Mexico's demand for AI-related talent doubled during 2025, with approximately 68,000 job postings requiring AI skills, yet organizations are discovering that hiring technical experts is only half the battle. The real challenge lies in finding and developing employees who can integrate artificial intelligence into everyday business processes, according to PwC's 2026 AI Jobs Barometer. This mismatch between what companies are hiring for and what they actually need reveals a fundamental shift in how enterprises approach AI transformation.

What Types of AI Jobs Are Companies Actually Creating?

The AI labor market in Mexico is splitting into two distinct categories, each reflecting different organizational priorities. During 2025, companies added approximately 32,300 positions focused on AI users, professionals who apply AI tools to automate routine tasks and improve operational performance. These roles require AI literacy and practical application skills rather than advanced technical expertise.

The second category, AI developer positions, involves designing, training, deploying, and maintaining AI models. While smaller in absolute volume, developer roles expanded rapidly, increasing by about 2,200 positions during 2025, representing 59.5% growth compared with the previous year. This dual expansion reflects simultaneous investment in AI adoption across business functions and in the technical capabilities required to build internal AI solutions.

"Mexico has experienced greater AI adoption across the workforce over the last year. The labor market is evolving along two paths: companies are looking for people who can use AI in their daily work, while others are investing in professionals with advanced technical capabilities," said Claudia Zarco, Managing Director of Workforce Transformation at PwC Mexico.

Claudia Zarco, Managing Director of Workforce Transformation, PwC Mexico

User-focused positions continue to dominate hiring activity, accounting for the vast majority of new AI-related roles. This pattern suggests that most organizations are prioritizing workforce productivity through AI-enabled processes rather than building proprietary AI systems from scratch.

How Does AI Adoption Vary Across Different Industries?

The concentration of AI roles differs dramatically by sector, revealing how AI maturity varies across the economy. The Technology, Media, and Telecommunications (TMT) sector remains the country's leading AI-intensive industry, with 11.3% of AI developer roles concentrated within it, the highest proportion among all sectors analyzed. This concentration indicates that technology companies are investing heavily in developing internal capabilities to design, train, and implement proprietary AI models.

Consumer Markets presents a contrasting adoption pattern. Approximately 94.5% of its AI-related vacancies correspond to AI user roles, indicating broader operational adoption rather than internal AI development. These differences highlight how AI maturity varies across industries, with technology companies focusing on technical infrastructure while consumer-facing organizations prioritize workforce productivity through AI-enabled processes.

How to Build an AI-Ready Workforce: Five Strategic Priorities

PwC's research identifies concrete steps organizations should take to expand AI adoption and navigate the talent challenge:

• Focus on High-Impact Use Cases: Prioritize AI implementations capable of generating measurable improvements in operational efficiency, revenue generation, or customer experience rather than pursuing AI adoption for its own sake.
• Integrate AI Into Workforce Development: Organizations should invest in reskilling, upskilling, and continuous learning aligned with critical business processes and strategic objectives, embedding AI capability development into broader talent strategies.
• Adopt Industry-Specific Transformation Strategies: Recognize that AI maturity differs substantially across sectors and tailor transformation approaches accordingly rather than applying one-size-fits-all solutions.
• Treat Skills Transformation as Strategic Capability: Redesign roles before changing business requirements create talent shortages, positioning workforce skills transformation as a competitive advantage.
• Establish Scalable AI Operating Models: Build governance frameworks, data management practices, and technology platforms capable of enabling enterprise-wide AI implementation rather than isolated pilots.

Beyond hiring activity, the research identifies significant changes in workforce skill requirements. PwC found a 0.27 positive correlation between AI exposure and the pace of skills transformation between 2021 and 2025. Occupations with greater AI exposure recorded an average net skills change score of 2.74, compared with 1.59 among occupations with lower AI exposure, indicating that AI is fundamentally reshaping what capabilities employees need to possess.

"The transformation of skills is becoming a competitive advantage across roles exposed to AI. Organizations in Mexico that anticipate these changes and redesign roles while developing workforce capabilities around critical business processes and strategic objectives will be better positioned to respond to evolving market demands," noted Zarco.

Claudia Zarco, Managing Director of Workforce Transformation, PwC Mexico

How Are Enterprise Giants Scaling AI Beyond Experimentation?

While Mexico's labor market reflects broader global trends, major enterprises are simultaneously moving beyond pilot projects to embed AI across entire organizations. Haleon, a consumer health company, announced a five-year collaboration with Microsoft to scale digital, data, and AI capabilities across the business. The agreement builds on Haleon's existing use of Microsoft 365 Copilot and supports wider adoption of AI-powered tools, helping teams automate routine tasks and focus on higher-value work.

Similarly, Myridius signed a strategic collaboration agreement with Amazon Web Services (AWS) to help enterprises move from AI experimentation to scaled transformation. The partnership focuses on operationalizing generative and agentic AI, improving engineering velocity, and reducing transformation complexity by combining cloud capabilities with AI-native engineering expertise.

"Myridius believes AI must move beyond experimentation and become embedded into the way enterprises innovate, modernize, and create business value. By deepening our collaboration with AWS, we are strengthening our ability to help organizations across financial services, insurance, healthcare, manufacturing, logistics, retail, travel, technology, and nonprofit sectors modernize faster, accelerate AI adoption responsibly, and deliver measurable outcomes," said Girish Pai, Chief Operating Officer at Myridius.

Girish Pai, Chief Operating Officer, Myridius

These enterprise partnerships underscore a critical insight: the companies succeeding with AI are those treating it as a workforce transformation challenge, not merely a technology deployment. They are investing in governance frameworks, security capabilities, and workforce enablement alongside cloud infrastructure and AI tools. The talent shortage Mexico's labor market reveals is not a temporary hiring problem but a signal that organizations must fundamentally rethink how they develop, train, and deploy their workforce in an AI-native business environment.