AI in Business: How to Implement Automation Without Violating Legislation

Business interest in artificial intelligence continues to grow. Companies are implementing chatbots, voice assistants, customer service systems, and automating sales and internal processes. However, along with these technological advantages come legal risks.

In practice, many companies focus on the functionality of their solution, but don’t always consider data storage, information transfer, and compliance with personal data laws. These aspects often become the source of complaints from regulatory authorities.

Why AI Use Contains Legal Risks

The use of artificial intelligence itself is not prohibited and does not require special permits. The main risks arise not from the technology itself, but from the way the system operates.

Most AI services operate through cloud infrastructure. To process user requests, information may be transferred to third-party servers located outside of Russia. If a request includes personally identifiable information, the company must comply with personal data laws.

The problem is that many organizations don’t always understand what data is actually being transmitted to the neural network. Even a simple conversation with a customer can contain a last name, phone number, email address, order details, or other personal information.

Particular attention is paid to cross-border data transfer

One of the most sensitive issues remains the transfer of personal data outside the Russian Federation.

If an AI solution uses foreign infrastructure or foreign data processing services, the company must assess in advance the legality of such transfer and compliance with all mandatory procedures.

Without proper legal preparation, using external services may result in violations of personal data laws, administrative fines, and remedial orders.

Therefore, before launching AI projects, it is recommended to conduct a preliminary audit of the information systems and data transmission channels used.

Solution architecture matters

From a legal point of view, the key factor is not the name of the neural network, but the architecture of the specific solution.

In practice, there are several options for organizing the work of AI systems.

Using external cloud services. In this case, user information is transferred to a third-party service provider for processing. This approach is typically the simplest to implement, but raises the most legal issues.

A mixed model. Data is partially stored internally, while individual requests are sent to external services to generate responses. While risks are lower in this model, they remain and require additional analysis.

On-premises deployment. The model and database are hosted on the organization’s own infrastructure or on servers fully controlled by the company. This approach provides the highest level of control over information and significantly reduces legal risks.

What to check before signing a contract with a contractor

When choosing an AI solution provider, it is important to evaluate not only the cost of implementation and the list of features.

Before signing the contract, it is advisable to find out:

• where the servers and equipment are physically located;
• who has access to the processed data;
• Are foreign cloud services used?
• Is it possible to deploy the system in the customer’s infrastructure?
• What information security measures are in place;
• Does the agreement provide guarantees for compliance with the requirements of personal data legislation?

If the contractor cannot clearly explain the data processing scheme and where it is stored, this may indicate that the solution has not been sufficiently developed from a legal perspective.

What documents should a company prepare?

To mitigate risks, a technical solution alone is not enough. Proper documentation of data processing processes is also essential.

Depending on the specifics of the project, companies may require:

• updated personal data processing policy;
• local acts regulating the use of information systems;
• agreements with contractors on data processing;
• documents confirming compliance with the requirements for the transfer of information to third parties;
• internal regulations for the use of AI tools by employees.

The availability of such documentation allows us to confirm that the organization controls data processing processes and takes the necessary measures to comply with the law.

Implementing artificial intelligence is becoming not only a technological but also a legal project. Before launching automation, it’s important to evaluate not only the solution’s effectiveness but also the data processing procedures, its storage location, and the division of responsibilities between the company and the contractor.

The sooner these issues are addressed, the lower the likelihood of facing regulatory complaints, financial losses, and the need to urgently restructure an already implemented system.