Risks, Vulnerabilities And Response: Threat Intelligence is Quietly Becoming The Connected Layer in Security

The market has shifted but most security teams have not.

As per Gartner®, by 2028, more than 50% of organizations adopting cyberthreat intelligence (CTI) technologies will prioritize platforms that natively operationalize intelligence through automated detection rule generation, enforcement actions and takedown workflows over those that primarily deliver enrichment and reporting.

Cyberthreat intelligence (CTI) has moved past its enrichment-and-reporting roots. It still needs to be accurate and timely. But too often it arrives, gets logged, and then sits there  perfectly correct and completely unused, while the analyst who should act on it is three incidents deep in something else.

That’s the quiet failure mode. Not missing intelligence, but unused intelligence.

The market has spent a decade getting adept in collecting: feeds are richer, coverage is wider, and the volume of indicators flowing into the average operations centre has never been higher. What hasn’t kept pace is the distance between knowing something and doing something about it. For most programmes, that distance is still measured in manual effort.

Leaders operationalise intelligence. Everyone else just reports it.

Source: Gartner, Magic Quadrant for Cyberthreat Intelligence Technologies, Jonathan Nunez, Carlos De Sola Caraballo, 4 May 2026. GARTNER and MAGIC QUADRANT are registered trademarks of Gartner, Inc. and/or its affiliates.

The relevance question

“We’re preparing for threats we don’t even face.”

It’s the objection that surfaces whenever the threat intelligence budget is on the table. And most of the time, the person saying it is right about their current intelligence.

A generic feed reports every threat to everyone. It buries the handful aimed at your sector under thousands that will never touch you. Spend enough months wading through that, and “we don’t face these threats” becomes the obvious conclusion.

But the problem isn’t intelligence. It’s untargeted intelligence. 

A bank and a telco are hunted by different actors, through different infrastructure, for different reasons. Intelligence tuned to your sector, your stack, and the adversaries actually pointed at you is the opposite of noise — it’s the filter that tells you which threats are real for you and which are someone else’s problem. Relevance is the first test. But it’s only the first,  because even intelligence aimed at exactly the right threats fails the moment it stands alone.

The gap

The dashboard is where intelligence is made visible, not used.

The feeds are running. The reports are thorough. The dashboard is populated. Leadership sees activity, and activity reads as capability. Then an attack lands that the programme had every signal to anticipate, and nobody connects the alert to the action until after the fact.              

The gap isn’t analytical. It’s operational. 

What separates intelligence that changes outcomes from intelligence that does not

The source

Not all “intelligence” is intelligence, and most teams can’t tell which is which.

A great deal of what gets sold as threat intelligence is open-source data with a logo on it. When a feed draws from the same public sources as a dozen other vendors, the underlying data is identical. What you’re paying for is the formatting.

The intelligence that actually moves outcomes is the intelligence that’s hard to get, and the depth runs much further down than most programmes ever reach: persistent, analyst-managed access inside closed criminal forums.

Incident-response findings that validate what’s real. Proprietary fraud telemetry. And at the bottom, infrastructure-level signals like BGP monitoring that almost no one collects at all.

The reason depth matters is attribution. Linking an indicator you see today to a campaign you saw eighteen months ago, confidently, not speculatively, is only possible if you were watching eighteen months ago.

This is the part of the market that’s genuinely difficult to replicate, and it’s worth being honest about why. Twenty-one years of proprietary telemetry and more than 1,500 joint investigations alongside agencies like INTERPOL, Europol, and AFRIPOL isn’t a marketing line. It’s a head start that compounds. Every investigation feeds the next one. The advantage isn’t data volume, it’s continuity.

The convergence

Your fraud team and your security team are investigating the same attacker. They just don’t know it.

This is the blind spot almost nobody has named out loud, and it’s the one I’d fix first.In most organisations, fraud and cybersecurity are two functions with two stacks, two escalation paths, and two sets of data that never touch. The fraud team watches transactions. The security team watches infrastructure. Both are competent. Neither sees the whole picture.

That asymmetry is the liability. And it’s getting worse, because the ecosystems themselves are converging; ransomware groups and fraud operators increasingly share infrastructure, tooling, and monetisation paths.

When the criminal economy stops distinguishing between cyber and fraud, a defence that still does is structurally a step behind. The fix isn’t another integration bolted on after the fact. It’s fusing fraud intelligence and threat intelligence at the data layer, so the correlation happens in one place instead of in a meeting three weeks later.

The adversary doesn’t separate cyber from fraud. At some point, the defence has to stop doing it too.

From assist to act

The next shift isn’t more intelligence. It’s intelligence that reasons for itself.

Machine learning has supported detection and prioritisation for years. That part isn’t new. What’s changing is where the intelligence happens: generative AI and autonomous agents are moving into the downstream work that used to be entirely human — incident response, threat hunting, exposure prioritisation.

The line that matters isn’t whether a platform has AI. It’s whether the AI is trusted to reason and act, or only to summarise. One makes the analyst slightly faster. The other changes who does the work. This is the direction Group-IB built Prevyn AI for. Named for “pre-vision,” it’s the cognitive core of the Unified Risk Platform —reasoning over an intelligence data lake built from decades of cybercrime investigations and law enforcement collaboration. It already runs in agentic mode in Threat Intelligence and assistive mode in Managed XDR, preparing the insights and, increasingly, taking the actions that follow them.

That’s what moving from reactive to predictive actually looks like. Not a chatbot bolted onto a dashboard, but intelligence that takes the next step itself.

The next intelligence

The budget conversation no one starts early enough

There’s a quieter argument the buying committee tends to raise late: cost predictability. A consolidated platform, one data lake covering threat intelligence, fraud, detection and response, with unlimited users, APIs, hunting rules and takedowns turns a sprawl of per-seat, per-query line items into a single, forecastable number. For a large team, that’s not a feature. It’s the difference between a budget you can defend and one you keep re-explaining.

What are the defining currents?

The market is moving from observability to consequence.

The direction of travel is clear, and it’s worth saying plainly. The market is consolidating around platforms that can prove an outcome: closed-loop enforcement, fraud and threat data fused at the source, attribution with real depth behind it. Passive feed consumption, however polished the dashboard, is quietly becoming indefensible as a standalone strategy. Prediction-first defence isn’t a slogan. It’s a concrete set of moving parts: attack-path modelling that shows you where an intrusion goes next, predictive fraud disruption, and unified incident management that runs across threat intelligence, attack surface, digital risk and cloud posture as one motion rather than four tools.

Intelligence is only as good as what happens next. Everything in your programme that comes after the alert is the part that actually defends you.

If you want to understand where the gaps are in your threat intelligence programme, not a demo, just a direct conversation, tell us your sector, your current workflows, and how intelligence reaches your security operations today.

We’ll help you identify where intelligence is being lost, delayed, or disconnected from action. Talk to Group-IB experts.