NeurIPS2025 Workshop Research Development of AI in Mexico: Main Applications
Abstract
The Research Development of AI in Mexico: Main Applications workshop seeks to showcase, strengthen, and connect the most impactful developments in Artificial Intelligence (AI) and Data Science emerging from Mexico and the broader Latin American region. Over the past four decades, Mexico has cultivated a robust research community in AI through pioneering contributions in areas such as computational intelligence, autonomous robotics, fuzzy systems, and natural language processing, led by institutions including CIC–IPN, INAOE, UNAM, ITESM, CINVESTAV, and Universidad Veracruzana. Today, the region is undergoing a strategic transformation, shifting from foundational research to the development of applied AI technologies addressing real-world needs in healthcare, education, agriculture, smart cities, cybersecurity, and sustainability. This evolution has been further propelled by increased access to open data, advances in computing infrastructure, and growing collaborations between academia, government, and industry. Despite these advances, Latin America faces distinctive challenges in the development and deployment of AI. These include limited funding, underrepresentation in global AI initiatives, digital inequality, and the need for responsible, inclusive, and culturally relevant AI systems. Additionally, emerging concerns related to AI ethics, algorithmic bias, and regulatory frameworks must be addressed proactively to ensure equitable and trustworthy technology adoption. This workshop aims to bring together researchers, students, practitioners, and policymakers for meaningful dialogue about the current landscape and future direction of AI in Mexico and Latin America. By promoting interdisciplinary collaboration, the workshop will showcase impactful case studies, emerging research paths, and opportunities for cross-border cooperation, while fostering a shared vision for AI that is ethical, sustainable, and aligned with regional priorities.