Mexico's AI Growth in Manufacturing: Overcoming Challenges

Artificial intelligence (AI) is gaining ground in Mexico's manufacturing sector, but its adoption is advancing cautiously. With 965% growth in the number of companies developing AI between 2018 and 2024, according to Endeavor, sector leaders recognize its potential to optimize costs and improve the supply chain. 

According to a KPMG report, 35% of business leaders in Mexico's manufacturing sector believe that AI implementation will be crucial in the future to remain competitive in the long term. Another 29% believe that its adoption will be relevant in the medium term, while 18% see AI as a short-term need. Only 18% of respondents believe that AI will not be essential to their business in the future.

In terms of the main problems that leaders are looking to solve through AI, 73% of respondents list optimization and cost reduction as one of the most important goals. Other key problems include improving cybersecurity (57%), supply chain management (55%) and data-driven decision making (55%). These results reflect a clear focus on how artificial intelligence can bring tangible improvements in areas critical to manufacturing operations.

AI adoption is also influenced by external factors such as nearshoring, which is driven by the need for diversification and cost reduction. The proximity to the United States and the growing demand for manufacturing in North America position Mexico as a strategic destination for investment. This also increases the pressure for companies to adopt advanced technologies to improve productivity and remain competitive.

Nevertheless, challenges remain. Endeavor's study, The Age of AI in Mexico, highlights some of the risks associated with the adoption of this technology, highlighting the lack of specific regulation for AI, staff training, and concerns about data privacy and security, highlighting the growing importance of protecting digital infrastructures from potential threats.

Training and the development of teams that can adapt legacy processes with new technology are key to addressing these challenges. This highlights the need for a balanced approach, where technology automation complements human capital, rather than replacing it entirely, MBN previously reported.

Aldo Lopez, Vice President and Co-Founder, Onest SmartLogistics, emphasized that, to reach effective AI adoption, companies not only need to invest in technology, but also in robust infrastructures, such as networks and telecommunications, that support these advances and ensure seamless integration and operation without obstacles.

“AI’s implementation in the manufacturing sector not only requires investment in technology, but also in the training and reconfiguration of work teams, which implies a significant organizational transformation adapted to the specific needs of each business so as not to generate disruptions that affect daily operations,” KPMG points out.

The logistics sector is also going through a similar transformation. According to a Samsara report, 51% of logistics leaders are already using AI, and 93% of organizations are expected to adopt AI by 2026. The use of AI in logistics, such as route optimization and improved inventory management, can offer key lessons for the manufacturing sector, especially in critical areas such as reducing operating costs and improving accuracy.