Latin American Businesses Rapidly Scale AI Amid Governance Challenges

Recent findings from RSM's "AI Readiness in Latin America 2026" report reveal that 68% of businesses currently adopting artificial intelligence (AI) in Latin America plan to scale their efforts within the next year. This ambitious growth trajectory underscores a significant shift in the region’s approach to AI, driven primarily by the pursuit of operational efficiency. However, the report also highlights critical governance and workforce challenges that could impede this momentum.

The survey, which included over 400 business leaders across Latin America, indicates that approximately 40% of organizations are already implementing AI technologies. While the enthusiasm for AI is palpable, the report reveals a concerning lack of formal governance structures. Only 18% of respondents reported having established AI governance frameworks, and a mere 4% indicated comprehensive training programs for employees. This lack of preparedness is compounded by the fact that only 8% of employees feel fully equipped to engage with AI tools.

Eileen Turkot, Market Leader for Latin America at RSM International, emphasizes that the primary risk lies not in a lack of interest but in the premature scaling of AI initiatives without the necessary capabilities. This sentiment is echoed in the report’s findings, which identify governance, employee policies, and risk management as areas where many organizations fall short. The data suggests that companies with robust governance structures are more likely to conduct thorough AI risk assessments, indicating that governance is essential not just for compliance but as a foundation for sustainable growth.

Efficiency remains the predominant driver of AI adoption, with 67% of respondents citing it as their main motivation. Planned investments are primarily directed toward IT, operations, and marketing. However, the report notes that human resources and security are receiving less attention, despite their crucial roles in ensuring workforce readiness and risk management. This imbalance could lead to significant vulnerabilities as companies scale their AI capabilities.

The findings signal a pressing need for organizations to develop clear governance models and role-specific training programs. Without these foundational elements, investments in AI technology risk becoming sunk costs, contributing to technical debt rather than delivering tangible business value. Turkot warns that without a structured approach to AI deployment, companies may struggle to translate their initial curiosity into lasting institutional capacity.

As AI becomes increasingly integrated into everyday operations, the organizations that prioritize governance and employee preparedness will likely gain a competitive edge. Establishing clear frameworks for AI usage and risk assessment will not only enhance operational efficiency but also build trust among stakeholders. This is particularly important as regulatory scrutiny around AI grows, making governance not just a best practice but a necessity for long-term success.

Looking ahead, businesses that proactively address these governance and workforce challenges will be better positioned to harness the full potential of AI. The ability to scale effectively while managing risk will distinguish leaders from laggards in the AI landscape. As the market evolves, companies that invest in robust governance frameworks and comprehensive employee training will not only mitigate risks but also unlock new avenues for innovation and growth.