Mexico is increasing the supply of technology training
In January 2026, the ATDT announced the launch of the Public Artificial Intelligence Training Center with 10,000 students.
The program was designed to develop skills in high-demand technology areas and establish links with academic institutions and technology companies.
In May, the Agency opened a second call with 30,000 places and five-month programs in five strategic areas:
- artificial intelligence;
- cybersecurity;
- cloud;
- data analytics;
- networks and infrastructure.
The call also included complementary training and participation by technology companies in the course content.
This scale makes digital talent an explicit public-policy priority.
Training people does not mean a company has adopted AI
A certification demonstrates learning within a program.
It does not show that the organization where a person works has a use case, sufficient data, access to tools, a stable process, or authority to implement changes.
That difference matters in industry.
An engineer can learn to use generative models and return to a company where:
- documentation is fragmented;
- data has no approved source;
- systems are not connected;
- the workflow changes from person to person;
- no one is accountable for AI output;
- no metrics exist to evaluate the result.
In that environment, the constraint is not only individual skill.
It is organizational readiness.
Talent needs a concrete place in the workflow
AI skills gain value when they connect with a real problem.
Not everyone needs to develop models, and not every workflow needs automation.
A company may need different profiles to:
- structure data;
- automate repeatable tasks;
- analyze information;
- design integrations;
- review security;
- evaluate results;
- maintain infrastructure;
- translate operational needs into technical specifications.
Talent planning should begin with those workflows rather than a generic list of “AI skills.”
Technical training needs to be combined with judgment
Model capabilities change quickly and are not uniform across tasks.
A competent person is therefore not only someone who knows a tool. They also need to know when to use it, what information to provide, what output to review, which sources to consult, and when to escalate a decision to a specialist.
In an industrial environment, this validation capacity matters because some tasks have physical, economic, contractual, or regulatory consequences.
Training should strengthen both tool use and the ability to review its results.
Companies also need to build a learning path
The public program increases the supply of external training. The company still needs to determine how that learning becomes an institutional capability.
An internal path can include:
- identifying candidate workflows;
- documenting the current process;
- defining owners;
- establishing the knowledge each role needs;
- training with cases close to real work;
- running limited tests;
- measuring quality and usefulness;
- documenting what was learned before scaling.
This avoids building teams around tools that later fail to find a concrete application.
Digital talent does not end with a certification. It begins to create capacity when it can operate inside a system that knows what problem it wants to solve.
Frequently asked questions
How many people began the first cohort of the Public AI Training Center?
The ATDT reported that 10,000 students began activities in January 2026.
How many places did the second call open?
The second call opened 30,000 places and accepted applications through July 5, 2026.
Which areas does the training cover?
The second call covered artificial intelligence, cybersecurity, cloud, data analytics, and networks and infrastructure, along with complementary training.
Does training employees mean a company has adopted AI?
No. Training develops skills. Adoption also requires workflows, tools, data, responsibilities, controls, and evidence of use inside the organization.
Sources
- Digital Transformation and Telecommunications Agency. “Mexico launches the largest Artificial Intelligence Training Center in Latin America.” January 2026. https://www.gob.mx/atdt/comunicacion/mexico-pone-en-marcha-el-mayor-centro-de-formacion-en-inteligencia-artificial-de-latinoamerica
- Digital Transformation and Telecommunications Agency. “Public AI Training Center opens 30,000 places for its second cohort.” Call open May 26 through July 5, 2026. https://www.gob.mx/atdt/comunicacion/centro-publico-de-formacion-en-ia-abre-30-mil-lugares-para-segunda-generacion
- MEXIA / Public Artificial Intelligence Training Center. Program portal and training information. https://www.mexia.gob.mx/