When will the EU AI Act come into effect?

The AI Act will become fully applicable in 2026 (except for a few provisions) with a phased enforcement timeline that began on August 1, 2024. Various provisions came into effect after their effective date. Provisions on prohibited AI practices came into effect in February 2025, with various other obligations and chapters coming into effect gradually in 2025, 2026, and 2027.

Which AI systems are considered high-risk?

High-risk AI systems include any AI systems that pose significant impacts on health, safety, or fundamental rights. These include AI used in critical infrastructure, medical devices, law enforcement, recruitment, education, and financial services. Any providers or deployers of such systems must adhere to the requirements related to risk management, data governance, transparency, and human oversight.

How will the EU AI Act be enforced?

The newly created European AI Office will oversee the enforcement of the AI Act. This office will work with the various supervisory authorities in the EU member states and coordinate efforts related to compliance, audits, investigation of violations, and future recommendations.

What penalties exist for non-compliance?

Non-compliance with the AI Act can result in fines of up to €35 million or 7% of a company's annual turnover, whichever is higher. The penalties are tiered based on the severity of the violation. Violations of prohibited AI practices carry the highest penalties, while non-compliance with other obligations (such as those for high-risk systems) can result in fines up to €15 million or 3% of global turnover. Providing incorrect information to authorities carries the lowest penalties, up to €7.5 million or 1% of global turnover.

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LLM Firewall Integration:
A CISO’s Guide to Securing GenAI Applications

In the rapidly evolving landscape of GenAI and Large Language Models (LLMs) integration into business processes, the risks to sensitive data, individual privacy, and intellectual property are escalating. Recognized authorities like OWASP and NIST are pinpointing emerging threats, highlighting the urgent need for robust security measures to protect GenAI applications.

LLM firewalls are designed with specific policies covering data, tone, and topics, and include proactive measures such as warning and session termination. This helps prevent external attacks and control internal misuse while preserving the integrity of your data.

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Ensure robust data security controls to accelerate Agentic AI adoption across the enterprise.

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Discover shadow and cloud-native assets and accurately classify data

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Analyze breach impact & automate notifications to affected individuals

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Understand data lineage and secure real-time streaming data

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Monitor user access to data and enforce least privilege controls

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Build safe enterprise AI systems

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Implement rule-aware AI copilots across your organization’s data anywhere

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Data Vectorization and Ingestion
Extract info from complex Unstructured Files, convert it into AI-ready formats, and sync to vector databases

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Data Curation and Sanitization for AI
Transform raw, unstructured files into data ready for model training and tuning

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Context-aware LLM Firewalls
Protect AI interactions with intelligent retrieval, response, and prompt firewalls

View

Unstructured Data Governance
Manage and govern unstructured data to enable its safe use with generative AI

View
Govern data for safe innovation

Data Discovery & Classification
Discover shadow and cloud-native assets and accurately classify data

View

Unstructured Data Governance
Manage unstructured data to enable safe use with generative AI

View

Data Access Governance
Monitor sensitive data access and prevent unauthorized use

View

AI Governance
Establish controls for safe adoption of AI technologies including GenAI

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Data Catalog
Enable users to easily find, understand, trust and access the data they need

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Data Lineage
Automatically track changes and transformations of data throughout its lifecycle

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Data Quality
Conduct data quality checks and validation across various data types

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Automate data privacy operations

Data Mapping Automation
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Comply with emerging AI regulations and ensure safe use of AI

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Data Subject Request Automation
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Automate your entire assessment lifecycle and demonstrate compliance

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Use automation to audit and improve compliance with global regulations and industry standards

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Consent Management
Manage your first-party and third-party consent lifecycle from scanning to reporting

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Seamlessly track and manage user consent with your mobile app, get compliant with all major global regulations.

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