Fraud Management & Cybercrime
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Ransomware
AI Is Fueling Innovation and Blind Spots. Deep Observability Helps Close the Gap.

From automating content creation to transforming customer experiences, artificial intelligence technologies are driving rapid innovation. Like any disruptive innovation, AI brings both complexity and risk. As AI workloads expand, they generate increasing volumes of data, much of it opaque to security teams. Recent research from the 2025 Hybrid Cloud Security Survey found that one in three organizations has experienced a doubling of network traffic due to generative AI over the past two years. That surge isn’t just pushing the limits of visibility, it’s overwhelming it.
This visibility gap has real consequences. Breaches are rising at an alarming rate, driven by blind spots in data in motion. Many organizations lack insight into lateral east-west traffic and existing tools generally aren’t designed to detect AI workloads or identify shadow AI. The old adage rings truer than ever in the AI era: if you can’t see it, you can’t secure it.
Threat Actors Are Exploiting AI Noise
As AI traffic grows more dynamic and distributed across hybrid cloud environments, attackers are using the noise to mask their movements. Increased attacks targeting large language models and more AI-powered threats are emerging. Many of these threats are hidden within encrypted traffic or shadow AI activity, contributing to a 17% annual rise in data breaches, according to the survey.
More than half of organizations reported a breach, highlighting the heightened exposure many now face as AI adoption accelerates, along with other threats. The reality is that modern threats exploit what security teams cannot see. Shadow AI, encrypted communications and unsanctioned tool access make it increasingly difficult for security and IT leaders to maintain control.
Security Tools Must Evolve
Most existing security architectures weren’t built to monitor the scale, speed and nature of AI activity. As a result, security and IT teams are struggling with inconsistent visibility and growing complexity, exacerbated by tool overlap, especially in hybrid environments spanning on-premises data centers, public clouds and containers. Visibility gaps are a barrier to centralized control, making it harder to manage risk as gen AI deployments grow.
With gen AI spending projected to rise by 76% this year, CISOs must reassess their cybersecurity strategies. The answer isn’t to deploy more tools, but to secure the existing ones with best practices that start with observing AI traffic. With more than 99,000 companies developing AI tools today, the scale of the problem is expanding rapidly. The question now is how security teams can adapt their tool stacks to stay ahead.
Why Deep Observability
Achieving complete visibility into data in motion, including encrypted and lateral traffic, is no longer optional. It is a prerequisite for secure and scalable AI operations. That is where deep observability comes in. By combining network-derived telemetry, such as packets, flows and metadata with metrics, events, logs and traces, or MELT data, deep observability provides the full context needed to detect, investigate and respond to emerging threats.
Solutions, such as Gigamon AI Traffic Intelligence extend this approach by enabling organizations to identify and classify gen AI and LLM traffic, including encrypted flows, without relying on endpoint agents. This helps uncover shadow AI activity and delivers actionable data for governance and control, directly within the Gigamon Deep Observability Pipeline.
Innovation and Security Can Coexist
AI does not have to come at the cost of control. With complete visibility into all data in motion, organizations can support innovation while maintaining strong security. Deep observability helps them to eliminate blind spots, strengthen policy enforcement and boost operational efficiency across complex hybrid cloud environments.
In a landscape where both AI and risk are accelerating, deep observability is no longer a nice-to-have – it is essential. Nine in 10 security and IT leaders agree, stating that deep observability is a foundational element of cloud security today.
Read the full 2025 Hybrid Cloud Security Survey to explore how leaders are navigating the intersection of AI innovation and cybersecurity strategy.
