Data-Driven Mexico: Turning Strategy into Economic Reality

Companies in Mexico face a critical gap between the intent to invest in data and AI and their effective operational execution. Despite a notable increase in projected spending, the country maintains a digital maturity index of only 41.7%, which limits measurable economic impact.

The central challenge is converting data into tangible value. “We often lose sight that to be data-driven is to be value-driven. The most valuable thing is to understand what moves the needle,” said Gabriel Olguín, IT LATAM Director, PPG Industries, during the Mexico AI, Cloud and Data Summit 2025. The primary obstacle is not technological acquisition, but rather strategic alignment and organizational implementation capability.

Mexico’s macroeconomic environment presents a compelling case for the accelerated adoption of data-driven strategies. An annual Gross Domestic Product (GDP) growth of 1.2% in 2Q25, with only three states exceeding the 4.5% growth target, shows stagnation that traditional business models struggle to overcome.

A 0.7% contraction in secondary activities, which include the manufacturing sector responsible for 21.7% of the national GDP, is another warning sign. In this scenario, advanced analytics and AI emerge as strategic tools that can enhance corporate resilience. Projections indicate that generative AI alone could contribute up to 6.2% of Mexico’s national GDP, positioning digital transformation as an economic imperative.

"The goal is to leverage data to gain deeper business insight, drive informed decisions, and uncover opportunities for growth," says Sofia Pérez, Director General, AMITI.

However, the transition from strategy to execution is hindered by structural, human and strategic factors. The fundamental challenge is not technological but one of leadership, organizational redesign and human capital development.

Digital transformation requires a change in mindset driven from the C-suite. Pérez notes the need to develop skills such as curiosity and strategic thinking throughout the staff, not just in technical roles, so that strategic plans permeate the organization.

This approach requires "general digital literacy" within companies. “The technology and analysis areas must be seen as part of the business, not external areas. This cultural promotion enables greater preparation and evolution across all organizational areas,” says Irma Caleti, Corporate Systems Americas Director, Japan Tobacco International.

Organizations also face difficulties integrating diverse sources and managing large data volumes, as they often lack a robust data governance framework. The lack of adequate governance frameworks and a common language are the primary obstacles impeding synergy, says César Omar González, Deputy Director of Architecture and Data Governance, BanBajio.

This issue is reflected at the national level. Mexico scores 2.8 out of 100 on the Institutional pillar of the Government AI Readiness Index. Joseph Hernández, Mexico Data Office Head, Citi, points to the need for a balance between governance and technology, highlighting that data ownership is key, and includes privacy, regulatory frameworks, and protection.

“Data is not just IT’s responsibility; it requires enterprise-wide alignment and a shared data governance culture,” says Hernández.

The problem is exacerbated by a critical shortage of professionals. Up to 70% of companies report difficulty hiring AI specialists, with demand tripling compared to the rest of Latin America. This fact is related to the country's low R&D investment (0.28% of GDP compared to the OECD average of 2.72%).

Collaborative investment in human capital among government, academia, and the private sector is required to develop the specialized talent the market demands. “Companies that successfully integrate these analytical capabilities are expected to lead their industries and become the primary architects of Mexico's future economic competitiveness,” says González.

Despite the challenges, the application of data strategies is already generating value. In manufacturing, predictive maintenance has resulted in a 10% improvement in production efficiency and a 20%–30% reduction in unplanned downtime since 2023, with estimated annual savings of US$300,000 per plant.

In the financial sector, the separation of Citi and Banamex shows a large-scale data agility exercise, which enabled two banks to operate independently and securely "basically from one day to the next," says Hernández. 

In retail, Comex used data to understand who customers are, why they buy, and which products predominate by store, says Olguín. This allowed the company "to provide a tailored offer" to better capitalize on the existing market.

Proprietary technology can also address specific opportunity areas through tools that show executives "day-to-day information to compare" period against period, moving from static reports to specific databases to expand client portfolios, says González.

“To close the gap between strategy and economic reality, concerted actions are required. First, public policy that develops a national AI strategy is necessary to provide investment certainty. Second, corporate strategy where C-suite leadership actively drives a data-first culture, linking KPIs to data initiatives,” says Pérez.