Why AI in LATAM Fails (And How ERP is the Solution)

The conversation around Artificial Intelligence in LATAM companies often starts in the wrong place: debating the best model, the trendiest tool, or the flashiest use case.

However, the data tells a different story. A study by MIT Sloan Management Review documented that only 10% of companies manage to scale their AI initiatives beyond a pilot phase. In LATAM, that number is even more pronounced, and surprisingly, the root cause isn't technological.

The Real Barrier: Data Infrastructure

The fundamental issue lies in the operational foundations of businesses. We see processes that were never properly documented, vital information fragmented across countless spreadsheets, and entire operations depending on a single person's judgment rather than a centralized system.

No AI model, no matter how advanced, can operate reliably on such an unstable foundation. AI amplifies what already exists: if it amplifies disorder, the results will be unpredictable and costly.

ERP as the Foundation for Artificial Intelligence

ERP (Enterprise Resource Planning) systems are often perceived as boring or outdated technology, while AI is viewed as the future. But the reality is that a structured ERP, such as Odoo, isn't the step that comes after implementing AI. It is the fundamental prerequisite that makes it possible for AI to function in a real production environment, not just in an isolated demo.

Integrating all sales, inventory, finance, and operations data into a Single Source of Truth is what allows algorithms to have the real-world context necessary to make decisions, generate accurate predictions, and automate complex tasks.

The Correct Order for Digital Transformation

To scale successfully, companies must adopt the following sequential approach:

• Diagnosis First: Understand where the disorder lies and identify which critical processes lack standardization.
• Structure Second: Implement an ERP to unify and centralize information across the entire company.
• Intelligent Automation Last: Deploy AI models on top of a clean, structured database.

In that order, not the other way around.

A Question for Your Business

Has your company already resolved its data infrastructure with a solid ERP before moving forward with Artificial Intelligence projects, or are you also investing in the AI model before organizing your operational base?