United Kingdom, Mexico Set Path for AI and Data Sovereignty

Mexico stands at a critical juncture regarding its digital infrastructure and the management of corporate information. To help address it, the British Embassy, under the framework of the AI Mission in Mexico City, hosted a strategic roundtable to establish collaborative frameworks for AI development between British technology firms and the Mexican business ecosystem. The initiative focuses on adoption of international standards, technical education, and the strengthening of data sovereignty within the private sector.

"There is a visible lack of maturity in the Mexican market where large corporations advance through operational efficiencies while SMEs hesitate due to a lack of technical knowledge,” says says Verónica Viniegra, CEO, MAYia Edgenet. “If we do not integrate privacy, high-quality data, and cybersecurity under international frameworks, we cannot conduct the technological train toward the desired economic objectives."

Mexico manages a significant portion of its corporate and sovereign data through external infrastructures. Participants at the roundtable, including representatives from the National Chamber of the Electronics, Telecommunications and Information Technology Industry (CANIETI), the Mexican Association of the Information Technology Industry (AMITI), and the Open Data Institute (ODI), among various other industrial chambers, noted that 90% of the data from Mexican companies is stored outside the country. This creates challenges for digital sovereignty, national security, and geo-strategic positioning. The United Kingdom, which has maintained a leading position in AI strategies since 2017, could serve as a primary reference for Mexico to implement best practices in data ethics and algorithmic transparency.

The relevance of this mission lies in the regulatory gap in the US–Mexico region. While the European Union has moved toward risk-based AI legislation, Mexico is still navigating the implementation of regulations for its Law of Protection of Personal Data. “The lack of a clear regulatory roadmap has led to a fragmented ecosystem where sectoral leaders in banking and fintech adopt international standards, such as ISO/IEC 42001, while the rest of the industry remains underserved,” says Chanel Medellín, Sr. Specialist Instructor MX & NoLA, BSI.

Analysis of International Standards and Normalization

A primary objective of the UK Embassy mission is the harmonization of technical standards to facilitate cross-border collaboration. The roundtable discussed the necessity of translating international standards, specifically ISO/IEC 42001 and ISO/IEC 42005, into Mexican National Standards (NMX). These standards provide a management system for AI that addresses safety, transparency, and accountability.

The transition to NMX is not merely a bureaucratic step but a strategic incentive for local supply chains. Eneas Castellanos, President and Advisor, CANACINTRA, says that many local providers struggle to integrate into global value chains because they lack these certifications. By establishing a local version of these standards, the industry can create a "sandbox" environment. This allows SMEs to test AI implementations under controlled risks before attempting full-scale international certification.

Furthermore, the implementation of these standards addresses the "hidden factory" within manufacturing. “Defensive AI applications can eliminate waste and improve productivity indices without requiring "rocket science" level investments,” says Enven Wong, 

Director of Corporate Solutions and Government Solutions, Pearson Corporate. “Companies must master statistical foundations and probability before advancing to complex algorithmic innovation.”

The Four Pillars of AI Competency

The Open Data Institute, represented by Dave Tarrant, Principal Technical Consultant, presented a specialized framework to address the divide between technical teams and decision-makers. Research conducted by the institute suggests that the success of AI in the workplace depends on four distinct levels of competency.

1. AI Literacy: This involves a critical understanding of what AI does, including the ability to recognize biases and question automated decisions.

2. AI Skills: This represents the technical capacity to build, train, and deploy mathematical models and data science systems.

3. AI Fluency: This is the ability to think in terms of AI and data, effectively communicating the limitations and assumptions of a model to the rest of the organization.

4. AI Acumen: This focuses on strategic responsibility, including risk analysis, ethical requirements, and compliance at the executive level.

“Education should not focus solely on creating more data scientists. Instead, organizations require "data translators" who sit between the technical experts and the business leaders,” says Tarrant. “The more accessible data is, the greater the value it has.” He also encourages Mexican firms to adopt global open standards to ensure data is reusable and trustworthy.

Digital Sovereignty and the Role of Infrastructure

The roundtable highlighted that digital sovereignty is a matter of economic security. Representatives from Mexican data centers emphasized that capital and talent are already available within the country to support the decentralization of information. By moving data processing closer to the source in states like Jalisco, Nuevo Leon, and Mexico City, companies can reduce latency and increase control over sensitive information.

However, some issues could arise if AI is not used transparently. “In Mexico, government agencies are increasingly using metadata and algorithms to monitor fiscal discrepancies,” says Jocelyn Garcia, Strategic alliances country leader, T-Systems Mexico. “However, these algorithms are rarely transparent, leaving the average citizen and small business owner at a disadvantage”. 

Garcia notes that the lack of an ethical framework for government AI use could lead to an environment where data is used for surveillance rather than for administrative efficiency.

The gap between academic output and industrial needs remains a significant barrier to Mexico’s technological development. Efforts are being made to fill this gap. For example, the Association National of Institutions of Education in Information Technologies (ANIEI), represented by Lourdes Sánchez, President, reports that it is aligning university curricula with the real-world demands of 53 major technology companies.

Antonio Velasco, Representative, Monterrey IT Cluster, says that his organization has spent seven years educating clients on the value of AI in high-precision manufacturing. Velasco notes that while "micro-credentials" and short courses are popular, they often fail to provide the deep mathematical foundation required for sustainable innovation. 

The consensus among the participants is that the year 2026 will be a turning point for the implementation of AI at the enterprise level, making it imperative to accelerate talent development programs today.

Strategic Commitments and Next Steps

During the event, the UK Embassy committed to facilitate access to research and maturity assessment tools developed by British institutions. This will allow Mexican companies to perform self-evaluations on their data readiness and ethical frameworks.

The British Embassy and the trade chambers also plan to establish a repository of "lessons learned" to prevent companies from repeating common errors in AI adoption. This includes strategies for mitigating "hallucinations" in generative models through Retrieval-Augmented Generation (RAG) frameworks. By sharing these technical insights, the collaborative network aims to lower the barrier to entry for the 4.5 million SMEs that form the backbone of the Mexican economy.

As the "British AI Mission" continues its work in Mexico City, the focus remains on building bilateral trust. The integration of UK expertise in data ethics with Mexican industrial capacity provides a roadmap for a more resilient and sovereign digital future.