What is Protect & Leverage AI?
Protect & Leverage AI is a dual discipline in enterprise cyber resilience: protecting the full AI application stack—data lakes, pipelines, vector databases, model checkpoints, and compute infrastructure—from threats like data poisoning, adversarial attacks, and model corruption; and leveraging AI-enhanced intelligence to accelerate threat detection, strengthen anomaly detection, and automate recovery. Commvault Cloud is built for both sides—delivering comprehensive AI data protection at scale, AI-assisted cyber resilience across hybrid environments, and secure AI extension through governed data activation and agentic automation.
Pontos principais
AI introduces powerful new capabilities for cybersecurity—and a new class of risks that necessitate dedicated protection. The enterprises that lead in AI adoption will be those that protecteleverage AI simultaneously, from a single unified platform.
- Mais de75% das organizações relatam ter sofrido violações de segurança relacionadas à IA,e26% of USeUK enterprises have faced AI data-poisoning intrusions.
- AI introduces new attack vectors—contaminação de dados, entradas adversárias, inversão de modelos,injeção de prompts,emachine identity compromise—that traditional data security tools were not designed to detect or stop.
- AI-enhanced threat detectioneanomaly detection help identify zero-day threats, behavioral anomalies,ephishing patterns at a speedescale no human security team can sustain alone.
- Generative AI can be used in cybersecurity for threat intelligence synthesis, phishing detection, automated incident response, predictive IT operations,eagentic recovery orchestration.
- Protecting AI workloads requires immutable, air-gapped backup of training data, model checkpoints, vector databases,ecompute infrastructure—not just application-layer data security controls.
- Commvault Cloud unifies AI workload protection, AI-enhanced cyber resilience,esecure AI extension through Data Activateean MCP-based agentic automation framework.
Why Protect & Leverage AI Matters
A IA é tanto o risco quanto a solução
AI has fundamentally changed the threat landscape—in both directions. On one side: data poisoning attacks that corrupt training data, adversarial prompts that manipulate model behavior, model inversion attacks that extract sensitive training data,eAI-assisted malware that adapts to evade detection in real time.
Por outro lado: recursos de segurança de dados aprimorados por IA que detectam ameaças de dia zero, identificam anomalias comportamentais em grande escala, sintetizam inteligência de ameaças de diversas fontes e automatizam a Recovery cibernética por meio de orquestração inteligente.
Mais de75% das organizações relatam ter sofrido violações de segurança relacionadas à IA,e26% of USeUK enterprises have faced AI data-poisoning intrusions. Organizations without a platform purpose-built to both protecteleverage AI can be exposed at the most critical layer of their infrastructure
Protegendo os dados de IA: o novo imperativo de resiliência
The AI application stack is a new and largely unprotected attack surface. Data lakes, training pipelines, vector databases, model checkpoints, and GPU compute infrastructure represent high-value enterprise assets requiring the same protection disciplines applied to traditional workloads—immutable backup, air-gapped storage, access governance, anomaly detection, and rapid, clean recovery.
Um modelo comprometido ou um conjunto de dados de treinamento adulterado pode corromper decisões e resultados de negócios em toda a empresa sem acionar um alerta de segurança tradicional. O Commvault Cloud pode estender a proteção de nível empresarial a lagos de dados, sistemas de arquivos, sistemas de recuperação vetorial e infraestrutura de computação na AWS, no Azure e no Google Cloud.
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Detecção de ameaças e resiliência aprimoradas por IA
AI-enhanced threat detection and anomaly detection change what is possible for enterprise security operations. Machine learning models analyze behavioral signals—user access patterns, backup job anomalies, data movement, and system activity—simultaneously and in real time, identifying deviations that indicate ransomware staging, data exfiltration, or credential abuse long before an attack completes.
A IA generativa sintetiza feeds de inteligência de ameaças em resumos prontos para analistas, gera insights preditivos sobre operações de TI e automatiza etapas de resposta a incidentes, como isolar sistemas afetados e redefinir credenciais comprometidas. Narecuperação cibernética, AI-enhanced Synthetic Recovery analyzes multiple backup versions to reconstruct a single verified, uncompromised recovery point—reducing the manual forensic effort that slows recovery after a ransomware event. Commvault Cloud embeds AI-enhanced intelligence across the detection and recovery lifecycle through Metallic AI, Arlie, and the agent library.
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Aproveitando a IA: dos dados protegidos à inovação
Protecting AI data creates a second compounding benefit: the data an organization protects is also its most complete and trusted dataset, making it a powerful foundation for AI and analytics initiatives. The capability of Commvault Cloud’s Data Activate bridges data protection and data intelligence—enabling organizations to discover, classify, and export governed backup data in open AI-ready formats (Apache Parquet, Iceberg) directly to platforms such as Snowflake and Azure AI, minimizing new pipelines or data security risks.
O MCP Server amplia ainda mais isso: permitindo que agentes de IA corporativos consultem o Commvault Cloud, acionem fluxos de trabalho de proteção e iniciem operações de Recovery por meio de interfaces conversacionais seguras e regidas por políticas.
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How Protect & Leverage AI Works
Key Components of Protect & Leverage AI
Commvault Cloud delivers Protect & Leverage AI through four interconnected capability sets: securing the AI application stack, embedding AI-enhanced intelligence into resilience operations, enabling agentic automation at enterprise scale, and activating protected data for AI and analytics. Together they form a unified foundation for responsible AI adoption.
1) AI Workload Protection and Recovery
Proteção abrangente para toda a pilha de IA em quatro categorias de cargas de trabalho:
Unified data and AI platforms: Amazon Redshift, Databricks, Google BigQuery.
Data lake storage and distributed file systems: Azure Data Lake Storage Gen 2; Amazon S3, S3 Express One Zone, FSx; HDFS, Lustre, GPFS.
Search and vector retrieval systems: Elasticsearch, Apache Solr, Azure Cosmos DB for NoSQL, Azure Database for PostgreSQL, Amazon Aurora PostgreSQL, Amazon DocumentDB, Amazon DynamoDB, Amazon RDS for PostgreSQL, Google Cloud SQL for MySQL and PostgreSQL, AlloyDB, PostgreSQL.
Compute and DevOps infrastructure: Amazon EC2 Trn2 UltraServers, GPU-enabled compute, AI on Kubernetes, Azure DevOps, Capacity Blocks for ML, GitHub, GitLab.
Backup imutável e isolado fisicamente, com recuperação granular e governança baseada em políticas, ajuda a manter ativos de dados de IA confiáveis em todas as nuvens e regiões. O AI Threat Defense ajuda a proteger contra injeção de prompts, adulteração de dados, ataques adversariais a modelos e comprometimento da identidade de máquinas
2) AI-Enhanced Detection and Synthetic Recovery
Metallic AI and Commvault’s built-in AI-assisted anomaly detection are designed to continuously monitor data patterns, user behaviors, and access anomalies across hybrid environments—surfacing threats before they spread and reducing false-positive fatigue for security teams. For recovery, AI-enhanced composite cleanpoint identification analyzes multiple backup versions to build an optimized recovery point from verified, uncompromised data—rather than forcing a binary choice between restore points that may contain malware. The result is faster, more confident recovery with less manual forensic effort after a ransomware or data corruption event.
3) Arlie, Agent Library, and Agentic Automation
Commvault’s Agent Library is designed to deliver specialized AI-enabled capabilities through Arlie—Commvault’s AI assistant—with dedicated agents:
Arlie Data Sense: Analyzes logs, alerts, backup job history, and threat scan results to surface root cause analysis, data security insights, and actionable recommendations.
Arlie Recover: Orchestrates policy-basedrecuperação cibernética workflows with human-in-the-loop confirmation for critical steps—from threat containment through cleanpoint identification to validated restoration.
Arlie Advisor: Automates protection policy recommendations and monitors for configuration drift to help keep plans aligned with business and compliance requirements.
The MCP Server connects Commvault Cloud to the broader enterprise AI ecosystem—enabling ChatGPT Enterprise, Claude, and other AI assistants to query data, trigger workflows, and initiate recovery through secure, conversational interfaces. Commvault’s Responsible AI framework is designed to keep all AI-assisted operations policy-based, transparent, and subject to human oversight.
4) Data Activate: Activating Trusted Data for AI
Data Activate can transform protected backup data into governed, AI-ready assets while helping reduce risk and avoiding the need for additional data platforms. Teams can discover relevant datasets within Commvault Cloud, apply classification, redaction, and sensitivity tagging, then export curated data in open formats (Apache Parquet, Iceberg) to downstream analytics and AI platforms. Built-in role-based access control, encryption, and zero-trust architecture help maintain compliance at every step. For organizations running data lakes across cloud environments, Data Activate activates historical and operational data for model training, analytics, and compliance workflows—turning stored backups into an innovation asset with full governance and audit trails.
Protect & Leverage AI in Practice
Resiliência da IA para todos os perfis de empresas
Protect & Leverage AI applies differently depending on AI maturity, infrastructure footprint, and data security priorities. Commvault Cloud supports three profiles: enterprises hardening AI workloads against threats, security operations teams accelerating detection and recovery, and cloud-native teams activating governed data for innovation.
Protegendo cargas de trabalho de IA e data lakes corporativos
Large enterprises running AI workloads across hybrid and multi-cloud environments face a fragmented protection landscape—most enterprise backup and cloud data security platforms were not built for data lakes, vector databases, model registries, or GPU compute infrastructure. Commvault Cloud closes this gap by extending enterprise-grade immutable backup and rapid recovery to the AI application stack. For organizations running data lakes on AWS (S3, FSx, Amazon Redshift), Azure (Data Lake Storage Gen 2, Cosmos DB), or Google Cloud (BigQuery, AlloyDB), Commvault is designed to provide consistent protection policies, granular recovery, and AI threat defense against data poisoning, prompt injection, and machine identity attacks. Commvault’s integration-first approach differentiates it from cloud data security vendors requiring separate control planes for AI workloads.
Detecção, resposta e ITOps preditivas aprimoradas por IA
Security operations teams gain AI-assisted threat detection and anomaly detection that monitors data patterns, access behaviors, and backup integrity across environments — surfacing threats and generating actionable insights rather than raw alert volume. Arlie Data Sense delivers root cause analysis from log and threat scan data, helping reduce manual triage on lean security teams. Arlie Recover can transform cyber incident response into a structured operator-guided workflow—from threat containment through cleanpoint identification to validated recovery. For predictive IT operations, AI-assisted analysis can identify configuration drift, protection coverage gaps, and anomalous patterns before they escalate into incidents. This is a fundamental shift from traditional rules-based backup management to AI-enabled operational intelligence.
Ativação de dados com IA regulamentada
Cloud-native organizations building AI applications need access to trusted, governed datasets for model training, fine-tuning, analytics, and compliance—without new pipelines or data security gaps. Commvault Cloud’s Data Activate exports governed backup data in AI-ready formats (Parquet, Iceberg) natively to platforms such as Snowflake and Azure AI—using open standards, not proprietary lock-in. For organizations evaluating the best cloud data security vendor for protecting and leveraging AI, Commvault’s integration-first strategy and native hyperscaler coverage across compute, storage, and data services differentiates it from vendors requiring separate control planes or additional agents per cloud.
Perguntas frequentes
Como a IA generativa pode ser utilizada na segurança cibernética?
A IA generativa pode ser aplicada em todo o ciclo de vida da segurança cibernética de cinco maneiras de alto impacto:
- Threat intelligence synthesis: Correlating signals from multiple data security feeds into analyst-ready summaries—accelerating detection-to-decision time significantly.
- AI phishing detection: Using behavioral and linguistic analysis to help identify phishing and spear-phishing attempts that evade signature-based filters, including AI-generated social engineering content.
- Automated incident response: Orchestrating containment actions—isolating systems, resetting compromised credentials, blocking malicious IPs—faster than human response workflows.
- Predictive IT operations: Identifying configuration drift, protection coverage gaps, and anomalous access patterns before they escalate into incidents.
- Agentic recovery workflows: Orchestrating complex cyber recovery sequences through conversational interfaces, with human-in-the-loop confirmation for critical actions.
O Commvault Cloud pode oferecer todos esses cinco recursos por meio do Metallic AI e da biblioteca de agentes Arlie, que inclui o Arlie Data Sense (análise de ameaças e resumo de logs), o Arlie Recovery (coordenação de recuperação por agente) e o Arlie Advisor (orientação contextual sobre segurança e resiliência).
Como a IA aprimora os recursos de detecção de ameaças?
AI enhances threat detection in three fundamental ways over traditional rules-based approaches. First, scale and speed: AI-enhanced models analyze millions of behavioral signals—network activity, user access, backup job anomalies, and data movement—simultaneously and in real time, where human analysts can only sample.
Em segundo lugar, detecção de ameaças de dia zero e desconhecidas: a detecção de anomalias assistida por IA identifica desvios em relação às linhas de base estabelecidas sem depender de assinaturas de ataque conhecidas, detectando ameaças que as ferramentas tradicionais deixam passar até que causem danos.
Third, reduced false positives: adaptive learning allows models to distinguish genuine anomalies from normal variation over time, reducing the alert fatigue that causes analysts to miss real threats. In data protection specifically, AI-enhanced anomaly detection identifies early signs of ransomware staging—unusual encryption patterns, backup deletion attempts, privilege escalations—before the main attack payload executes. Commvault Cloud embeds AI-enhanced anomaly detection across data protection, identity resilience, and cyber recovery workflows.
Qual é a diferença entre segurança de dados com IA e proteção de dados de IA?
AI data security means applying AI capabilities to protect enterprise data—using machine learning for threat detection, access governance, sensitive data classification, anomaly detection, and compliance enforcement across all data types.
Protecting AI data means securing the data that AI systems depend on: training datasets, model parameters, inference pipelines, vector databases, and the compute infrastructure running AI workloads.
Both are required for a complete enterprise AI security strategy. Organizations that invest in AI data security but neglect their AI infrastructure expose their models to poisoning, adversarial attacks, and corruption. Organizations that protect AI data but don’t apply AI in their data security operations are defending against modern threats with outdated tools.
O Commvault Cloud foi projetado para lidar com ambos em uma única plataforma: protegendo de forma abrangente as cargas de trabalho de IA, ao mesmo tempo em que incorpora detecção aprimorada por IA, detecção de anomalias e inteligência de recuperação baseada em agentes em todas as operações.
Quais são as principais ameaças às cargas de trabalho de IA que as empresas devem enfrentar?
Principais vetores de ameaça direcionados à infraestrutura de IA:
- Data poisoning and manipulation: Attackers inject malicious data into training sets to corrupt model behavior, causing incorrect outputs or creating exploitable backdoors.
- Adversarial attacks: Subtle input manipulations trick models into incorrect classifications—exploiting how neural networks process information.
- Model inversion attacks: Attackers extract sensitive training data by analyzing model outputs and behavioral patterns, exposing proprietary information.
- Prompt injection: Malicious inputs manipulate large language model behavior beyond its intended parameters—relevant for any enterprise using GenAI or agentic workflows.
- Machine identity compromise: Attackers hijack AI service accounts or API credentials to gain privileged access to AI systems and the data they process.
- AI supply chain attacks: Compromises in data sourcing, third-party model components, or deployment pipelines that undermine AI integrity at scale.
Commvault Cloud’s AI threat defense helps protect against prompt injection, poisoned models, and machine identity attacks. AI-assisted anomaly detection monitors for access patterns and behavioral signals that can indicate active threats to AI infrastructure.
Como a automação por IA melhora as operações de TI e o gerenciamento de backup em comparação com as abordagens tradicionais?
Traditional backup management requires administrators to manually configure policies, monitor job success, identify coverage gaps, and execute recovery procedures—creating operational overhead that scales poorly. AI automation can improve this in three specific areas. In protection management: AI-enabled policy recommendations analyze workload metadata and usage patterns to optimize backup configuration and continuously monitor for configuration drift heloping to remove manual review cycles.
In operations intelligence: AI-assisted log analysis surfaces root cause analysis and actionable recommendations rather than raw alert data, reducing time-to-resolution for operational issues and incident response. In recovery orchestration: agentic automation guides teams through complex recovery workflows—threat containment, cleanpoint identification, validated restoration—with structured decision support rather than fully manual execution.
A principal diferença em relação ao gerenciamento tradicional de backup: a automação por IA é capaz de lidar com a complexidade em grande escala, identificando quais cargas de trabalho parecem estar com proteção insuficiente, quais pontos de recuperação estão limpos e quais ações devem ser priorizadas em seguida. O Commvault Cloud pode oferecer esses três aspectos por meio do Metallic AI, da biblioteca de agentes Arlie e da estrutura do MCP Server.
Como a Commvault aborda a proteção e o aproveitamento da IA?
Commvault Cloud is designed to address both sides of the AI data security equation from a single unified platform. For data protection: comprehensive backup, immutable storage, and rapid recovery for the AI application stack—data lakes, vector databases, model registries, and compute infrastructure across AWS, Azure, and Google Cloud—with AI threat defense against data poisoning, prompt injection, and machine identity attacks.
Para resiliência: o Metallic AI e a biblioteca de agentes Arlie incorporam detecção de ameaças aprimorada por IA, detecção de anomalias e orquestração de Recovery por agentes em todas as operações da plataforma, incluindo inteligência para detecção de phishing, insights preditivos de operações de TI e resposta automatizada a incidentes. Para extensão: o Data Activate ativa dados de backup regulamentados em formatos abertos (Parquet, Iceberg) para análise, treinamento de modelos e conformidade; e o MCP Server permite que agentes de IA corporativos consultem, automatizem e interajam com a Commvault Cloud por meio de interfaces conversacionais de maneira segura.
Commvault operates under a Responsible AI framework focused on reliability, transparency, and human oversight—differentiating it from cloud data security vendors requiring proprietary AI layers or separate control planes. Integration-first: connects natively to Databricks, CrowdStrike, AWS, and other AI and data security ecosystems.
Proteção de dados pronta para IA
IA na Commvault: Inovação segura, resiliência inteligente
