The combination of artificial intelligence (AI) and personal data has been a key topic in many business and even government discussions. Despite the transformative potential for companies across all sectors, combining these two factors raises a series of legal, ethical, and technical questions, especially regarding compliance with the General Data Protection Law (LGPD). After all, how far does the use of customer data on AI platforms go? How can innovation be guaranteed without compromising privacy and individual rights?

In 2024, an IBM survey revealed that more than 41% of Brazilian companies already use AI at some level, mainly to improve customer service, automate processes, and analyze consumer behavior. However, when it comes to the LGPD, only 36% of Brazilian companies claim to be fully confident in complying with the Law, as indicated by the IT Trends Snapshot 2023 study by Logicalis, a global technology solutions and services company.

In a world where being online is synonymous with providing data, and the core principle of AI is to learn from it, addressing this combination has become essential. Whether to train language models, recognize consumption patterns, or predict behaviors, the quality and quantity of data are decisive factors for machine learning. This means that when using AI, companies need to feed their algorithms with information — often extracted from customer interactions, usage logs, registrations, browsing histories, and feedback.

A fintech, for example, can use AI to predict risk of default based on past transaction data. An e-commerce business can personalize offers based on purchase history, clicks, and interactions with specific content. Meanwhile, AI-based virtual assistants are trained on customer service data to improve the accuracy of their responses. The point that requires attention is that a large portion of this data is personal and, therefore, protected by the LGPD.

What does the LGPD say about the use of data in AI?

In force since 2020, the LGPD establishes clear guidelines for the processing of personal data throughout the Brazilian territory. Among its key principles are purpose (using data only for what was disclosed), transparency, and necessity.

In the context of AI, one of the most sensitive points is the use of automated decisions. Article 20 of the LGPD guarantees customers the right to request a review of decisions made solely through automated processing that affect their interests — such as a credit denial, for example.

Additionally, the LGPD encourages the use of anonymized data (when it is not possible to identify the data subject, i.e., the customer), which significantly reduces legal risks. However, if the AI is being trained with data that identifies these consumers, clear and informed consent, or another legal basis that justifies its use, is required.

Advantages of using AI with customer data

Despite the challenges, the ethical use of data in AI solutions can bring significant gains. In fact, this is the main factor that has contributed to this combination. 

Companies like Nubank already use AI to prevent fraud in real-time, based on app usage behavior. Magalu, on the other hand, invests in AI to personalize product recommendations, aiming to increase conversion rates without compromising user privacy.

Among the main advantages of using data in AI are:

• Operational efficiency: algorithms can automate tasks such as resume screening, document analysis, and answering frequently asked questions, the famous FAQs.
  
  
  

• Improved customer experience: personalized chatbots and virtual assistants make customer service faster and more accurate.
  
  
  

• Generation of strategic insights: AIs can identify hidden trends in data and guide more assertive decisions for marketing, sales, and product departments, creating new opportunities.
  
  

What about the legal risks and challenges?

The greatest risk of improper use of AI with personal data is the violation of the LGPD, which can result in fines of up to 2% of the company's annual revenue, reaching up to R$ 50 million per violation.

Risks include data leaks, lack of transparency, misuse, and even the reproduction of discriminatory biases, as algorithms can replicate biased data — as has already happened with facial recognition and automated recruitment systems. 

To balance innovation and compliance, technical, legal, and governance measures must be adopted. The basic principles for companies wishing to use customer data in AI are:

• Obtain consent when necessary, using clear and objective language.
  
  
  

• Prefer anonymized data in model training processes.
  
  
  

• Implement access and security controls, guaranteeing the integrity of the data used.
  
  
  

• Document the legal bases for processing in Data Protection Impact Assessments (DPIA).
  
  
  

• Promote AI governance, creating technology ethics committees and protocols for reviewing automated decisions.
  
  

How to prepare for an AI-regulated future

The regulation of AI is advancing globally. In 2024, the European Union approved the AI Act, which establishes obligations proportional to the risk of the AI system — and inspires similar legislation in other countries, including Brazil.

Companies that anticipate this and create clear internal policies will come out ahead. This includes training legal, technical, and product teams on LGPD and AI, reviewing contracts with AI suppliers to ensure data protection clauses, and conducting frequent audits on how data is collected, used, and stored.

Innovating with AI and respecting customer privacy are not opposing goals — they are complementary paths toward safer, more reliable, and responsible technology. The LGPD is here to stay, as is AI, and their combined applications require continuous attention, cross-departmental dialogue, and an ethical commitment to who really matters: the user.