Webinar Description
Key Takeaways
- Agentic AI introduces autonomous systems that operate independently, creating security challenges that traditional controls cannot address
- The enterprise attack surface now extends across users, AI agents, APIs, browsers and SaaS applications
- Data-centric Zero Trust models are emerging as a foundational approach to securing AI-driven environments
- Designed for CISOs, security architects, compliance executives and leaders in regulated industries
- Features Forrester VP of CISO Research Jeff Pollard alongside Skyhigh Security
Introduction
The rapid adoption of agentic AI across enterprise environments is forcing security leaders to reconsider fundamental assumptions about how organisations protect sensitive data and manage risk. Unlike conventional large language model interfaces that respond to user prompts, agentic AI systems operate autonomously, making decisions and taking actions without continuous human oversight. This shift introduces security considerations that existing frameworks were never designed to address, particularly in regulated industries where data governance and compliance requirements are stringent.
A forthcoming webinar hosted by Skyhigh Security brings together industry expertise to examine these challenges. Featuring Jeff Pollard, VP of CISO Research at Forrester, the session explores why agentic AI fundamentally changes the enterprise risk landscape and what security architectures must evolve to meet these new demands.
About This Event
Titled “Why Agentic AI Breaks Traditional Security and What Comes Next,” this virtual webinar provides an executive-level discussion on the security implications of autonomous AI systems. The format combines expert presentation with interactive Q&A, allowing participants to engage directly with the speakers on specific organisational challenges.
The session is structured around practical guidance rather than theoretical discussion, addressing how organisations can protect sensitive data, enforce governance policies, and reduce overall risk exposure. Particular attention is given to the needs of regulated environments where compliance obligations add complexity to security decisions.
Understanding the Agentic AI Security Challenge
Traditional security controls were designed around predictable patterns of human behaviour and well-defined system interactions. Users authenticate, access resources within defined permissions, and generate activity logs that security teams can monitor and analyse. Agentic AI disrupts this model by introducing autonomous actors that can initiate actions, access data, and interact with systems at machine speed without direct human instruction.
This autonomy creates several distinct security challenges. Agents may access sensitive data across multiple systems to complete tasks, potentially exposing information in ways that traditional data loss prevention tools cannot anticipate. They may interact with external services, APIs, and SaaS applications, expanding the attack surface beyond conventional network boundaries. Perhaps most significantly, the speed and scale at which agents operate can outpace human oversight, making real-time governance essential rather than optional.
The webinar examines why existing security architectures struggle with these dynamics. Controls designed to monitor and restrict human users often lack visibility into agent behaviour, while perimeter-based defences become less relevant when autonomous systems routinely cross traditional security boundaries to perform legitimate functions.
Data-Centric Zero Trust as a Foundation
Central to the discussion is the concept of data-centric Zero Trust, an architectural approach that shifts security focus from network perimeters to the data itself. Rather than assuming that users or systems within a network boundary can be trusted, Zero Trust requires continuous verification of every access request regardless of origin.
When applied to agentic AI environments, this model offers several advantages. By treating AI agents with the same scrutiny as any other actor, organisations can enforce consistent governance policies across human and machine interactions. Data classification and protection travel with the information rather than depending on where it resides, providing visibility even when agents move data between systems or services.
The session explores how organisations can implement data-centric Zero Trust without adding unsustainable complexity to their security operations. This includes discussion of how technologies such as Security Service Edge, Cloud Access Security Broker, Secure Web Gateway, and Private Access capabilities can work together to provide comprehensive coverage across the expanded attack surface that agentic AI creates.
Governance Challenges for Sanctioned and Unsanctioned AI
Enterprise AI adoption rarely follows a single, controlled path. While organisations may deploy sanctioned AI tools with appropriate security controls, employees and business units often adopt additional AI capabilities independently. This shadow AI phenomenon complicates governance efforts, as security teams cannot protect systems they do not know exist.
The webinar addresses strategies for gaining visibility into both sanctioned and unsanctioned AI usage across the enterprise. Effective governance requires understanding not only which AI tools are in use but also what data they access, what actions they can take, and how their behaviour aligns with organisational policies and regulatory requirements.
For organisations in regulated industries, these governance challenges carry additional weight. Financial services, healthcare, and other sectors face specific obligations around data handling, audit trails, and accountability that become more difficult to satisfy when autonomous systems are involved in data processing. The discussion examines how security architectures can maintain compliance and observability even as AI capabilities proliferate.
Simplifying Security Architecture
A recurring theme throughout the session is the tension between comprehensive security coverage and operational complexity. Adding new controls for each emerging threat vector can create sprawling security environments that are difficult to manage, expensive to maintain, and prone to gaps where different tools fail to integrate effectively.
The webinar explores approaches to simplifying security architecture while improving rather than sacrificing protection. This includes examination of how converged platforms that combine multiple security functions can reduce complexity while providing consistent policy enforcement across users, agents, APIs, browsers, and SaaS applications. Technologies referenced include Cloud-Native Application Protection Platforms, Data Loss Prevention, and Secure Browser Controls, each addressing specific aspects of the modern attack surface.
The MITRE ATT&CK framework provides context for understanding how threats manifest and how defensive capabilities map to attacker techniques, helping organisations prioritise investments based on realistic threat models rather than vendor marketing.
Who Should Attend
The webinar is designed for senior cybersecurity and technology leaders responsible for enterprise security strategy and architecture. This includes Chief Information Security Officers evaluating how AI adoption affects their risk posture, security architects designing controls for AI-enabled environments, and data security leaders concerned with protecting sensitive information as it flows through autonomous systems.
Cloud security leaders will find relevant discussion of how agentic AI interacts with cloud services and SaaS applications, while risk and compliance executives can gain insight into governance frameworks suitable for autonomous AI. Leaders in regulated industries facing specific compliance obligations around AI usage and data handling will find particular value in the session’s treatment of observability and audit requirements.
Industry Context
The emergence of agentic AI represents a significant inflection point for enterprise security. While organisations have spent years adapting to cloud computing, mobile workforces, and SaaS proliferation, autonomous AI introduces a fundamentally different challenge: systems that act rather than merely respond, that make decisions rather than simply process instructions.
Security vendors and analysts are actively developing frameworks and technologies to address these challenges, but the field remains nascent. Organisations adopting agentic AI today are often navigating without established best practices, making expert guidance particularly valuable. The combination of Forrester’s research perspective and Skyhigh Security’s technical expertise offers attendees insight into both the strategic landscape and practical implementation considerations.
As AI capabilities continue to advance and enterprise adoption accelerates, the security decisions organisations make now will shape their risk exposure for years to come. Understanding the limitations of traditional controls and the requirements for modern AI security architecture has become essential knowledge for security leaders across industries.