AI in Cyber Security - Examples in 2025

AI-powered software, trained on vast datasets, now monitors thousands of endpoints, cloud containers, and network flows simultaneously. Artificial intelligence companies like Vectra AI and ReliaQuest use behavior-based detection rather than signature-based rules. This means they can catch zero-day threats, insider anomalies, and lateral movement across a network in real time—before damage occurs. These AI-powered systems learn “normal” behavior and flag deviations instantly, significantly improving response speed and accuracy.

With the sheer volume of alerts generated daily, human analysts can suffer from alert fatigue. AI security platforms reduce this burden using machine learning to automatically prioritize threats. Solutions from companies like Deep Instinct apply predictive analysis to sort critical threats from benign anomalies. This triage ensures that human analysts focus only on high-impact incidents. Artificial intelligence companies are increasingly embedding autonomous triage engines into their platforms, reducing false positives by up to 90%.

(XDR) platforms now come equipped with AI agents that autonomously isolate infected endpoints, block malicious IP addresses, or roll back compromised sessions. AI-powered security tools from vendors like CrowdStrike and SentinelOne automatically contain attacks before they propagate. These solutions are often the result of cutting-edge innovations developed by artificial intelligence companies that blend cybersecurity with real-time automation and threat intelligence.

As organizations increasingly deploy their own AI models, the need for governance becomes crucial. Tools from OneTrust and BigID provide intelligent compliance automation, ensuring that data governance policies, GDPR/CCPA regulations, and AI model explainability standards are met. These platforms use AI to audit, document, and secure AI pipelines—helping enterprises avoid non-compliance. By leveraging AI for governance, artificial intelligence companies help bridge the gap between innovation and regulation.

2025 marks the rise of agentic AI—AI agents capable of taking initiative and learning on their own. Behavioral analytics platforms like Vectra Detect and Darktrace’s Immune System use these agents to analyze user behavior over time, detect abnormal access patterns, and anticipate threats before they occur. For instance, if a user’s login time, geolocation, or data access habits suddenly deviate from normal, the system can flag or block the session. These advancements are the result of major breakthroughs by artificial intelligence companies investing in self-learning and generative cyber defense models.

With enterprises moving to hybrid cloud and multi-cloud architectures, securing data, apps, and APIs across disparate environments is a major challenge. AI-powered tools offer cloud-native security that integrates across platforms like AWS, Azure, and Google Cloud. Companies like Trend Micro and Palo Alto Networks are deploying AI to protect cloud workloads dynamically, making policy enforcement and threat monitoring seamless.

Artificial intelligence companies are enabling a new era where security is continuous, context-aware, and scalable across every environment—from edge devices to hyperscale cloud infrastructure.

Vectra AI’s NDR/XDR solutions (Vectra Detect, Recall, Stream) analyze attacker behavior signals across network and cloud environments, using real-time AI to correlate and prioritize attack data—now rated in Gartner’s 2025 Magic Quadrant.

This company applies deep learning to prevent and detect malware and advanced persistent threats (APTs) at scale. Its deep-learning AI predicts attacks before they happen by identifying anomalous behavior in real time.

Known for threat intelligence, Anomali now integrates NLP-based tools like Lens and Cloud-native XDR to automatically analyze structured and unstructured threat data, automating detection and response workflows globally.

Designed in India, Vastav.AI specializes in real-time deepfake detection for video, image, and audio content. Launched in March 2025, it boasts 99% accuracy in identifying AI-generated media, helping combat misinformation and fraud in sectors like media and law enforcement.

This Israeli startup (raised $100M Series B in July 2025) focuses on securing AI agents themselves. Its platform monitors autonomous agents, sets guardrails, detects vulnerabilities, and ensures regulatory compliance—addressing the increasing risk of rogue AI systems.

Traditionally known for privacy and compliance tools, OneTrust now offers agentic AI features like OneTrust Copilot and automated breach-response workflows. It integrates with Azure OpenAI for AI governance throughout the model lifecycle.

Companies like ReliaQuest, Vectra AI, Deep Instinct, and OneTrust utilize agentic AI and open XDR architectures to monitor and autonomously react to threats. This capability is critical as threat actors increasingly deploy AI to conduct phishing, credential stuffing, or reconnaissance, making human-only detection obsolete.

Platforms such as Vastav.AI showcase how AI can identify manipulated media—vital in 2025, when deepfake scams surged globally by over 3000% in 2023–2024. This has applications in media authentication, election integrity, and fraud detection.

Emerging tools like AdaPhish use LLMs and vector databases to automate phishing detection and anonymization, enabling adaptive, scalable protection while preserving privacy for security education and incident tracking in real time (arXiv).

AI agents like RunSybil’s Sybil simulate attacker workflows—mapping sites, probing inputs, chaining vulnerabilities—to perform continuous, automated penetration testing. These AI-powered pen-test platforms offer “artificial intuition” beyond traditional scanners (WIRED).

In a landmark move, Palo Alto Networks finalized a $25 billion acquisition of CyberArk in July 2025. The acquisition significantly strengthens Palo Alto’s identity and access security capabilities by integrating CyberArk’s privileged access management solutions with AI-driven threat detection systems. This strategic alignment highlights the growing importance of AI-powered security tools as a core pillar of modern cybersecurity frameworks.

Trend Micro deepened its alliance with Google Cloud to enhance its flagship security platform, Vision One. By integrating Google’s advanced AI models, Trend Micro has boosted its ability to deliver real-time compliance monitoring, intelligent data protection, and machine learning–powered scam detection across complex, multi-cloud environments. This partnership illustrates how leading Artificial Intelligence Companies are combining cloud and AI innovations to tackle emerging cyber threats more efficiently.

Cybercriminals are also embracing AI—deploying AI chatbots to negotiate ransomware demands and leveraging automation for targeted phishing and system breaches. In a recent wave of attacks, over 400 SharePoint servers were compromised using AI-enhanced tactics. This surge in attacker sophistication has sparked a growing demand for AI-based threat hunting solutions, such as Nebulock, a rising platform backed by Bain Capital. The increasing complexity of threats reinforces the urgent need for AI-driven, adaptive cybersecurity strategies.