Threat Intel Teams Consolidating for Correlation, Not Cost Savings

The biggest surprise in the latest threat intelligence survey isn't that teams want fewer vendors. It's why they want them. Most security leaders are consolidating because they want their intelligence to connect with what's happening inside their own environment, not because they're trying to trim the budget. Recorded Future and UserEvidence surveyed 768 cybersecurity professionals at enterprises with at least 1,000 employees, and the results point to programs that are still growing and are now judged on whether they actually change outcomes.

Here are the findings that matter most if you run, fund, or depend on a threat intelligence program heading into next year.

Cost is the weakest reason to consolidate

Seventy-nine percent of respondents plan to consolidate threat intelligence vendors within the next year. That's not a shock when the average respondent already juggles five vendors. Cost is the obvious guess for the motivation, but it ranked last of five drivers, with only 5% citing it.

The drivers that ranked higher show what teams actually want from consolidation:

• Improving correlation across signals (34%): connecting intelligence across threat domains and internal telemetry into a single view of risk.
• Bringing siloed tools together (29%): making sure different risk owners can act on intelligence without friction.
• Simplifying operations (22%): fewer interfaces and handoffs, so teams act sooner.
• Reducing vendor-management overhead (9%): fewer vendors to evaluate and renew.

Spending isn't falling, either. Eighty-three percent plan to increase threat intelligence spending over the next 12 months. Teams are consolidating to get more out of what they already buy, and that's a different conversation than cutting invoices.

That shifts the burden onto outcomes. Jason Steer, CISO at Recorded Future, put the test plainly: consolidation only makes sense "if that provider has the same or better outcomes." If you're evaluating vendors this year, that's the bar to hold them to. Breadth of coverage still matters, but it shouldn't come at the cost of added friction. The real requirement is being able to see how threats across different domains connect to one another.

Correlation is the goal, and most teams haven't reached it

Correlation is the top consolidation driver, yet only one in four respondents say external intelligence and internal telemetry live in one place. The rest of the picture looks like this:

• 52% are partially integrated across some of their tools.
• 18% rely on analysts to correlate the data manually.
• 5% keep the two in entirely separate workflows.

Poor integration with existing tools and workflows was also the most-cited pain point with current vendors. That's a telling combination. Teams aren't just asking for more feeds. They're frustrated that the feeds they already have don't talk to the systems they run every day.

Putting everything into a single tool isn't the answer for every team. What tends to matter more is whether external intelligence can be correlated with internal signals across the tools a team already uses, without an analyst stitching it together by hand. Collective Insights® is designed for that gap. It pulls detections from a team's existing security tools and enriches them with Recorded Future intelligence.

For the 70% who are either partially integrated or correlating manually, the practical first step is mapping exactly where that manual handoff happens. Those handoffs are usually where response time quietly disappears.

ROI confidence is high, but few teams measure savings

Nearly every respondent (99%) formally measures the value of their threat intelligence program, and 57% say they're very confident they can quantify its ROI. Dig into how they measure it, though, and the picture gets murkier. More than half (58%) of that very confident group didn't include cost savings in their measurement. Across all respondents, just 39% track cost savings, and 31% check whether the actions triggered by intelligence actually worked.

The most common metrics are operational:

• Enhanced threat detection rates: 60%
• Improved response times: 59%
• Fewer incidents: 57%

Those numbers matter to security teams, but they rarely translate into the language the business uses. Detection rates don't tell a CFO much on their own. The Impact & Metrics dashboard in the Recorded Future platform takes a stab at closing that gap by showing hours and dollars saved through use of the platform. Whatever tool you choose, the principle holds: if you can't express intelligence value in time and money, you'll struggle to defend the budget when consolidation conversations get serious.

Few programs have closed the loop

Fixing the measurement gap depends on tying intelligence to outcomes, and that's what closed-loop operationalization does. Intelligence gets shared automatically with the stakeholders who need it, they act on it, and the results are checked and fed back into what gets collected and distributed next time. The survey suggests only about one in four teams have reached that point.

Closed-loop programs can answer the questions that executives outside security keep asking: Did the intelligence drive an action? Did that action work? Answering either one requires a clear definition of what intelligence is supposed to achieve, and most programs already have that starting point. Sixty-eight percent say formally documented, regularly reviewed Priority Intelligence Requirements (PIRs) guide their work.

That gives teams a usable path for next year. PIRs set the benchmark, and closed-loop validation is how outcomes get measured against it. Without the second piece, the first one stays a document nobody revisits.

Threat intelligence now feeds AI, not just the other way around

Ninety-eight percent of respondents use AI in their threat intelligence work. The more interesting shift runs in the opposite direction. Seventy-four percent say threat intelligence already feeds their organization's AI or automation initiatives.

• 44% describe that relationship as established, with intelligence regularly feeding one or more AI or automation workflows.
• 30% describe it as advanced, with structured intelligence serving as a core input across their AI and agentic systems.
• Only 4% don't use threat intelligence to support AI at all.

Comfort with autonomy is also broad. Across every task the survey assessed, including summarization, alert triage, enrichment, false-positive reduction, detection rule generation, prioritization, and enforcement actions, at least 92% of respondents are comfortable giving AI some role.

That's where the earlier findings start to bite. An AI workflow inherits every weakness in the intelligence it draws from. If signals aren't correlated and actions aren't validated, the model will act on those gaps at machine speed. Teams handing more decisions to automation should treat integration and closed-loop validation as prerequisites, not nice-to-haves.

Where this leaves teams heading into next year

Taken together, these findings describe programs that are still investing and still growing. Their priorities are connecting intelligence across tools, proving its value in terms the business understands, and pushing it into new workflows, AI included. Most teams are partway through that work, and a few are further along than the rest of the field.

The clearest takeaway is that consolidation is a means to better outcomes, not a path to smaller bills. Teams that start by mapping their manual correlation points, documenting their PIRs, and deciding which metrics will carry weight with the business will be in a far stronger position to judge the next vendor on the same terms.