, and labor conversion”, prepared by the Colombian Association of Capital Cities (Asocapitales).
Within the group of working people exposed to artificial intelligence, nearly 2.76 million people (22% of the employed) perform jobs that can be strengthened through the incorporation of AI tools, the report adds.
Another 3.27 million (26.1%) are in occupations with high exposure and low complementarity, making them the priority population for adaptation and eventual labor conversion programs.
Exposure to AI does not mean loss of work
The study warns that the impact will initially be concentrated in urban formal employment, especially in administrative tasks, customer service, BPO, accounting, financial services, document review, basic content production, and initial programming.
Women and young people present particular exposure due to their participation in these activities and in entry-level jobs in the labor market, says the report, presented at the Mayors’ Meeting of the Inter-American Development Bank (IDB) Network of Cities.
The research covers a strategic characterization of the 32 capital cities. The quantitative matrix of exposure and labor complementarity uses information from DANE’s Great Integrated Household Survey for 23 cities and metropolitan areas, corresponding to the 2021-2025 period.
“Exposure to artificial intelligence does not mean loss of work, but that a percentage of these jobs has a degree of impact facing this technology,” said Andres Santamaria, general director of Asocapitales. “With this report we are not saying that there is a loss of employment. We are saying that there are opportunities to be more efficient and that it is necessary to improve the technological capabilities of public servants and citizens.”
The cities with highest risk
The territorial measurement indicates that Bogota leads the proportion of employed persons in the category of high exposure and low complementarity, with 28.7%. It is followed by Manizales and its metropolitan area, with 27.9%; and Cali and its metropolitan area, with 26.6%. The average of the 23 cities and metropolitan areas analyzed is 26.1%.
Bogota’s approach has been pointed out as a benchmark by international organizations that accompany cities in their preparation for artificial intelligence. Oliver Wise, from the Bloomberg Center for Government Excellence at Johns Hopkins University, explained why this way of addressing the challenge makes a difference.
“Bogota is moving from analysis to a practical strategy: measuring how work is changing, helping workers develop the necessary capabilities to use AI, and accompanying transitions in those jobs that will likely be most affected,” he stated.
The mayor of Bogota, Carlos Fernando Galan, highlighted the importance of the country’s capitals anticipating the effects of artificial intelligence on employment.
“In Bogota we are very conscious of this challenge and this opportunity. We want to lead this conversation and the implementation of artificial intelligence tools to move toward a city that takes advantage of this technology to provide better services to citizens,” Galan stated.
The challenge also begins from professional training: 43.5% of higher education graduates in 2024 in the 32 capitals (199,447 people) graduated from fields associated with high exposure and low complementarity to AI.
To face the situation, Asocapitales proposes a two-way response: 1) Adaptability: broad training so workers learn to use artificial intelligence, increase their productivity, and remain in their occupations; and 2) labor conversion: targeted pathways of between 3 and 18 months, linked to real vacancies, for those who must transition toward new functions or occupations.
Roadmap to face the situation
According to the report, cities have a decisive window of between 24 and 36 months to organize their response systems. During the first year, each capital should build its local labor risk map, establish agreements with productive sectors, and launch the first training programs.
Asocapitales also asks to create a National System of Adaptability, Anticipation, and Labor Conversion facing artificial intelligence, incorporate a territorial component into the national AI policy, and guarantee continuous measurement of the labor market in the nine capitals that currently do not have sufficient information.
Another proposal involves establishing a competitive territorial labor conversion fund; funding pilots during 2027 and 2028; incorporating this policy into the next National Development Plan; incentivizing companies that train and convert their workers before laying them off; and launching an interoperable information system on skills, vacancies, and career paths.
The document states that mayors’ offices can start immediately through local employment and AI observatories, alliances with the National Learning Service (SENA) and universities, agreements with companies, and programs to train and convert their own officials.
For Asocapitales, this roadmap seeks to ensure that technological transformation translates into opportunities rather than exclusion for the country’s workers.