From AI Assistants to AI Agents: The Next “Big Thing” is Here!

There is no denying the fact that in recent years artificial intelligence has emerged as a critical ally in our cyber defense strategies. 

Security Operations Centers (SOCs) are actively leveraging AI to process vast amounts of threat data, identify patterns invisible to human analysts, and streamline incident response workflows that once required countless manual hours. AI assistants serve as invaluable partners for cybersecurity teams by enhancing threat research capabilities, processing intelligence at machine speed, and reducing the cognitive burden of security operations. 

But in a world where threats evolve by the minute and attack surfaces expand exponentially, we must ask ourselves: What's next in this AI security evolution?

The Limitations of AI Assistants

Today's AI assistants excel at retrieving and synthesizing security data, identifying patterns, and presenting insights. However, they remain limited by a human-in-the-loop model, requiring constant prompting and analyst intervention. While they ease cognitive load, they are still evolving toward full autonomy—leaving analysts to interpret findings, decide actions, and execute responses manually.

This creates bottlenecks and delays in threat management and incident response—where speed is critical. In essence, AI is evolving rapidly, and security teams are beginning to realize its full potential in transforming cybersecurity from reactive to proactive. 

AI Agents: Moving A Step Forward in Advanced Cyber Defense

AI agents are the next “Big Thing” in security automation. Gaining significant attention, they were featured in Forrester’s Top 10 Emerging Technologies for 2024.  Unlike assistants, they don’t just respond to queries—they take action. 

Integrated with security systems, they automate tasks and orchestrate workflows across the threat lifecycle. What sets them apart is their ability to close the gap between insight and action. Instead of merely alerting analysts, AI agents analyze threats, make decisions, and trigger coordinated responses, streamlining security operations and enhancing efficiency. They operate beyond predefined inputs and fixed outputs, devise strategies, utilize tools, and adaptively generate outcomes with a certain degree of autonomy.

While intelligent AI agents are still in their early stages, they are evolving rapidly. However, with the various branches and applications of artificial intelligence—whether AI, AI-driven assistants, or AI agents—the distinctions can sometimes blur. To clarify their roles in cybersecurity, let’s examine how different approaches—manual, AI assistant-based, and AI agent-driven—manage the threat lifecycle of an Advanced Persistent Threat (APT) targeting critical infrastructure.

The Legacy Manual Approach follows a simple Detection → Analysis → Response model, relying heavily on human intervention at every stage.

AI assistants enhance analysis, streamline investigations, provide recommended actions to queries via NLP, facilitate execution, and improve decision-making. However, they still require manual intervention to a large extent, as analysts must repeatedly input queries to trigger actions.

The real transformation comes with Agent-Driven Orchestrated Response, where intelligence not only informs action but also drives automated, near-real-time responses, making security operations faster, more efficient, and truly proactive.

Through seamless orchestration, AI agents integrate with the entire security ecosystem—interacting with detection, intelligence, threat hunting, SOC, incident response, IT, and other tools for data gathering, analysis, and actioning. Furthermore, fully autonomous AI agents can dynamically generate playbooks, enabling end-to-end automated security operations that achieve desired outcomes at machine speed.

Why AI Agents Should Matter for the Cybersecurity Teams

For security leaders and practitioners, AI agents address some of the most pressing challenges:

1. Enhance analyst productivity by automating routine investigation and response tasks, freeing skilled professionals to focus on strategic initiatives, advanced threat hunting, and security engineering—areas where human expertise is essential. A recent Gartner report predicts that by 2028, 33% of enterprise software applications will incorporate agentic AI, up from less than 1% in 2024. This shift will enable 15% of day-to-day work
2. Reduce manual workloads to tackle talent shortages- Organizations that lack the resources to staff 24/7 security operations can leverage AI agents to ensure continuous monitoring and rapid response without increasing headcount.
3. Accelerate and refine threat mitigation. In cybersecurity, every second counts—reducing response times from hours to seconds can mean the difference between a contained incident and a widespread breach.

To prepare for this shift, organizations should start by automating high-volume, repeatable security workflows, gradually introducing AI-driven processes. Beginning with contained use cases allows teams to build confidence in AI-driven automation before scaling to more complex scenarios. However, the full potential of AI agents depends on expanding integration capabilities and continuous learning, ensuring they evolve alongside emerging threats.

Looking Ahead

The shift from AI assistants to AI agents marks the most profound transformation in enterprise security since the rise of SOCs. Organizations that embrace this evolution will gain unmatched advantages in threat detection speed, response precision, and operational efficiency. The question isn’t whether security operations will become agent-driven, but how quickly organizations can adapt and leverage them to drive outcomes.

In upcoming articles, I’ll explore implementation strategies for agentic security operations, highlighting high-impact use cases and practical approaches for integrating autonomous capabilities. 

Stay tuned for the next installment in this “AI Agents for Security Operations” series!