The Road for Mexican Companies to Unlock AI Agent Potential

The adoption of AI in Mexico is accelerating, with 495,000 companies incorporating the technology in the last year. However, this quantitative advance reveals a critical strategic maturity gap that positions the transition to autonomous AI agents as the next significant challenge, and the greatest competitive opportunity for the country's business sector.

“AI is a tool to support business value, automate processes, and optimize resources, but strong governance remains essential,” said Jesús Vázquez, IT Director of the Latin American Region and AGS Mexico, Alcon, during the Mexico AI, Cloud & Data Summit 2025. 

The Mexican business ecosystem has responded quickly to AI, creating a landscape of widespread but shallow adoption. Amazon Web Services’ (AWS) Unlocking Mexico’s AI Potential 2025 report notes that, during 2024, the total penetration rate rose from 29% to 38%, meaning over 2 million companies now use some form of AI. The report points to chatbots (69% adoption) and Generative AI (66%) as the most common tools.

However, this breadth of adoption contrasts sharply with its depth. Only 3% of companies in Mexico have reached an advanced stage of implementation. AWS explains that just 7% of companies apply AI to advanced processes, while 72% limit it to basic, isolated uses.

"There is significant hype and misinformation surrounding AI. Its implementation can be risky and create cultural barriers, as expectations are often unrealistic. Nearly 80% of AI projects fail to achieve their intended outcomes," says Héctor Romero, Chief AI Officer,  TV Azteca.

This superficiality creates a paradox. While 88% of companies report productivity improvements, only 30% have seen significant business benefits. This indicates companies are achieving tactical, task-level efficiency but are failing to translate those small wins into strategic, business-level value like new revenue streams or significant cost reductions. This gap is the direct consequence of technological adoption that precedes a coherent integration strategy.

The Road to AI Agents: A Strategic Roadmap

The transition from isolated AI tools to orchestrated autonomous agents represents the next frontier of competitiveness. This leap demands a clear understanding of the opportunities, obstacles, and strategic path forward.

"An AI agent is not a concept that has not been managed for a long time. What is interesting is how it is enhanced by Generative AI, which enables it to make decisions," says Jorge Valdes de la O, IT Director, Grupo Infra.

Autonomous AI agents are software entities that make decisions and execute complex actions to meet business objectives without direct human intervention. Their impact could be transformative across Mexico’s key sectors.

In the manufacturing and automotive industries, agents can enable predictive maintenance to reduce downtime, use computer vision for superior quality control, and dynamically optimize supply chains. An analysis by McKinsey shows that AI at this scale can increase productivity by two to three times and reduce defects by up to 99%.

In financial and tax services, AI agents can be critical for efficiency and compliance within the Tax Administration Service (SAT) framework. They can automate real-time fraud detection and manage complex tax reconciliations, mitigating compliance risks, and freeing human capital for high-value strategic planning.

The communications sector is also leveraging this technology. “From a communications perspective, we see this technology as an opportunity to reinvent ourselves. Three advantages stand out: radically optimizing the network, transforming the user experience, and increasing agility to identify and implement new revenue streams,” says Pablo Castillo, Deputy Director of Innovation and Technology, izzi.

Identifying the Fundamental Obstacles

Despite this potential, several interconnected obstacles hinder large-scale adoption in Mexico. The primary bottleneck is a human capital deficit. A Bain & Company survey reports that 56% of companies cite a lack of talent as the main barrier to adoption, a problem compounded by a knowledge gap at the executive level.

"Infrastructure and talent represent significant areas of opportunity in Mexico when it comes to implementing this technology," explains Vázquez.

This is reinforced by cultural and strategic inertia. An analysis by IPADE Business School underscores that the core issue is not a lack of technology, but the absence of a clear integration strategy from leadership. This is coupled with technical and data governance hurdles, as integrating new AI with legacy systems is complex, and concerns over data quality, bias, and privacy are paramount for effective and ethical implementation. Finally, a nascent regulatory framework for AI creates legal uncertainty, making companies hesitant to commit to long-term investments.

These challenges create a vicious cycle: a lack of strategic vision prevents investment in talent and the skills shortage leads to poor AI implementation. These issues lead to a failure in generating significant ROI, which reinforces leadership’s skepticism and inaction.

A Strategic Guide for Business Leaders

Breaking the cycle of low maturity requires a deliberate roadmap focused on building organizational capabilities, not just acquiring technology. Companies would benefit from an approach that prioritizes strategy over the tool. This would involve the development of a formal AI strategy aligned with core business objectives. 

"Every company has different departments, cultures, and levels of expertise. It is important to listen to diverse perspectives, as they can lead to replicable solutions," says Javier Blaustein, Vice President Latam, Jeen.ai.

Another suggestion is investing in human capital, and treating workforce training as a strategic investment. This requires robust upskilling and reskilling programs focused on both technical skills and complementary human skills like critical thinking. Robust data governance is also essential. This can be achieved through the establishment of a transparent framework for data collection, use, and privacy. 

From Automation to Autonomy

The AI landscape in Mexico is at a crossroads. While basic tool adoption is widespread, true competitive advantage will come from scaling to the next phase: autonomous AI agents. This future paradigm, where agents execute complex business objectives independently, is expected to profoundly redefine industries.

Companies that fail to build the necessary strategic, cultural, and data governance foundations risk becoming structurally unable to compete in the coming era of autonomous automation. The path to unlocking this potential does not begin with new technology, but with the leadership commitment to transform the organization from within.