Why Agentic AI Breaks Traditional Security and What Comes Next
A cybersecurity leader's guide to autonomous AI, emerging risk, and data-centric protection.
Watch Skyhigh Security and guest speaker Jeff Pollard, Forrester's VP of CISO Research, discuss what makes agentic AI fundamentally different, how these systems work, and what organizations need to do now to protect sensitive data, enforce governance, and reduce risk in highly regulated environments.
- What agentic AI actually is, and why autonomy, tool use, and credentialed access create a new class of enterprise risk
- Where the attack surface expands — users, agents, apps, APIs, browser activity, workflows, and the data underneath them
- Why sanctioned and shadow AI adoption both demand stronger governance, visibility, and real-time enforcement
- What a data-centric Zero Trust architecture for AI looks like when protection sits as close to the data as possible
Agentic AI changes everything
Agentic AI introduces new security challenges across prompts, outputs, identities, APIs, browsers, SaaS apps, private applications, and machine-driven workflows. At the same time, threat actors are using AI to accelerate social engineering, vulnerability discovery, and attack execution — compressing response windows for teams that were already stretched thin.
The difference is autonomy. A chat interface returns an answer and waits. An agent interprets intent, chains tool calls, and acts across systems using credentials of its own. That single shift moves the control point off the network and onto the data, the identity, and the session — which is exactly where most existing architectures have the least visibility.
Autonomy
Outputs stop being answers and start being triggers. The agent interprets intent and executes across tools, APIs, and enterprise systems.
Credentialed Access
Agents carry identities, tokens, and standing access, which widens the blast radius of any single compromise well beyond one user.
Data-Centric Control
Protection has to sit as close to the sensitive data as possible, because the perimeter no longer bounds the workflow.
What this executive-level session covers
How agentic AI actually works — and why it changes the enterprise risk model rather than just extending it.
Where traditional security controls fall short once systems can act on their own.
How AI is accelerating attacker speed and sophistication, and what that compresses on the defensive side.
Why identity, data access, browser activity, and APIs have become the critical control points.
What a data-centric, Zero Trust architecture for AI security should include.
How regulated organizations can strengthen governance without adding unnecessary complexity:
Learn from a leading security mind
제프는 포레스터에서 CISO 역할에 대한 연구를 주도하며, 보안 전략, 예산, 성과 지표, 사업 타당성 분석 및 이사회 발표를 전문으로 다룹니다. 또한 그의 연구 분야에는 관리형 보안 서비스, 전문 보안 서비스, 그리고 미래 지향적인 보안 혁신도 포함됩니다.
Ready to secure what's next?
Agentic AI is already reshaping how enterprises work, automate, and access data. Watch the session and see what the architecture to protect it looks like.
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