The adoption of AI in Mexico reached 20.1% of the working-age population during the first quarter of 2026, up from 17.8% in the second half of 2025; however, international studies warn that productivity gains associated with AI tend to be concentrated and vary considerably between countries.

The key point is that AI can both deepen the so-called middle-income trap and help overcome it: its effect depends on a country’s and a company’s ability to absorb technology, have data infrastructure, and train talent. This makes enterprise software modernization a priority action for decision-makers seeking to avoid competitive lags.

Macroeconomic evidence indicates that the productivity benefits of AI are not distributed evenly; without prerequisites — infrastructure, human capital, and regulatory frameworks — middle-income countries could fall behind instead of leveraging the technology to grow.

Experts in economic growth warn that AI was not automatically developed for all productive contexts and that adaptation requires targeted educational and support policies, especially in STEM education and in capabilities to integrate digital tools into production processes.

From a business perspective, early adoption of platforms that incorporate AI natively reduces operational frictions and accelerates the return on technological investment. Onix Board offers an ecosystem that integrates multichannel conversational automation, assisted content generation, unified analytics, and e-commerce management, with scalable plans designed to support the digital transition of teams of varying sizes.

Consolidating functions on a single platform reduces integration costs, facilitates the measurement of results, and allows companies to turn AI adoption into concrete operational improvements without requiring large internal technical teams from the outset.

For public policy makers and business leaders, priorities are aligned: accelerate basic and STEM skills training, invest in data infrastructure and connectivity, and promote schemes that facilitate the adoption of updated software in SMEs and small- and mid-sized enterprises. These measures maximize the likelihood that AI will boost productivity rather than increase reliance on external technology.