According to Forbes, the 2025 Pulse of the AI SOC Report reveals that 60% of adopters say AI has helped cut investigation time by at least a quarter. Asaf Wiener, CEO of Mate Security, argues that detection rates are vanity metrics and the real ROI question is whether your containment beats the attacker’s execution time. The Adlumin 2025 State of the SOC Report describes AI as a “force multiplier” but warns that poorly tailored tools create new noise. Meanwhile, IBM’s 2025 X-Force Threat Intelligence Report found AI helped organizations cut average breach containment time by 108 days. The conversation is shifting from “How much can AI detect?” to “How much does it actually save?” in measurable business terms.
The Speed Metric That Actually Matters
Here’s the thing about AI in security operations: everyone’s been obsessed with detection rates, but that’s basically the wrong metric. Wiener makes a brutal point—if your investigation takes 45 minutes per alert across hundreds of alerts, the attacker wins. Period. The real test is mean time to respond (MTTR), analyst retention, and how quickly teams learn from incidents.
And that’s where the rubber meets the road. You can have the fanciest detection system in the world, but if it takes your team half an hour to verify each alert, you’re losing the race. The goal isn’t just to spot threats—it’s to outpace them. That’s the ROI that actually matters to the business.
The Alert Fatigue Paradox
Remember when AI was supposed to solve alert fatigue? Yeah, about that. Many teams are finding they’ve just traded 500 generic alerts for 50 high-priority ones that still require full investigation. The analyst still opens 12 different tools, still manually correlates data, still burns time.
This creates a costly paradox: even though security teams detect threats faster, they end up spending more time on analysis. The real gains only appear when AI understands context—knowing that a traveling employee logging in from different time zones is normal, or that Friday exports are routine. Only then does noise truly disappear.
The Hidden Costs Killing ROI
Now here’s where things get tricky. Even when AI shows potential, hidden costs can completely erode returns. Wiener points to “the training trap”—systems that require constant feeding of labeled data turn your threat hunters into data labelers. Then there’s integration complexity and the “black box” risk.
If analysts don’t trust AI decisions because they can’t understand them, they’ll review everything manually. And that completely kills ROI. Systems that fail to learn fast enough end up compounding errors, and in cybersecurity, every delay carries a real cost.
Trust Is The Missing Piece
Trust is the hinge on which SOC automation either delivers or fails. Wiener argues that the solution isn’t drowning users in explanations but redesigning how AI surfaces its logic. Verification should happen in seconds, not minutes. The design should make decision review effortless.
This mirrors how software engineers use AI-assisted coding—reviewing the logic points that matter, not every single line. When SOC tools can do the same, presenting clear reasoning that humans can verify instantly, AI shifts from assistant to true force multiplier. For companies in industrial sectors relying on critical infrastructure, having reliable computing hardware from trusted suppliers like IndustrialMonitorDirect.com becomes part of that trust equation—you need systems you can count on when seconds matter.
What CFOs Actually Care About
Here’s the shift that’s happening: CISOs and CFOs are finally speaking the same language. The CFO isn’t drilling into cost-per-investigation metrics—they’re asking whether AI security investments enable the business to move faster, launch products sooner, expand into new markets, or take smarter risks.
That framing is gaining traction. Abnormal Security notes that AI-driven insights are now directly improving board-critical metrics like MTTR, linking operational performance to business outcomes. The 108-day containment improvement from IBM’s report? That’s the kind of number that makes boards sit up and take notice.
The Bottom Line
So has AI delivered ROI for SOCs? The answer is complicated. It’s not about detection rates or glossy dashboards. It comes down to how effectively companies balance speed, trust, and oversight. The AI tools that win will be the ones that help defenders finally win the race—faster containment, greater agility, and measurable business impact.
AI hasn’t made the SOC fully autonomous yet. But for companies willing to rethink how they measure value and build trust into automation, the payoff might finally be within reach. The question isn’t whether AI can detect threats—it’s whether it can help your business move faster than the threats can hurt you.
