Mastering Shadow AI with SASE: Security & transparency for Gen-AI in the company

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SASE: Security and transparency for AI in the company

Generative AI has long been part of everyday working life. Tools such as Copilot or ChatGPT increase productivity – but also bring new risks: Data leakage, incorrect content and uncontrolled use of unapproved tools jeopardize data protection, compliance and security.

The problems of using AI:

Lack of transparency about tools used
Uncontrolled Shadow AI activities
Compliance and security risks

The solution: SASE

Secure Access Service Edge combines network and security functions in a cloud-based platform that creates transparency and makes shadow IT controllable.

Uniform guidelines and central control
Protection against data loss and unauthorized access
Scalable cloud security without the need for hardware

With SASE, companies secure their AI usage: efficiently, transparently and future-proof.

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Regulatory guard rails: The EU AI Act

The EU AI Act came into force in mid-2024. It classifies AI systems into different categories according to risk potential and obliges companies to implement strict control mechanisms. This makes it clear that AI can no longer be operated without binding governance. Companies need to rethink internal processes, monitoring and security solutions.

Key points of the EU AI Act:

Classification of AI systems according to risk: prohibited, high risk, limited, minimal
Transparency and documentation obligation for high-risk systems
Ensuring data protection, security and fundamental rights as the primary objective
Commitment to internal control and governance structures
Significant sanctions for breaches of the requirements

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The dark side of efficiency: what Shadow AI means

More than 70 percent of companies are already using GenAI in individual departments, but many without clear preparation. The unofficial use of unapproved tools by employees is particularly problematic. If sensitive data is entered into external services, security gaps and compliance breaches occur. An incident in the summer of 2024 in the financial sector showed how internal communication can be leaked uncontrollably and cause major damage.

In a nutshell:

Shadow IT becomes even more difficult to recognize through AI
Lack of training increases the risk of incorrect entries
Heavy fines may be imposed for violations of the EU AI Act
Security and IT teams are often not sufficiently involved
Transparency and clear governance are crucial for trust

Open law book in front of an EU flag - symbol for European regulations, data protection and IT compliance with Savecall.

SASE in practice: rules and flexible models

Security needs rules and technology

A technical foundation alone is not enough. Companies must define clear guidelines on which tools may be used, which data types are processed and who is responsible for approvals. These guidelines are supplemented by continuous monitoring and targeted employee training. Savecall provides support with consulting, operation and – if desired – a Managed SASE model in which our specialists take over configuration and monitoring. Find out more about Managed SASE now.

Additional focal points:

Definition of binding policies for AI and cloud use
Establishment of approval processes and responsibilities
Continuous risk analysis and monitoring
Raising employee awareness through training

Glass puzzle pieces on a bright desk symbolize flexible SASE models and structured IT security solutions. In the background, three people confer in a modern office with natural light.

Flexible models for different requirements

Companies have various options for implementing SASE: cloud-native, cloud-managed on-premise, fully managed or in hybrid form. Each variant has specific advantages and disadvantages, depending on the size of the company, existing infrastructure and strategic requirements. Savecall analyzes these factors and develops a tailor-made concept that balances security, performance and costs.

Important options at a glance:

Cloud-native: lean, scalable, ideal for branch structures
Cloud-managed on-premise: higher performance through local checks
Managed SASE: Operation and configuration by Savecall, optionally co-managed
Hybrid: combination of cloud and on-premise security for global environments

SASE as a control instrument

These risks can be mitigated with a Savecall SASE architecture. The platform combines SD-WAN with security services such as cloud access security brokers, secure web gateways, firewall-as-a-service, zero-trust network access and data loss prevention. End-to-end visibility is crucial: companies can see which AI models and applications are in use – even if they are encrypted or have not been officially introduced.

Monitoring and analysis functions make anomalies visible, prevent data leaks and enable compliance with regulations such as the GDPR. At the same time, the flexible SD-WAN infrastructure ensures that data flows are prioritized and secured depending on user identity or context.

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Conclusion:

Security for Gen AI requires proactive measures

The spread of GenAI is progressing faster than traditional security structures. Those who do not take measures today risk data loss and compliance violations. A Savecall SASE solution provides companies with a platform that combines visibility, control and protection. This makes it possible to exploit the potential of GenAI without accepting any risks.

Contact our SASE experts now and arrange a consultation.

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