AI use among large Mexican companies doubled to 48.5% by June 2026, and executives are responding with role redesign, upskilling, and human oversight rather than broad job cuts. Banxico data shows that 79.4% of firms planning AI adoption expect stable or growing employment, while skills gaps, not worker resistance, are the main constraint. Manufacturers, service providers, HR firms, and large corporations are among the most affected as AI talent demand intensifies.
Mexican CEOs are preparing leadership teams for AI adoption by redesigning roles, funding upskilling, and keeping human oversight over critical decisions, rather than planning broad workforce reductions. Recent data from Banxico, KPMG, and EY shows that most large companies expect stable or growing headcount as AI use expands.
This approach responds to a gap between how employees use AI and how organizations direct it. According to Microsoft’s Work Trend Index 2026, 67% of Mexican AI users now perform work they could not do a year ago, yet only 28% perceive clear leadership alignment to turn that progress into organizational change, as reported by MBN. “The opportunity lies in aligning technology, leadership, and human judgment to create value responsibly and sustainably,” says Ezequiel Glinsky, Chief Technology Officer, Microsoft Latin America.
AI adoption among Mexico’s large companies has accelerated over the past year, which places workforce planning higher on executive agendas. A Banco de Mexico (Banxico) analysis, published on Sept. 10, 2026, as part of its April–June 2026 Regional Economies Report, shows that 48.5% of firms with more than 100 workers used at least one AI technology in June 2026. In September 2025, 24.3% of firms reported using or planning to use AI within 12 months, although the central bank notes that the questions are not directly comparable. Looking ahead, 64.8% of firms expect to use AI within three years. Adoption is higher among the largest companies, at 69.9% for firms with more than 1,000 workers, compared with 43.7% for those with 101 to 250 workers.
The same survey indicates that AI has not yet displaced employment at scale. Among firms already using AI, 67.5% report no significant change in employment over the past three years, 19.6% report a positive effect, and 12.9% report a decrease. Among firms planning to use AI, 32.6% expect employment to increase over the next three years and 46.8% expect no significant change, while a smaller share anticipates negative effects. Banxico states that these figures reflect company responses, not its own forecast, and adds that developing worker competencies will be relevant for effective adoption.
Global CEO data points in a similar direction. KPMG’s 2026 Global CEO Outlook, which surveyed 1,400 CEOs of companies with annual revenues above US$500 million between Aug. 11 and Sept. 21, 2026, finds that 79% consider AI a top investment priority for the next three years and 72% expect to allocate more than 10% of their budgets to it next year. At the same time, 89% expect total headcount to grow over the next three years, although 62% anticipate growth below 5%.
Survey data and executive statements point to four main ways leaders are preparing their organizations: communicating with employees, retraining them, keeping human oversight over decisions, and competing for scarce AI talent.
The first is transparency about how AI will affect roles. According to KPMG, over the next 12 months, 51% of CEOs plan to openly communicate the effect of AI on roles, 46% plan to launch reskilling and upskilling programs, and 46% intend to offer personalized training on how AI can support employees’ work. The same survey shows that the main obstacles are skills gaps, cited by 56% of CEOs, and the difficulty of training employees on AI systems, cited by 52%. Workforce resistance to AI ranks lower, with 26% describing it as a very or quite complex challenge.
Mexico’s executive agenda follows this pattern. In an analysis of the May 2026 EY-Parthenon CEO Outlook Survey, Olivier Hache, EY-Parthenon Managing Partner, EY Mexico, writes that the AI priorities of Mexican business leaders include upskilling, expanding talent pools, and promoting collaboration between people and technology. The analysis also lists the lack of specialized data and AI talent among the leading risks identified by executives.
The second focus is human oversight in sensitive processes. In an interview with MBN, Francisco Martínez Domene, CEO, The Adecco Group Mexico, says that at his company “final interviews and hiring decisions are never left to automated AI platforms,” and notes that Mexico lacks specific AI governance in hiring. He adds that “capitalizing on this momentum requires accelerating workforce upskilling and reskilling initiatives,” in a labor market where informal work accounts for about 56% of employment.
The third factor is competition for AI-ready talent, which raises the cost of relying only on external hiring. According to PwC’s 2026 AI Jobs Barometer, job postings requiring AI skills in Mexico doubled during 2025 to roughly 68,000. Data compiled by MBN also shows that 55% of Mexican companies cite a lack of trained personnel as a barrier to deploying more complex AI models, while enrollment in generative AI courses in Mexico grew by 356% year over year in 2025. These conditions support employer-led training as a complement to recruitment.
The fourth element is the link between productivity and jobs. Banxico’s survey shows that 39.1% of AI-using firms report a positive effect on sales or revenue per worker over the past three years, while 57.3% report no significant change yet. Among firms planning to use AI, 60.2% expect productivity gains over the next three years. Banxico also notes that its survey measures whether firms use a technology, not how intensively, and that deep integration is likely at an early stage.
Taken together, the data shows that Mexican companies are treating AI adoption as a matter of leadership and skills rather than a direct substitute for labor. The main measures are role redesign, structured training, clear communication with employees, and human control over high-impact decisions.