Artificial intelligence in businesses requires alignment with LGPD and robust governance

Adopting artificial intelligence in organizations enhances the ability to automate tasks, analyze data, and generate content. However, using these tools may involve personal information, confidential data, and decisions that require proper oversight.

The role of LGPD in AI usage

The General Data Protection Law sets rules for handling information related to identified or identifiable individuals. This includes situations where such data is collected, stored, shared, or used by artificial intelligence systems.

The National Data Protection Authority highlights specific challenges related to using personal data in generative AI systems, such as data scraping, unauthorized information sharing, and generating content that may contain personal data.

In practice, companies must assess what information is input into an AI tool and for what purpose. For example, an employee who copies a database containing names, documents, or customer data into an external tool creates a new data processing flow that needs to be analyzed.

Compliance and governance of AI systems

Compliance refers to the policies, controls, and procedures that help organizations adhere to laws, regulations, and internal rules. With AI’s expansion, this work now also involves governing AI systems.

Key areas for evaluation include:

• Which AI tools are authorized by the company
• What types of data can be input into these systems
• Who can use specific tools
• How AI-generated results are reviewed
• How incidents and risks are recorded

The NIST, a U.S. standards institute, recommends a structured approach to AI risk management. Its framework organizes the process into four functions: govern, map, measure, and manage risks.

This type of governance also helps define responsibilities. Instead of viewing AI solely as a productivity tool, companies can establish controls to monitor its use throughout its lifecycle.

Precautions professionals should take

The first step is understanding that not all information should be input into an AI tool. Personal data, strategic information, contracts, internal documents, and customer data may require specific controls.

It’s also essential to verify how the tool handles submitted data and what its privacy settings are. A company’s internal policy should set clear limits for using public and corporate tools.

Another critical aspect is human review. AI systems can produce incorrect answers, incomplete information, or biased results. NIST includes characteristics such as transparency, security, privacy, and bias management among the factors related to AI system reliability.

Impact on different areas of operation

The relationship between AI, LGPD, and compliance isn’t limited to technology professionals. Marketing, human resources, finance, legal, customer service, and other areas may use tools that process personal information.

The ANPD maintains specific initiatives to test artificial intelligence systems and data protection in a supervised environment. In August 2026, the authority published a methodology to assess aspects such as transparency, explainability, and protection of personal data in AI projects.

For professionals, understanding these concepts helps identify risks before a tool is used in daily activities. For companies, this knowledge can contribute to creating usage policies, evaluation processes, and oversight mechanisms.

The advancement of artificial intelligence also increases the need for professionals who can connect technology, business, data protection, and risk management, especially in activities involving personal information.