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Kaspersky Leverages 20 Years of AI Innovation to Transform Cybersecurity Landscape

Kaspersky’s AI-driven cybersecurity innovations saved businesses an average of $2.2 million in 2024, thwarting over six million mobile attacks.

Cybersecurity is rapidly evolving, driven by the increasing complexity and speed of cyber threats. A recent survey revealed that 94% of organizations consider AI-powered solutions essential to counter these challenges. In 2024, businesses utilizing AI and automation in their cybersecurity strategies saved an average of $2.2 million compared to those that did not. This demand has prompted vendors to race to offer “next-gen” AI features. However, not all AI solutions are created equal; many are hindered by limited datasets or inadequate context, leading to potential false positives and missed threats.

Among the leaders in this space is Kaspersky, which has been integrating AI and machine learning (ML) into its cybersecurity offerings for over 20 years. While popular culture depicted AI as a threat, Kaspersky has focused on harnessing its potential to enhance security. This foresight, alongside sustained investment, has positioned Kaspersky to provide innovative, reliable protection backed by years of experience and proven efficacy.

By accumulating vast amounts of anonymized global telemetry from millions of endpoints, Kaspersky has built advanced ML models that are resilient against evolving threats. Unlike many competitors, Kaspersky embeds AI into every aspect of its technology stack. Ilya Markelov, Head of Unified Platform at Kaspersky, emphasized, “All of our products include AI technology. SIEM, EPP, EDR, NDR, XDR, MDR, Threat Intelligence, all of them. Where there’s no AI assistant, there’s KSN, a global network delivering insights from our cloud-based models to our customers. AI drives almost everything we do.” This comprehensive integration leads to quicker detection and smarter automation across its product range.

Kaspersky’s commitment to AI innovation began in 2004 with the development of its first AI/ML technology for automatic malware analysis, humorously named Auto-woodpecker. This tool automated the labor-intensive task of analyzing malware, significantly enhancing productivity. Kaspersky has since patented numerous AI technologies, including an automated false-positive testing mechanism in 2015, and has seen a marked increase in the effectiveness of its AI-driven products.

Most recently, in 2025, Kaspersky upgraded its Security Information and Event Management (SIEM) platform with a new AI module designed for faster and more effective alert triage. Kaspersky’s extensive investment in AI has culminated in a portfolio that offers rapid, intelligent protection tailored for businesses of all sizes. Its systems provide real-time threat detection, behavioral analysis, and automated responses to both known and emerging threats.

In 2024 alone, Kaspersky’s cloud-based AI technology thwarted over six million attacks on mobile users by identifying previously unknown malicious Android applications in real-time. Its Anti Targeted Attack (KATA) solution employs ML to detect complex, multi-stage threats, while the machine learning-based web phishing detection engine flags approximately 1,000 phishing webpages daily. This full integration of AI at every level allows even smaller businesses to access enterprise-grade protection without extensive in-house resources.

Kaspersky’s long-standing commitment to in-house AI development enables it to continuously refine its technologies and stay ahead of evolving threats. Eugene Kaspersky, the company’s CEO and founder, expressed pride in being one of the first in the cybersecurity sector to adopt AI effectively, enabling them to counter the staggering volume of nearly half a million new malware samples generated daily. As cyber threats grow in speed and sophistication, Kaspersky’s AI-driven capabilities are positioned to become an even more valuable asset in safeguarding organizations from cyber harm.

See also
Rachel Torres
Written By

At AIPressa, my work focuses on exploring the paradox of AI in cybersecurity: it's both our best defense and our greatest threat. I've closely followed how AI systems detect vulnerabilities in milliseconds while attackers simultaneously use them to create increasingly sophisticated malware. My approach: explaining technical complexities in an accessible way without losing the urgency of the topic. When I'm not researching the latest AI-driven threats, I'm probably testing security tools or reading about the next attack vector keeping CISOs awake at night.

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