AI-Powered Data Analytics Is Gaining Momentum in Latin America

Artificial intelligence is changing the way companies use their data. Today, the challenge is not simply to collect information, but to interpret it, detect patterns, and turn it into faster decisions.

According to the IDB, in its analysis published in July 2026, approximately 80% of companies in Latin America and the Caribbean use AI tools, but only 23% report economic benefits, and just 6% perceive a significant impact.

These figures reveal an opportunity: moving beyond experimentation with artificial intelligence and integrating it into specific processes, such as sales analysis, financial planning, and operational optimization.

As Product Owner at Rootlenses, I believe the key differentiator lies in making AI-powered data analytics accessible to more teams without relying exclusively on technical specialists.

Which Industries Are Leading the Way in AI-Powered Data Analytics Opportunities?

There is no single regional ranking that measures the use of AI-powered data analytics tools exclusively by industry. However, UBS's analysis of 15 sectors and more than 60 companies in Latin America identifies financial services, retail, education, healthcare, and information technology among the sectors undergoing significant AI-driven transformations.

Based on this evidence and the use cases across each industry, we have identified five priority areas:

1. Financial Services and Banking

Banking stands out because of the volume of transactional data it processes and the need to make decisions based on up-to-date information.

The IBM Global AI Adoption Index 2023 found that 49% of IT professionals surveyed at large global financial services companies reported active AI implementation within their organizations.

AI-powered data analytics opportunities:

• Detection of anomalies and potential fraud.
• Credit risk and customer behavior analysis.
• Identification of transaction trends and profitability patterns.
• Natural language queries about financial indicators.

2. Retail and E-commerce

Retail generates data on sales, inventory, pricing, and purchasing behavior. Analyzing this information helps businesses anticipate demand and reduce operational losses.

UBS identifies retail as one of the sectors where AI is driving significant changes across Latin America.

AI-powered data analytics opportunities:

• Demand forecasting and inventory stockout prevention.
• Sales comparisons by product, store, and period.
• Product profitability and turnover analysis.
• Customer segmentation and identification of purchasing patterns.

3. Technology and Telecommunications

Technology and telecommunications companies work with large volumes of operational data, digital activity, and user behavior information.

IBM reported that 37% of IT professionals surveyed at large global telecommunications companies indicated that their organizations were already actively implementing AI.

AI-powered data analytics opportunities:

• Detection of anomalies in networks and systems.
• Customer churn analysis (churn).
• Monitoring of service performance indicators.
• Automation of reports and performance analysis.

4. Healthcare

Hospitals, clinics, and healthcare networks can use AI-powered data analytics to improve resource management and gain a better understanding of their operational indicators.

Although clinical applications require specific validation and safeguards, immediate opportunities exist in administrative processes.

AI-powered data analytics opportunities:

• Analysis of waiting times and occupancy rates.
• Staff and resource planning.
• Identification of trends in demand for services.
• Tracking of costs and operational indicators.

5. Manufacturing and Logistics

Production and distribution generate data on inventory, maintenance, operating times, and deliveries. AI makes it possible to detect deviations and improve planning.

AI-powered data analytics opportunities:

• Failure prediction and preventive maintenance.
• Cost and productivity analysis.
• Inventory and distribution optimization.
• Identification of operational bottlenecks.

The Challenge: Turning Data into Decisions

The potential is clear, but adoption does not guarantee results. The fAIr Tech Radar report by the IDB and its partners, published in 2025, highlights gaps in maturity, governance, and inclusion that Latin America faces in the responsible use of AI.

From our perspective at Rootlenses, three capabilities are essential:

• Accessibility: Enable teams to query their data in natural language without relying on SQL or advanced programming skills.
• Trust: Maintain appropriate access controls, privacy protections, and traceability for enterprise information.
• Actionability: Turn the results of AI-powered data analytics into measurable decisions, not just reports.

Conclusion: The Future of AI-Powered Data Analytics in Latin America

Financial services, retail, technology, healthcare, and manufacturing represent significant opportunities to expand the use of AI-powered data analytics. However, real progress will depend on how each company integrates these capabilities into its operations.

At Rootlenses, we believe democratizing access to data is an essential step. With Rootlenses Insight, teams can explore enterprise information through natural language queries and obtain answers that support decision-making without needing SQL knowledge.

The goal is not to use AI simply because it is a trend, but to turn the data companies already generate into a competitive advantage.

Is Your Team Leveraging Its Data to Make Better Decisions? 

Discover how Rootlenses Insight can help make AI-powered data analytics accessible to more people across your organization.

By Juan Daniel Flórez, Product Owner at Rootlenses