You’re a CISO at a mid-size financial services firm. Your security team just flagged an alert: a developer inadvertently uploaded a dataset containing customer names and account numbers into a generative AI tool – bypassing every review process you thought was working. Now your compliance team is asking which systems were exposed and your legal team wants to know if GDPR or PCI DSS reporting is triggered. You have no clear answers.

This scenario plays out across industries every day, and it doesn’t require a sophisticated attack – just a single unclassified file and an unsecured AI prompt. The core problem isn’t intent – it’s visibility. Without a systematic way to discover and classify sensitive data before it reaches AI pipelines, organizations are operating on trust rather than evidence.

Commvault Data & AI Security gives teams clear visibility and control over sensitive data by scanning, classifying, and governing it across structured, semi-structured, and unstructured environments — so they can quickly understand what data they have, where it resides, and which users or AI models are allowed to access it.

What Is Sensitive Data Discovery?

Sensitive data discovery is the automated process of scanning an organization’s data environments to identify what sensitive data exists and where it lives so that you can then apply policies to the data for access, risk, or lifecycle management.. That includes structured databases, unstructured file stores, cloud buckets, and backup repositories – anywhere regulated or confidential information might reside.

For most enterprises, this data is scattered across dozens of environments. Customer PII lives in cloud storage. PHI resides in legacy on-premises systems. Intellectual property and API keys may be embedded in files that haven’t been accessed in years. Without automated discovery, security teams have no reliable way to know what they’re protecting – or what they’re inadvertently exposing. Research suggests 99% of organizations have sensitive data exposed that AI systems can inadvertently surface. Commvault Cloud helps address this challenge through Risk Analysis, which performs continuous, DSPM-aligned discovery across live and backup environments.

Why Does Sensitive Data Discovery Matter for AI Security: When sensitive data is undiscovered and unclassified, it doesn’t just sit quietly – it moves. As employees and systems feed data into generative AI tools, unclassified sensitive data can enter AI pipelines without review, without governance, and without any audit trail. Commvault Cloud Risk Analysis helps teams close this gap before sensitive data reaches an AI prompt or a training dataset. 

How Does Data Classification Work?

Once data is discovered, classification uses machine learning to tag it by type and sensitivity – identifying PII, PHI, PCI, financial records, API keys, intellectual property, and other confidential categories. Classification is what makes discovery actionable: without it, you have a map but no legend.

Commvault Cloud classification ability includes more than 100 pre-built ML classifiers and supports custom classification schemas, covering structured, unstructured, and semi-structured data formats. Organizations can use out-of-the-box templates for region specific data types, like U.S. social security numbers,for regulations like GDPR, HIPAA, PCI DSS, or configure classifiers to match their specific data taxonomy. Classification metadata is synchronized to live environments so downstream teams can act on consistent sensitivity labels. It also helps prevent sensitive shadow data from being unknowingly ingested into AI training pipelines.

100+ pre-built ML classifiers: Covers PII, PHI, PCI, financial data, API keys, and intellectual property across structured, semi-structured, and unstructured data formats. Custom classification schemas: Configure classifiers to match your specific data taxonomy and business needs — not limited to out-of-the-box frameworks. Regulatory templates: Pre-built templates for GDPR, HIPAA, and PCI DSS for rapid compliance alignment. Metadata synchronization: Classification labels synchronized to live environments so security, compliance, and data engineering teams act on consistent data.

Why Does Access Governance Need to Cover AI Models, Not Just Human Users?

57% of cyberattacks now begin with compromised identities – and the attack surface has expanded well beyond human users. AI models, agents, and automated pipelines now access sensitive data at scale, often without the same controls applied to people.

Commvault Cloud Data & AI Access Governance extends classification-based policy controls to both human users and AI models. Powered by the Satori Cyber integration, it applies real-time, agentless access controls to structured data platforms including Snowflake, Redshift, Databricks, and Microsoft Fabric – with LLM prompt monitoring to help prevent sensitive data from leaking through AI responses.

Agentless enforcement: Real-time access controls applied without installing agents on data platforms — via the Satori Cyber integration. LLM prompt monitoring: Monitors AI inputs and outputs for sensitive or unpermitted data, applying privacy controls to minimize exposure through generative AI interactions. Platform coverage: Supports Snowflake, Redshift, Databricks, and Microsoft Fabric. Identity-based policy: Controls extend to both human users and AI models with consistent policy enforcement across both.

Who Is Commvault Data & AI Security For?

Commvault Data & AI Security is designed for enterprise security teams, compliance officers, and AI and data teams that need unified visibility and governance across a sprawling, hybrid data estate.

For security teams: identifies data hotspots, closes overly permissive access gaps, and surfaces AI-specific risks – reducing blast radius in the event of a breach.

For compliance teams in regulated industries: supports GDPR, HIPAA, PCI DSS v4.0, CCPA, DORA, NIS2, and the EU AI Act through discovery, classification, and audit-ready reporting. Commvault was recognized in the IDC MarketScape: Worldwide Cyber-Recovery 2025 Vendor Assessment.

For AI and data teams: Commvault Cloud Data Rooms offers a governed, self-service workspace to discover, classify, and export trusted backup data in open AI-ready formats.

Sensitive data discovery and classification: Scans structured, semi-structured, and unstructured data using 100+ pre-built ML classifiers, with support for custom schemas. 

Data and AI access governance: Applies classification-based policy controls to restrict access for human users and AI models – with masking, redaction, and real-time enforcement via Satori Cyber. 

Data Risk Assessment: Identifies high-sensitivity data concentrations and redundant, obsolete, or trivial (ROT) data to help teams prioritize remediation. 

LLM prompt monitoring: Monitors AI inputs and outputs for sensitive or unpermitted data and applies privacy controls. 

Commvault Data Activate for AI activation: Governed workspace to export trusted backup data in open AI-ready formats with built-in classification, redaction, and audit trails. 

DSPM-aligned discovery: Continuously monitors data location, access permissions, and security configuration – detecting misplaced data and unauthorized access in real time. 

Commvault Data & AI Security brings together the discovery, classification, and access governance capabilities organizations need to help reduce sensitive data exposure and support responsible AI use. Rather than applying blanket protection across all data, Commvault helps teams understand their data landscape – what they have, where it lives, and who or what has access – then apply targeted controls where they matter most. Combined with immutable backup and cyber recovery capabilities, this approach helps organizations move from reactive data management to proactive, policy-driven governance that supports both cyber resilience and compliant AI adoption.