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Artificial intelligence (AI) is increasingly embedded in modern organisations—from standalone generative AI apps to AI copilots in popular SaaS platforms, and the integration of self-hosted or public large language models (LLMs) in private applications tailored to specific business needs.
The recently introduced EU AI Act sets out to regulate AI development and usage, ensuring that AI systems are safe, ethical, and respect fundamental rights. This legislation represents a major step by the European Union to govern AI within its jurisdiction. If your organisation develops or manages AI systems, understanding this regulation is crucial.
The Netskope secure access service edge (SASE) platform offers a comprehensive set of capabilities for securing and complying with AI regulations, including risk management, transparency, monitoring, reporting, and regulatory adherence. If you’re eager for details now, download the Netskope guide to the EU AI Act here. If not, keep reading for a deeper dive.
Why Is the EU AI Act Important?
The EU AI Act has drawn significant attention, especially from businesses in high-risk sectors like healthcare and finance. Compliance will be critical for organisations handling sensitive information or developing AI-driven technologies.
The Act classifies AI systems into four risk-based categories:
- Prohibited AI Systems: These include applications such as social scoring, banned due to safety and human rights concerns.
- High-risk Systems: AI used in healthcare, employment, and law enforcement faces stricter rules due to its potential impact on individuals’ lives or human rights
- General-purpose AI: Systems like chatbots must meet transparency requirements.
- Minimal-risk Systems: Tools such as spam filters have few, if any, obligations under the Act.
What does this mean for your business?
Complying with the EU AI Act not only requires a robust approach to identify and categorise AI systems but also applying data governance and risk management. Key considerations for organisations include:
- Control access to AI systems: Identify use of AI systems and control access based on the categorisation of AI system (i.e. Prohibited, High-risk, General-purpose).
- Data loss prevention (DLP): Safeguard sensitive data processed by AI systems from unauthorised access and breaches.
- Risk management: Implement ongoing monitoring to identify and mitigate risks associated with AI deployment.<