Generative Artificial Intelligence does not automatically use your company's data to train public models, provided you use corporate tools with explicit privacy clauses. The real risk of data breaches occurs when employees enter confidential information into free and public versions of chatbots, whose terms of use allow data collection for algorithm improvement.
To understand whether generative AI uses company data, it is necessary to separate the ecosystem into two drastic scenarios: consumer (public) tools and enterprise tools.
| Safety Criteria | Public AI (Free Versions) | Enterprise Integrated AI (Skyone Studio / Autosky) |
| Model Training | Yes. The prompts feed into future algorithm updates. | No. The model is static or isolated in a private environment. |
| Compliance with LGPD (Brazilian General Data Protection Law) | Non-existent. There is no guarantee of traceability of the data entered. | Total. The data travels encrypted and respects the cloud perimeter. |
| Data Retention | Undetermined, according to the terms of use accepted by the user. | Zero retention for external training purposes. |
Modernizing processes with AI requires an infrastructure that guarantees cybersecurity from the ground up. This is where cloud and integration solutions are a game-changer.
By migrating legacy systems to the cloud through Autosky, the operational environment gains a robust cybersecurity layer, where data traffic is monitored and isolated. Additionally, Skyone Studio acts as the ideal iPaaS (Integration Platform as a Service) engine to securely connect the company's databases to private artificial intelligence instances.
Moving corporate data to AI does not mean relinquishing intellectual property, provided that data governance is mediated by a secure iPaaS running on a robust cloud infrastructure.
Skyone's golden rule
Yes, if your team uses tools without governance, your company will be violating the LGPD (Brazilian General Data Protection Law). Sharing customer data, contracts, or medical reports in public generative AI constitutes a data breach, as it removes the company's control over the lifecycle of that information.
To mitigate this risk and avoid financial penalties, IT leaders use Skyone Studio to mask sensitive data before it is sent to AI-based language models.
Absolutely. The safest and most efficient strategy on the market is the implementation of hybrid architectures. The company uses the data stored in its cloud and connects it to a closed language model via secure APIs.
AI functions as an intelligent query assistant: it reads the data, solves the internal user's problem, and ends the session without sending a single line of information to external repositories.
No. Enterprise versions or access via the official API have contracts that prohibit the use of user data for training new OpenAI models.
The data becomes the property of the AI development company for the purpose of improving the system, and may reappear as a response to third-party queries in the future.
iPaaS (like Skyone Studio) standardizes data flow, enabling the creation of security filters, end-to-end encryption, and data anonymization before it reaches the AI.
No, as long as the cloud infrastructure uses data encryption at rest and in transit, strict access control (IAM), and network segmentation through platforms like Autosky.
Yes, multimodal models process entire files, whether structured or unstructured. Therefore, strategic files should never be submitted to public platforms.
RAC is an architecture where AI searches for information in an external, secure database owned by the company itself to answer a question, eliminating the need to train the global model with private data.
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