Advanced language models are changing the way businesses operate, from customer service to strategic decision making. But their integration into the cloud poses challenges that go beyond scalability and performance: security and governance of these models have become a priority.

Nowadays, threats not only affect data, but also the integrity of the models themselves. Attacks such as model extraction, which makes it possible to replicate a model through its APIs, put the intellectual property of companies at risk. At the same time, data poisoning attacks manipulate the training of the model to alter its results. In a cloud environment, where access is global and systems are increasingly complex, protecting these models requires more than just basic cybersecurity measures. 

A cloud infrastructure designed for security 

Shielding AI models in the cloud is not just about applying security patches, but building a resilient and well-managed architecture. Some key strategies include: 

• Isolation and segmentation: Running models in controlled environments, with restricted access, reduces exposure to threats. 

• Hybrid and multi-cloud: Distributing workloads across different environments helps mitigate risks and ensures greater control over data. 

• Zero Trust and access management: Multi-factor authentication, permission control and real-time monitoring to prevent unauthorized access. 

• Explainable artificial intelligence (XAI): Detecting anomalies in models helps to identify tampering attempts before they cause damage. 

Security without cost escalation 

You have to protect AI and do it without compromising your budget. Many companies lose money on oversized or poorly optimized infrastructures. To avoid this, it is key: 

• Automate resource management: AI-based tools can adjust cloud usage according to demand, avoiding waste. 

• Adopt a FinOps approach: Controlling the operational costs of AI in the cloud allows you to balance investment and value. 

• Comply with data regulations: Regulations such as the AI Act in Europe require an infrastructure that ensures privacy and traceability without impacting performance. 

The future of AI in the cloud: security as a foundation for growth 

As artificial intelligence advances, your infrastructure must evolve at the same pace. Companies that integrate security, efficiency and compliance from the ground up will be better prepared to harness the full potential of AI without taking unnecessary risks. 

Cloud & AI Infrastructure 2025 will be the meeting point to explore how organizations are solving these challenges. From resilient architectures to compliance strategies, this event is key for professionals looking to learn more about the industry, its challenges and innovations. Don't miss it!