Day One Recap at RSAC Conference: AI in Security Takes Center Stage with Enthusiasm

** Reinventing Cybersecurity with Agentic AI: A New Era of Security Operations**

AI has taken center stage at the RSAC Conference, becoming the buzzword across the security industry. In Hugh Thompson's opening remarks, he emphasized, "AI has flipped everything. The way attackers operate, the wide-spread use of AI, the security implications, it's massive change."

From generative AI technologies like ChatGPT, DeepSeek, and Copilot, the conversation has shifted towards agentic AI. This new development involves the application of AI to traditional security domains, especially in the security operations center. Other topics include AI-driven application security, defending against adversarial attacks on large language models (LLMs), and compliance and governance.

In a keynote, Vasu Jakkal, Microsoft's corporate vice president for security, highlighted agentic AI as a pioneering technology of our time due to its ability to help attain rapid competency across multiple domains. Jakkal stressed that security is an early adopter of AI, contending that "AI has the best use case, or definitely the most serious use case, in security."

Jeetu Patel, Cisco's Executive Vice President and Chief Product Officer, echoed this sentiment, predicting that security would be a key driver for AI adoption. Interestingly, Patel noted that this trend is somewhat ironic given security practitioners' tendency to be wary of new technologies.

On Monday, Cisco announced its open-source AI model built specifically for security purposes. Patel stated, "We're using general models out there in the market, and what the security community needs right now is its own AI model."

The RSA Innovation Sandbox competition showcased the growing role of AI in startups. Of the ten finalists, seven had prominent AI components in their businesses. However, the judges posed tough questions reflecting the industry's challenges, such as the difficulty of controlling multiple AI agents or the resource demands of implementing numerous checks on AI processes.

Moinul Khan, co-founder and CEO of Aurascape AI, shared the optimistic perspective of many security executives, stating that AI will become mainstream in the next few years, making solutions like theirs increasingly relevant.

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A Deeper Look at Agentic AI in Cybersecurity

Operational Impact and Use Cases

Automation and Efficiency: Agentic AI streamlines repetitive tasks by automating log parsing, evidence gathering, and timeline creation, freeing up analysts to focus on high-value activities.
Threat Detection and Response: AI agents support human analysts with rapid decision-making during unpredictable, high-stress situations, accelerating investigation and response.
Continuous Improvement and Adaptability: AI agents learn and refine their reasoning, adapting to new threats and enhancing overall cyber resilience.

Integration with Existing Security Frameworks

Digital Twins and Simulations: Some vendors combine agentic AI with digital twin technology, enabling organizations to test their defenses proactively and refine their responses to evolving threats.
Proactive Threat Management: Agentic AI processes threat intelligence, integrates vulnerability data, and simulates potential attacks against IT infrastructures. It then recommends and sometimes implements protective measures.

Future Trends in Agentic AI for Cybersecurity

Greater Autonomy and Decision-Making: Future AI agents will make complex decisions autonomously, taking on active incident management and orchestration of security responses.
Human-AI Collaboration: The trend is toward deeper collaboration, with AI agents handling routine tasks and supporting human analysts with context, next steps, and evidence-based recommendations.
AI-Driven Risk Anticipation: AI will increasingly anticipate risks, simulate attack scenarios, and provide actionable insights before threats materialize, enabling organizations to shift from reactive to proactive security models.
Policy and Ethical Frameworks: As agentic AI becomes more embedded in security operations, a heightened focus will be placed on developing policy, technical safeguards, and organizational practices to ensure secure, responsible deployment.

Utilization by Established Vendors and Startups

Established Vendors: Companies like Trend Micro are integrating agentic AI into their security platforms, focusing on enterprise-grade solutions that offer scalability, integration with existing tools, and robust support.
Startups: New entrants often focus on niche problems, leveraging agentic AI for innovative uses, such as autonomous threat hunting, anomaly detection, and rapid incident response. Startups are agile in adopting the latest AI research and can quickly adapt to emerging threats, providing specialized solutions that complement or outperform legacy systems.

Agentic AI is poised to revolutionize the cybersecurity landscape, empowering organizations to adapt to the rapidly evolving threat landscape, reduce analyst burnout, and transition from reactive to proactive security postures.

In the cybersecurity realm, the application of Agentic AI is expected to enhance compliance and governance by automating repetitive tasks such as log parsing and evidence gathering, thereby allowing analysts to focus on high-value activities like responding to complex threats.
Established vendors like Trend Micro are integrating Agentic AI into their security platforms, aiming to provide enterprise-grade solutions that offer scalability, integrate with existing tools, and help organizations transition from reactive to proactive security postures by anticipating risks and simulating attack scenarios.