The Rise of AI in Data protection: A Deep Dive into Leading Solutions
The data protection landscape is undergoing a rapid conversion, fueled by the integration of Artificial Intelligence (AI) and Machine Learning (ML). No longer simply about backup and recovery, modern solutions are leveraging AI to proactively defend against threats, optimize performance, and simplify complex IT operations. This article provides an in-depth look at how leading vendors – Cohesity, Commvault, Druva, Rubrik, and Veeam – are incorporating AI into their offerings, and what that means for your organization.
Why AI is Crucial for Modern Data Protection
Traditional data protection strategies are struggling to keep pace with the escalating sophistication of cyberattacks, particularly ransomware. AI offers a critical advantage by automating threat detection, accelerating recovery, and providing bright insights that were previously unachievable to obtain. Beyond security, AI is also driving efficiency gains in areas like capacity planning and data management, ultimately reducing costs and improving overall data resilience.
how Leading Vendors are Implementing AI
Here’s a detailed breakdown of how each vendor is utilizing AI within their data protection suites:
1. Cohesity: AI-Powered Resilience & Insight
Cohesity is embedding AI across it’s platform, focusing on proactive threat mitigation and streamlined data access.
Ransomware Defense: Cohesity Turing utilizes AI/ML for complete discovery, detection, and reporting of potential ransomware threats.
DataHawk: This offering leverages AI-based threat detection, “cyber vaulting,” and a complex data classification tool to bolster ransomware protection.
intelligent Data Access: Gaia, Cohesity’s conversational search tool, allows IT teams to interact with backup data using natural language, simplifying data retrieval and analysis.
Capacity Optimization: AI-driven capacity planning helps organizations optimize storage costs and ensure sufficient resources for data protection needs.
2.Commvault: AI-driven Recovery & Compliance
Commvault’s Metallic AI suite is at the forefront of intelligent data protection, offering advanced capabilities for both recovery and risk management.
Anomaly Detection: AI-assisted anomaly detection identifies unusual activity that could indicate a security breach or data corruption.
Accelerated Recovery: “AI-enabled bursting” allows for faster data recovery, minimizing downtime during critical incidents.
Data Classification: AI-based data classification prioritizes backups and enhances compliance efforts by identifying sensitive data.
Threat & Risk Management: Commvault leverages AI/ML for proactive threat detection, recovery assistance, and overall risk assessment across on-premise and cloud environments.
3. Druva: AI as a Copilot for Data Protection
Druva is pioneering the use of AI as a collaborative assistant for IT teams, with a focus on productivity and proactive security.
Dru – The AI Copilot: Launched in 2023, dru provides a conversational interface to simplify management, improve reporting, and empower better decision-making. Dru Investigate: This tool utilizes large language models and retrieval-augmented generation to accelerate security investigations, identify at-risk data, and reduce the workload on security teams. It provides a focused view of potential threats within backup environments.
4. Rubrik: AI for Cyber Response & Recovery
Rubrik’s AI assistant, Ruby, is designed to help organizations respond to and recover from cyberattacks with speed and precision.
Cyber Response Automation: Ruby provides AI-powered anomaly detection and guidance on isolating and removing infected data.
Threat Identification: Machine learning analyzes data deletions, modifications, and encryption to identify hidden threats within backups. Rapid Recovery: Rubrik identifies the most recent clean backups and facilitates the creation of clean VMware instances for swift recovery.
5. Veeam: AI-Powered Monitoring, Prediction & Security
Veeam is integrating AI across its platform to enhance backup performance, predict potential risks, and strengthen security posture.
Predictive Analysis: AI-based analysis monitors backup performance and identifies potential risks before they impact operations.
Ransomware & Threat Detection: ML-driven threat detection continuously scans backups for anomalies, providing early warning of potential attacks.
Data Management & Classification: AI-powered data management and classification enable smarter storage decisions and optimize resource allocation.
* AI Model access: Veeam supports the Model Context protocol, allowing secure access to enterprise data for AI model training - opening new possibilities for data-driven innovation.
