Anomali Named SC Awards Finalist x2: What the Recognition Reflects About Where Security Operations Is Headed

The conversation about AI in security has a mythology problem. Walk into most boardrooms today and the discussion centers on tools, copilots, and models. Which AI should we buy? How many alerts will it reduce? When will it pay for itself?

Those are the wrong questions to start with — and the gap between where those conversations begin and where security operations actually need to go is where most AI projects fail. The failure rate on enterprise AI initiatives is running at roughly 95 percent. AI isn't a technology shift. It is business model disruption.

What we hear, traversing the globe and working alongside some of the world's largest enterprises in both the public and private sector, is that the organizations making real progress have learned to start somewhere different. They start at the top of the lighthouse. They ask what the business needs to accomplish, work down to the data strategy that enables it, and only then do they turn to technology. That sequence — business strategy first, data strategy second, technology third — is what separates organizations that are getting outcomes from AI from the ones accumulating proofs of concept that prove nothing.

It is against that backdrop that we are proud to share that Anomali has been named a finalist in the 2026 SC Awards in two categories: Best Threat Intelligence Technology and Best AI/ML Data Analytics Security Solution.

What the SC Awards Actually Represent for SecOps  Impact

The SC Awards are now in their 29th year. Entries are evaluated across 33 specialty categories by a panel of cybersecurity practitioners, industry leaders, and members of the CyberRisk Alliance CISO community — professionals representing healthcare, financial services, education, and technology. These are not marketing judges. They are people who operate inside the threat landscape every day and understand what it takes to deliver real-world security impact.

Being recognized in two categories by that panel matters precisely because of who is doing the recognizing. As CyberRisk Alliance Chief Content Officer Kelley Damore noted, being named a finalist is a mark of credibility and trust — validation from peers who understand the realities practitioners face.

We would add one thing to that: any recognition like this belongs first to the customers who were bold enough to co-innovate with us. They were willing to challenge the legacy architecture, to move past the alphabet soup of point solutions, and to build toward something fundamentally different. They are the ones who proved it works.

Why These Two Categories Are Inseparable: The Architecture Behind AI-Driven Threat Intelligence and Security Analytics

The SC Awards recognized Anomali in Best Threat Intelligence Technology and Best AI/ML Data Analytics Security Solution. That pairing is not accidental. It reflects the architectural conviction that has driven platform development since we set out to replace some of the largest enterprise SIEMs in the world.

Most vendors treat data and intelligence as separate problems. You buy a SIEM to collect data. You buy a threat intelligence platform to add context. You build integrations and hope the two systems talk to each other fast enough to be useful. The result is what most SOC teams live with every day — enrichment workflows that slow investigation, alert queues that grow faster than analysts can clear them, and AI tools that produce output practitioners still have to manually verify.

The reason that keeps happening is not the AI. It is the data underneath it.

Putting AI next to bad data is like hiring a genius who doesn't speak your language. All the capability in the world, and none of the results. Data that is siloed, unindexed, or fragmented does not become AI-ready just because you deploy a model on top of it. The missing ingredient — what most failed AI projects never address — is the ontology and taxonomy that gives AI a blueprint to understand data, not just access to it.

Intelligence must be embedded at ingestion, not bolted on later. Every event needs to be enriched with contextual intelligence in real time. That is what produces high-fidelity detections instead of raw alerts. That is what allows agentic AI to reason across data and drive decisions rather than generate more work for analysts.

The sequence matters and it cannot be inverted: visibility first, then context, then outcomes. Number one is maximizing visibility of data. Intelligence is variable number two. AI-driven outcomes only emerge reliably from that foundation — not before it.

The Threat Landscape Has Changed the Terms of the Problem: Why Modern Cyber Threats Require an Agentic SOC Architecture

There is another dimension to why architecture matters now that did not apply with the same urgency five years ago. The threat landscape has moved to a level of sophistication, precision, and speed that practitioners have not encountered before.

This is an infinite chess match. The difference today is that adversaries have access to the same AI capabilities that defenders do — and their job got easier with AI. Machine-driven, AI-precision attacks operate at a pace no human analyst can match manually. Rogue nation-state actors and sophisticated criminal organizations can now scale their campaigns in ways that make the alert-centric, reactive SOC model structurally inadequate.

Spending more time chasing the past is not the answer. The organizations that will be ahead of this are the ones investing now in predicting where the threat is going, not just detecting where it has been.

That is what an agentic SOC is designed to do. Not more dashboards. Not another layer of alerts. Intelligent, autonomous agents operating with governance and auditability built in — a fleet of agents, not one or two — moving the human role from reactive triage to cognitive oversight at a level the old model never made possible.

Securing from AI, securing the AI, and securing with AI are three distinct problems that all require the same foundation: unified data, fidelity of context, and an intelligent architecture that can keep pace with the threat.

The Business Model Disruption Nobody Is Talking About Enough

Strip away the security-specific language for a moment and the underlying dynamic becomes clearer. AI is not a technology shift. It is the biggest business model disruption humanity has encountered, and it’s more horizontal in its reach across every function of the enterprise than anything before it.

The same pattern played out when robots entered the factory floor. It played out in biomedical, where surgical equipment is now far more effective and robotic than it was a decade ago. It played out in the cloud transition, which had nothing to do with technology and everything to do with a disruption to how businesses operate and create value. Each time, the instinct was to treat it as incremental — to add the new capability to the old architecture and call it progress. Each time, that approach eventually gave way to something more disruptive.

An incremental innovation will not solve a disruption. The organizations recognizing that now — and restructuring their data strategy, their talent, and their architecture accordingly — are the ones that will be best positioned when the dust settles.

AI is becoming a service layer economy. The value is no longer in workflow automation. It is in outcome ownership — AI executing the work after the click, shifting the SaaS proposition from selling software to delivering results. For security operations, that means moving from an alert engine to a platform that predicts, prevents, and responds autonomously within governed boundaries.

What Practitioners Should Take From This Moment Before Deploying AI in the SOC

Recognition from the SC Awards judges — people who understand what real-world security impact requires — is meaningful to us. But what it reflects more broadly is a market that is reaching a decision point.

The question most security leaders should be sitting with is not which AI tool to deploy next. It is whether the data foundation underneath their operations is actually capable of supporting the outcomes they need. Whether their current architecture is built to evolve or built to be replaced. Whether they are investing in an enterprise that sees its CISO and CIO as strategic drivers of a data and AI roadmap or as operators of a set of tools.

Be a student of this transition, not a professor of what has already been built. This is evolutionary, and we are all learning. Anybody who tells you they have it figured out is not telling the truth.

What is true is that the organizations that approach this with curiosity, with a triangulated strategy across business objectives, data architecture, and technology enablement, and with the discipline to govern what they build — those are the organizations that will define what the next era of security operations looks like.

The 2026 SC Awards finalists will be featured throughout the month on SC Media's website at www.scworld.com/sc-awards.

For a deeper look at how Anomali's Agentic SOC Platform is built to address these challenges, explore the full platform overview or watch our recent Agentic SOC Webinar.

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