Agentic AI—the next generation of reasoning models capable of autonomous action—is reshaping cybersecurity at unprecedented speed. It is already embedded in malware 

detection and SOC operations, driving massive efficiency gains. Yet, it also introduces new risks across the attack surface, from AI-powered phishing and adversarial manipulation to supply chain vulnerabilities and machine identity sprawl. The impact on enterprise security will depend less on technology and more on organizational adaptability. 

The Double-Edged Nature of Agentic AI 

AI systems are advancing at breakneck speed, and their influence on cybersecurity is undeniable. Agentic AI—models that can reason, plan, and act autonomously—is the next major inflection point. 

Companies like OpenAI, Google, and Anthropic have developed “reasoning models” that can analyze context, decompose problems, and execute actions. Combined with emerging frameworks like the Model Context Protocol (MCP), these systems can directly interface with business tools such as ERPs, CRMs, and data lakes. The result is autonomous agents that execute multi-step processes with minimal human intervention. 

McKinsey & Co. describes agentic AI as “among the fastest growing of this year’s trends,” with potential to transform productivity and decision-making. But with transformation comes exposure. As enterprises integrate these agents deeper into their digital core, the threat landscape is evolving just as fast. 

How Agentic AI Expands the Threat Landscape 

Agentic AI is both accelerating attacks and creating new vulnerabilities. 

1. Accelerating Attacks: 

Cybercriminals are already leveraging generative and reasoning models to scale and automate phishing, reconnaissance, and ransomware operations. Instead of one-off exploits, attackers now deploy adaptive, learning agents that continuously probe systems, find weaknesses, and evolve strategies in real time. 

A recent Anthropic Threat Intelligence report illustrates this shift. Criminals used its agentic software platform, Claude Code, to build an autonomous data-theft system that targeted 17 organizations—including hospitals and government entities.

The AI harvested sensitive data, determined ransom amounts, and prioritized exfiltration paths all without human oversight. Anthropic later disrupted the activity, but the episode underscores how sophisticated these agents have become. 

 2. Creating New Vulnerabilities: 

As enterprises embed agentic AI, they face three emerging categories of risk: 

• Supply Chain Exposure: Agentic systems integrate across multiple APIs and plug-ins, expanding dependency surfaces. A compromised agent or model endpoint can cascade across connected environments. 

• Runtime and Adversarial Attacks: Agents are dynamic, reasoning entities—susceptible to prompt injection, model poisoning, or data manipulation. Attackers can now exploit not just code, but decision logic itself. 

• Machine Identity and Credential Sprawl: Every AI agent requires its own credentials and permissions. At scale, this explosion of machine identities becomes a major governance and attack management challenge. 

Beyond external threats, there’s also an internal blind spot—shadow AI. KPMG research found that 57% of employees conceal their AI usage, often connecting unvetted tools into core workflows. Incidents like Replit’s autonomous agent deleting a production database highlight how governance gaps can create operational and reputational risk. 

In short, as agentic AI evolves, so too will the nature and velocity of cyber threats. 

How Agentic AI can Strengthen Security 

Despite its risks, agentic AI is also transforming defense capabilities—and fast. 

1. Core to Modern Detection and Response: 

Agentic AI is already embedded in next-generation security platforms. Microsoft, 

CrowdStrike, Palo Alto Networks, and others use AI reasoning models to detect anomalous behavior, correlate events, and predict threats before execution. These systems analyze vast telemetry data and identify emerging attack patterns faster than human teams ever could. 

2. Reinventing SOC Operations: 

Security Operations Centers (SOCs) are under immense strain. A Lightcast study shows a shortage of more than 225,000 cybersecurity professionals in the U.S., while 66% of SOC analysts report being overwhelmed by alert volumes (SANS 2024 SOC Survey). 

Agentic AI offers relief. It can: 

• Triage alerts and reduce false positives in real time. 

• Simulate likely attack paths before incidents occur. 

• Correlate activity across endpoints, networks, and identities. 

• Prioritize responses based on threat criticality and business impact. 

By automating lower-value, repetitive tasks, AI agents free human analysts to focus on containment, recovery, and strategic threat hunting. The result is not replacement—but augmentation. SOCs become faster, smarter, and more proactive. 

Building Security for the Age of Agents 

The promise of agentic AI cannot be separated from the need for resilience. To harness its benefits securely, enterprises must evolve their frameworks around four imperatives: 

1. Visibility and Control: Maintain clear observability over AI operations, especially autonomous agents acting on critical systems. 
2. Rollback and Containment: Build mechanisms for reversibility when AI agents make errors or exceed intended scope. 
3. Resilient Data Protection: Re-architect backup, recovery, and resilience strategies to include AI-driven workloads and decision systems. 
4. Governance and Upskilling: Establish clear accountability for AI actions, align with frameworks (NIST, ISO, MITRE, OWASP), and train employees to work alongside agents effectively. 

AI resilience must be proactive, not a bolt-on. As AI becomes embedded across infrastructure, security must evolve in lockstep—integrating governance, testing, and recovery as first principles. 

The Balancing Act Ahead 

Agentic AI will both amplify and defend enterprise security. It will help contain breaches faster, but it will also generate new failure modes and ethical risks. Whether it becomes an accelerant for protection or exposure will depend on how organizations adapt. 

The real gate to progress is not technical—it’s organizational. Companies that embed AI governance, invest in resilience, and upskill their workforce will turn Agentic AI into a security multiplier. Those who treat it as plug-and-play automation risk compounding their vulnerabilities. 

As with every technological revolution, the winners won’t be those who resist change—but those who master it.