ChatGPT in the company: cybersecurity and risk mitigation guide

Generative artificial intelligence is already integrated into the business environment and, in 2025, 87% of global companies were exposed to AI-powered cyberattacks. Its adoption improves productivity, but it also expands the attack surface if data handling is not properly controlled.

Using tools like ChatGPT without a clear strategy can compromise sensitive information. The human factor remains the main threat, present in more than 75% of security breaches, making its management a critical point to reduce risk.

Riesgos asociados al uso de IA generativa sin control

The use of tools like ChatGPT, combined with the human factor and without a defined security strategy, exposes organizations to risks that go beyond the technical scope. Some of the most common risks include:

• Data leakage due to misconfiguration: Storing conversations or inputting data into models without proper information isolation can lead to internal or external failures resulting in the exposure of critical assets.
  
  
• Loss of control over the digital footprint: When employees input sensitive data such as business strategies or source code into open platforms, the company loses the ability to control who accesses that information and how it is processed.
  
  
• Hyper-personalized phishing attacks: Cybercriminals use generative AI to create perfectly written emails and messages, removing traditional warning signs and increasing the success rate of scams.
  

• Social engineering with deepfakes: AI enables highly realistic imitation of identities and voices, facilitating impersonation fraud (such as CEO fraud) that is extremely difficult to distinguish from legitimate interactions.
• Regulatory compliance breaches: Uncontrolled data processing can lead to serious violations of data protection laws, exposing the company to legal penalties and reputational damage.
  
• Autonomous malware creation: Cybercriminals leverage these models to automate malicious code generation and identify vulnerabilities, increasing both the speed and sophistication of attacks.

How to identify AI-related risks and anomalies

Anticipating these incidents requires moving from reactive security to early detection based on pattern analysis. Key indicators that something is wrong include:

Monitoring unusual data flows

The most effective way to detect potential misuse is by analyzing outbound traffic to AI platforms. When massive data transfers or abnormal volumes are detected from critical areas such as legal or finance, it may indicate data exfiltration or uncontrolled tool usage.

Prompt injection or manipulation attempts

It is essential to monitor malicious inputs designed to force incorrect responses or access restricted information. A poorly protected chatbot can be manipulated into revealing data it should not expose, affecting both system reliability and data security.

Suspicious activity in corporate accounts

Credential theft to access corporate AI environments is increasing. Detecting unusual logins, such as access from unfamiliar locations or outside working hours, is a key indicator of potential unauthorized access compromising sensitive information or intellectual property.

Guide: steps to mitigate AI risks

Acting quickly is essential. The first 72 hours are critical to contain the incident, assess its impact, and comply with data protection regulations.

1. Implement a Zero Trust model

No asumas que las interacciones internas son seguras por defecto; cada acceso debe validarse de forma continua en función de la identidad, el dispositivo y el contexto del intento de conexión, reduciendo así el riesgo de movimientos laterales dentro de la red.

2. Data encryption and anonymization

Data must be encrypted both in transit and at rest, ensuring that even in the event of a breach or unauthorized access, the information cannot be interpreted or exploited by third parties.

3. Regular cybersecurity audits

Conducting periodic reviews of systems, applications, and configurations helps detect vulnerabilities and poor practices before they can be exploited by an attacker in a real environment.

4. Establish immediate response protocols

Clearly defining who acts and how to respond to an incident enables fast containment, applying measures such as access blocking, credential rotation, or isolation of compromised systems. Team training is key to ensuring correct execution without improvisation in real scenarios.

5. Incident notification

When an incident involves sensitive data exposure, communication must be fast, clear, and actionable. It is not only about reporting what happened, but also specifying what type of data may have been compromised and what immediate actions users must take to reduce exposure and prevent greater impact.

Work with a cybersecurity partner

At ESED, we operate with a fixed monthly fee that includes proactive services to keep your systems continuously protected and operational. This model allows companies to anticipate potential incidents without relying on reactive actions or variable costs.

In addition, you can assess your company’s level of preparedness for a cyberattack through our cybersecurity assessment. It does not require advanced technical knowledge and consists of 36 questions based on industry frameworks, designed to identify your organization’s true level of exposure and security maturity.