The Threat Intelligence Market Is Changing: Five Shifts Redefining How Intelligence Creates Value

For more than a decade, the threat intelligence market has been defined by accumulation: more feeds, more indicators, more reports, more dashboards. Success was often measured in volume, meaning how much intelligence a team could ingest, publish, or distribute.

That model no longer works.

The threat landscape has accelerated, data volumes have exploded, and security teams are operating under unprecedented pressure. In fact, modern SOCs receive an average of 4,484 alerts per day, and analysts spend nearly three hours daily just triaging them, with 83% of alerts later deemed false positives.  

At the same time, artificial intelligence has raised expectations for speed, scale, and consistency in security decision-making. Together, these forces are driving a fundamental transformation in how threat intelligence is produced, delivered, and consumed.

As Chris Vincent, Chief Commercial Officer at Anomali, framed it during a recent industry discussion:

“What worked even a few years ago, it no longer scales.”

The threat intelligence market isn’t disappearing, but it is being redefined. Below are the five most important ways it is changing, and what those shifts mean for security teams moving forward.

1. From Feeds and Reports to Decisions and Outcomes

Historically, threat intelligence has been descriptive. Platforms focused on collecting indicators, publishing reports, and delivering situational awareness. The assumption was that analysts downstream would interpret that information and decide what to do next.

“Threat intelligence is considered a separate function that produces reports and indicators or alerts that someone else will operationalize later,” said George Moser, Chief Growth Officer at Anomali and a former Fortune 1000 security leader. “That doesn’t work today.”

Threats now evolve in minutes, not weeks. Automated threat scanning activity has jumped to as high as 36,000 scans per second globally, with cybercriminals exploiting speed at scale. Static intelligence artifacts like PDFs, weekly summaries, bulk IOC lists are often obsolete by the time they reach the SOC. The value of intelligence is no longer measured by how much information it contains, but by how quickly it drives a defensible action.

This shift is redefining the market. Intelligence is expected to answer operational questions in real time:

• Is this activity real or noise?
• Is it relevant to my environment?
• What should we do next?

As Moser put it, intelligence must evolve “from a publishing function to a real-time decision engine.” The market is moving decisively toward solutions platforms that prioritize outcomes over output.

2. From Standalone TIPs to Intelligence Embedded in Operations

Another major change is structural: threat intelligence is no longer expected to live in a standalone system.

For years, cyber threat intelligence (CTI) teams operated upstream from the SOC. They produced high-quality analysis, but that intelligence often failed to translate cleanly into detections, prioritization, or response. The friction between intelligence production and operational execution made impact limited.

“Intelligence that isn’t embedded in operations creates friction,” Moser explained. “Many CTI teams still operate upstream from the SOC. They produce good intel, but it doesn’t translate directly into detections and response actions.”

Today’s security programs expect intelligence to be native to workflows. It should flow automatically into analytics, alerts, investigations, and automation, not arrive as a separate artifact that requires manual interpretation.

This expectation is reshaping the market. Legacy TIPs designed as intelligence repositories are giving way to platforms that embed intelligence directly into security operations. Intelligence is no longer an external input; it is a core layer of the SOC itself.

3. From Human-Only Analysis to Agentic, AI-Driven Execution

Perhaps the most profound shift in the threat intelligence market is the move beyond human-only workflows.

The scale of modern security data has outpaced human capacity. Analysts are overwhelmed, teams are understaffed, and adversaries increasingly use automation and AI to accelerate their attacks.

“Human-only analysis just doesn’t scale,” Moser noted. “What’s required today is intelligence embedded directly in decisions, investigations, and response.”

AI is changing what intelligence platforms are expected to deliver. Instead of simply summarizing data, intelligence systems are increasingly responsible for reasoning across signals, prioritizing threats, and recommending — or even executing — next steps.

Christian Karam, a technology investor and advisor, described this as a shift from descriptive intelligence to executable intelligence.

“We’re moving into a world where intelligence has to be a lot more executable,” he said. “The burden is on the industry to package this as a decision-making layer.”

This marks the rise of agentic intelligence: AI that doesn’t just advise, but acts. In this new model, intelligence platforms generate decisions, not just insights — fundamentally changing how value is delivered.

4. From IoC-Centric Intelligence to Behavior and Campaign Context

Another driver of change is the declining effectiveness of static indicators.

IoCs age quickly. Infrastructure rotates. Adversaries deliberately evade signature-based detection. Intelligence programs built primarily around indicator feeds struggle to keep pace with modern campaigns.

The market is responding by shifting toward behavior-based and campaign-level intelligence. Instead of asking, “Have I seen this IP before?”, security teams are asking:

• What behaviors does this activity represent?
• How does it map to known tactics and techniques?
• Is this part of a broader campaign?

This shift enables earlier detection and better prioritization, even when individual indicators are novel or short-lived. Intelligence is increasingly focused on intent, patterns, and relationships instead of artifacts only.

This change is redefining what “high-fidelity intelligence” actually means in practice.

5. From Tool Sprawl to Intelligence-Native Security Platforms

Finally, threat intelligence is being reshaped by consolidation.

Most SOCs today manage dozens of disconnected tools: SIEMs, TIPs, SOAR platforms, analytics engines, data lakes, and AI point solutions. This sprawl drains time, obscures context, and increases operational friction.

Organizations are responding by consolidating around platforms that unify data, intelligence, analytics, and automation.

“The industry is going to have to reinvent itself,” Karam observed. “Platforms need to capture context, create feedback loops, and be interoperable with existing investments.”

In this environment, threat intelligence is no longer a standalone category. It has become an architectural principle; intelligence-native platforms where context, reasoning, and automation are built in from the start.

This consolidation reflects a broader truth: intelligence creates the most value when it is inseparable from operations.

What This Means for the Future of Threat Intelligence

Taken together, these five shifts point to a clear conclusion: the threat intelligence function is fundamentally changing.  

Intelligence is no longer judged by volume, breadth of feeds, or the sophistication of reports. It is judged by:

• Speed to decision
• Consistency of outcomes
• Ability to scale withoutadding headcount
• Integration into real operational workflows

Security teams that continue to rely on static, standalone intelligence models will struggle to keep pace. Those that embrace intelligence as an embedded, agentic decision layer will be better positioned to detect threats earlier, respond faster, and operate more efficiently in an increasingly hostile environment.

The threat intelligence market is changing, but not because intelligence matters less. It now matters more than ever. Find out more about next the threat intelligence trends you need to know in our expert-led webinar.