Over the past year, one thing has become impossible to ignore: the gap between AI adoption and AI security has never been wider. Organizations are embedding AI faster than their security posture can adapt — deploying GenAI tools, building AI-powered applications, and experimenting with autonomous systems, often without the governance, visibility, or controls to match. It is precisely this growing divide that makes the 2026 AI Cybersecurity Summit so critical.

Findings from the forthcoming 2026 Global Threat Landscape Report reinforce why this gap is so consequential. AI enables attackers to act faster by automating reconnaissance and exploiting the same blind spots that appear when adoption outpaces security. As organizations rush to deploy AI, they inadvertently widen the attack surface — creating new entry points through unmanaged tools, unprotected APIs, and ungoverned data flows that adversaries are already learning to exploit.

At the same time, enterprises are rapidly embedding AI across their environments, from employee-facing GenAI tools to production workloads and emerging autonomous systems. The pace of that adoption, however, is creating a compounding challenge: security strategy is being left behind. New layers of risk—model exposure, uncontrolled data movement, API abuse, and prompt-based manipulation—are accumulating inside the infrastructure faster than traditional controls can address them.

And because AI is usually implemented piecemeal across teams, tools, and environments — often without centralized governance or consistent security controls — it introduces fragmentation that widens the gap further. Visibility becomes limited, policy enforcement becomes inconsistent, and defenders lose the ability to fully understand where AI is being used, how it behaves, and where it is introducing risk.

That combination frames the core issue behind the 2026 AI Cybersecurity Summit. The gap between AI adoption and AI security is not a temporary imbalance — it is an accelerating one. Organizations need to rethink how security can keep pace as AI moves through each stage of deployment at scale

AI Adoption Is Reshaping the Attack Surface

When businesses first begin their AI adoption journey, familiar challenges take on new shapes. Employees start using GenAI tools without formal approval, data exposure becomes more difficult to monitor, and governance begins to fragment across teams before any formal policies are established.

When organizations move beyond experimentation and begin building their own AI agents, custom AI applications, and large language models, the complexity deepens significantly. Proprietary models, APIs, and data pipelines introduce new exposure, infrastructure is pushed in unfamiliar directions, and security controls designed for static environments struggle to keep pace with dynamic, AI-driven workloads.

Over time, the attack surface not only grows but also becomes more dynamic, more distributed, and harder to understand.

This progression is a key organizing principle for the summit:

• Using GenAI stage: unmanaged GenAI usage and limited visibility
• Building AI stage: model risk, API exposure, and data movement
• Scaled stage: agentic AI increasing speed, volume, and risk complexity

Rather than treating AI security as a single problem, the AI Cybersecurity Summit focuses on how security priorities shift across these stages and what organizations are doing to adapt in real environments.

What the AI Summit Is Designed to Address

This year’s AI Cybersecurity Summit will focus on how AI is actually being deployed, not on how it is expected to behave in controlled scenarios. Attendees will gain a clearer understanding of how to secure AI as adoption progresses:

Creating a framework for securing AI across stages of adoption. Security decisions made early tend to persist. The summit will explore how priorities shift from GenAI usage to production AI so organizations can avoid locking in long-term risk.

Ensuring greater visibility and governance across AI usage. Critical sessions will examine how teams are gaining insight into AI activity, controlling access, and reducing unintended data exposure without slowing the business.

Developing a layered approach to protecting AI systems. The summit will highlight how security must extend across users, applications, models, APIs, and infrastructure, since fragmented controls do not hold up as environments scale.

Gaining a practical view of AI-powered operations. It will also examine how AI is being applied within security and network operations to help teams manage increasing complexity while maintaining oversight.

A Closer Look at the Agenda

The 2026 AI Cybersecurity Summit brings together Fortinet leaders, customers, and industry perspectives to examine AI security from multiple angles.

It opens with Russ Schafer, EVP at Fortinet, framing how accelerated AI adoption is changing enterprise risk and forcing a reassessment of security strategy. That perspective is extended by Neil MacDonald, Distinguished VP Analyst at Gartner, who will examine how AI is expanding the attack surface and why traditional models are struggling to keep pace.

From there, the summit will move into operational reality, with critical sessions focused on:

• How organizations can gain immediate visibility into GenAI applications and usage
• How companies can control internal use of GenAI tools and apply guardrails when needed
• How AI workloads and LLMs can be secured
• Where agentic AI is beginning to reshape security and network operations

Why This Conversation Is Different

One of the critical issues many organizations face is that AI security is often treated as a future concern or a specialized domain. That framing no longer holds. AI is now part of your core enterprise operations. It touches the infrastructure, applications, and workflows your organization depends on every day, making it harder to delay or reverse security decisions.

What organizations need to confront, and what the summit addresses directly, is a shift in how risk functions:

• It appears earlier, often before governance is in place
• It compounds as AI systems move into production
• It accelerates as automation and agentic AI increase speed

This requires security, infrastructure, and operations to function as a single, coordinated system rather than as separate layers.

Who Should Attend

The AI Cybersecurity Summit is designed for leaders and practitioners responsible for securing environments where AI is already in use or rapidly becoming part of core operations. This includes:

• Security and IT leaders shaping strategy and risk posture
• Architects and engineers responsible for implementation and control
• Teams managing infrastructure, applications, and operational workflows

If AI is influencing how your environment runs today, the discussions at the summit are directly relevant to the decisions you are already making.

AI is not waiting for security models to catch up. It has already begun changing how network and security environments operate. And the gap between adoption and security is where risk is accumulating. The AI Cybersecurity Summit will help you close that gap by focusing on how security must evolve as AI becomes part of your operational infrastructure.

Register now to secure your spot.