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.

What are the biggest data security challenges businesses face today?

Key challenges include data sprawl across multiple clouds, unauthorized access, ransomware threats, and risks from third parties. As organizations expand digitally, sensitive data spreads across many systems, making it harder to track, secure, and manage.

Why do data security challenges keep increasing every year?

Companies are creating more data than ever, much of it stored in cloud apps, collaboration tools, and SaaS platforms. With the rapid adoption of AI and automation, the number of data exposure points grows, giving attackers more opportunities to exploit.

How can automation make data security easier?

Automation helps by continuously scanning for sensitive data, tracking its movement, and alerting teams to unusual activity. Instead of depending on manual checks, automated tools work in real time, reducing effort and cost while keeping security consistent across the entire data environment.

How can Securiti help solve modern data security challenges?

Securiti’s Data Security and Privacy Automation Platform helps organizations find, classify, and protect sensitive data across on-prem systems, cloud environments, and SaaS apps. It brings data security, privacy, and compliance controls together in one platform, reducing risk and helping maintain continuous compliance with global regulations.

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June 1, 2025

Top Data Security Challenges & How to Solve Them

Learn the top data security challenges organizations face today. Learn about the challenge and its solution. Enhance your data security posture today.

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How to Implement a Robust Data Security Framework

Data privacy regulations mandate strict data security measures. Learn how to implement a robust data security framework to ensure swift compliance.

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What is Enterprise Data Security?

Get comprehensive insights into enterprise data security, what it is, its importance, key components, and how Securiti helps ensure the utmost enterprise data security.

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What is Cloud Security Posture Management (CSPM)?

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Why Enterprises Need DSPM in the AI Era

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What are Data Security Controls & Its Types

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What is cloud Security? – Definition

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Ensure robust data protection while scaling AI agents and copilots. Learn how to accelerate AI agents adoption securely across the enterprise

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Monitor user access to data and enforce least privilege controls

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

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Assess & improve compliance with security best practices frameworks

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Breach Impact Analysis
Analyze breach impact & automate notifications to affected individuals

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Data Flow Governance
Understand data lineage and secure real-time streaming data

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Build safe enterprise AI systems

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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

View

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

View

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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Conduct data quality checks and validation across various data types

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Automate data privacy operations

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Manage your entire data mapping lifecycle and automate RoPA reports

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Comply with emerging AI regulations and ensure safe use of AI

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