Agentic AI vs Generative AI: What CISOs Learned at RSA Conference 2025

RSA Conference 2025 was not just another tech event; it was a wake-up call. For many CISOs (Chief Information Security Officers), it became clear that the future of cybersecurity is no longer just about firewalls, signatures, or even generative AI. It’s about autonomous decision-making, adaptability, and mission-focused intelligence, also known as agentic AI.

While generative AI is still dominating headlines, its successor in real-world applications may well be its more independent and proactive cousin. This year’s RSA Conference made it official: the conversation has shifted from generative AI vs agentic AI to how both can be integrated effectively and securely into enterprise defense strategies.

What Is Agentic AI vs Generative AI?

The difference between agentic AI and generative AI lies in their fundamental approach to action.

Generative AI creates. It synthesizes content, text, images, and code based on the data it was trained on. It powers tools like ChatGPT, GitHub Copilot, and DALL·E. It’s reactive and input-driven.
Agentic AI, on the other hand, acts. It operates more like a digital agent with goals, context-awareness, and autonomy. It doesn’t just generate responses—it decides what to do next based on an evolving environment.

In short, Generative AI outputs; agentic AI operates.

This shift from content creation to goal-driven execution is pivotal for CISOs evaluating emerging AI tools. IBM explains this distinction in depth here.

Why RSA 2025 Was a Milestone for Agentic AI

RSA Conference 2025 marked a major inflection point in how cybersecurity leaders think about AI. A key highlight from Google Cloud’s blog emphasized how agentic AI systems were already being deployed in live SOC (Security Operations Center) environments.

Notable RSA Highlights:

Palo Alto Networks introduced agentic threat-hunting tools that autonomously seek out anomalies and launch mitigation workflows.
Google’s Chronicle demoed a system that initiated security investigations, gathered data from multiple platforms, and escalated incidents, all without human prompting.
CrowdStrike previewed agents that learn attacker behavior and revise their response tactics dynamically.

Generative AI vs Agentic AI: CISOs’ Strategic Takeaways

The discussions at RSA were filled with comparisons: agentic vs generative AI, proactive vs reactive, independent vs assistive. Here’s what resonated most with security leaders.

1. Autonomy Matters in Real-Time Threat Response

Generative AI can help write incident reports or even suggest patches. But in real-world attacks, delays cost millions. Agentic AI, by contrast, acts in real time. It initiates containment protocols, reroutes traffic, or suspends user access, all autonomously.

For time-sensitive security events, agentic systems outpace generative ones by design.

2. Scalability Through AI Agents

Many CISOs face staffing shortages in their SOCs. With agentic AI, a single intelligent system can scale decision-making across thousands of endpoints: learning, adapting, and executing without human bottlenecks. This was particularly emphasized in a Virtuoso blog on AI in QA and security.

3. Explainability and Governance Challenges

While generative AI has known hallucination issues, agentic AI introduces deeper risks: “Why did the agent do that?” becomes a harder question. CISOs must ensure that agentic systems include explainable AI components, audit trails, and override capabilities.

4. Toolchain Integration

Agentic AI isn’t plug-and-play. It requires integration with your SIEM, identity providers, endpoint tools, and orchestration platforms. Vendors at RSA emphasized open APIs and modular agents as the path forward.

Real-World Examples of Agentic AI in Security

The agentic AI vs generative AI comparison came to life through real-world demos and customer case studies shared at RSA.

Example 1: Financial Sector – Proactive Fraud Defense

A major global bank used agentic AI to autonomously flag suspicious behaviors, cross-reference them with past cases, and freeze accounts pending investigation, all without analyst intervention.

Example 2: Healthcare – HIPAA Compliance Automation

Hospitals deployed agentic systems that monitored EHR access patterns, flagged policy violations, and engaged internal compliance workflows instantly.

Example 3: Cloud Security – Autonomous IAM Policies

Cloud infrastructure companies leveraged agents that dynamically updated IAM (Identity and Access Management) permissions based on real-time behavioral baselines.

These are not theoretical models. These are production systems in Fortune 500 companies.

The Challenges of Agentic AI for CISOs

While the promise is enormous, the differences between generative AI and agentic AI also introduce critical challenges:

Control vs Autonomy: Letting AI take actions comes with risk. Who’s accountable if it locks out a CEO during a false positive?
Bias and Drift: Agentic AI learns and evolves, which means it can also drift from intended policy boundaries if not monitored.
Cost and Complexity: Implementing and tuning these systems takes time, data, and money.

As Harvard Business Review discussed in its December 2024 article, building effective AI governance is now just as important as building the AI itself.

How CISOs Can Prepare Now

RSA made one thing clear: agentic AI is no longer hype, it’s here. So, how should CISOs move forward?

1. Start with Low-Risk, High-Impact Areas

Deploy agentic systems for controlled tasks like log correlation, incident summarization, and alert triage.

2. Establish Guardrails Early

Set clear decision boundaries for AI agents. What they can and cannot do without human intervention should be documented and enforced.

3. Cross-Train Your Teams

Security analysts should learn how to interpret, tune, and monitor agentic AI systems. Consider training programs and simulations.

4. Choose Vendors with Transparency

Prioritize tools that offer explainability, rollback options, and integrations with your existing ecosystem.

Conclusion: A Shift from Assistants to Allies

Agentic AI is not just the next iteration of AI, it’s a new class of digital teammate. It moves security operations from being reactive to being resilient. At the RSA Conference 2025, CISOs didn’t just talk about it—they saw it in action.

As we move forward, understanding what is agentic AI vs generative AI isn’t just academic, it’s essential for building secure, scalable, and autonomous cyber defense strategies.

The future belongs to those who can balance the differences between agentic AI and generative AI, and wield both with purpose.

Connecting with CISOs in the Age of Agentic AI: How Execweb Helps Vendors Cut Through the Noise

With the growing interest in agentic AI, the challenge for vendors isn’t just building the right tools—it’s getting those tools in front of the right decision-makers. If you’re a cybersecurity solution provider looking to connect meaningfully with senior security leaders, Execweb is worth exploring.

Execweb is a trusted platform that facilitates high-value, one-on-one conversations between vetted vendors and CISOs. It’s built to help you build relationships, not just mailing lists.