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Your CFO wants to cut headcount. Your vendors promise autonomous security. And you're stuck in the middle, trying to figure out if AI agents can actually do the work.
Here's what Gartner found: they can't. At least not the way many vendors are selling it.
According to Gartner, "By 2027, 90% of successful AI implementations in cybersecurity will be tactical — task automation and process augmentation — rather than role replacement."¹
Not role replacement. Task automation.
That's not a minor distinction. It's the difference between a strategic investment and an expensive mistake.
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The pitch sounds good: AI handles Level 1 triage, your senior analysts focus on real threats, costs go down. It's a clean story, but Gartner research shows what happens in practice:
The training regime for most SOC organizations is built on experience gained in basic roles. Junior analysts build pattern recognition and foundational skills through Level 1 triage work. Gartner warns that solutions promising to automate this work will reduce practical learning opportunities for tomorrow's security analysts. Skills like investigating, validating with data, and cross-referencing with business priorities are developed through these foundational tasks. Cut that path, and you've undermined your ability to develop senior talent.
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Gartner breaks down what vendors leave out of the sales deck: data processing costs, security and retention overhead for the AI systems themselves, and the gap between trial pricing and long-term subscriptions. The report also flags the unquantified future training burden needed to validate AI findings. Factor in all of it, and the ROI math changes.
Gartner data shows that successful AI implementations in the SOC remain tactical—focused on task automation and process augmentation rather than role replacement. They require human oversight and critical validation by an analyst with contextual business knowledge. Without robust audit and ratification processes, automated response actions risk bypassing critical scrutiny.
Gartner research focuses on staffing impacts, retraining pressures, and the need for human-in-the-loop frameworks. All valid. But there's a structural problem the report doesn't cover: your agents inherit your infrastructure's blind spots.
If your SOC can't see NOC logs, and your NOC can't see endpoint data, your autonomous agents have the same limitations. You haven't solved the problem, you've automated it.
AI agents are only as good as the data they can access. Most organizations have logs scattered across silos: security in the SIEM, IT/ops in observability platforms, network teams in their own tools, compliance in another system. An agent that can only query one of those systems will miss issues that span multiple domains.
The Gartner framework for AI adoption is sound: augment rather than replace, maintain human validation, invest in upskilling. But none of that matters if your agents are working with fragmented visibility. You need a unified layer that lets them see across silos including SIEM, observability, network, cloud, and compliance, or you're building on a broken foundation.
If you're evaluating AI-driven SOC solutions, here's what Gartner research suggests you should focus on:
Gartner explicitly recommends implementing a "human-in-the-loop" framework where an analyst with contextual business knowledge validates AI-generated findings before automated response actions deploy. Don't trust vendor promises that AI can replace human roles like Level 1 triage.
Gartner advises redirecting cost savings from automation into reskilling programs. Focus on developing skills AI can't replace: advanced threat hunting, data validation, prompt engineering, and contextual threat understanding.
Factor in the often-overlooked costs Gartner identifies: data processing, security, retention for the models, and the training burden to validate AI findings. Differentiate between trial costs and longer-term subscription overhead.
And one more question Strike48 believes is essential: Can your agents actually see everything they need to investigate issues end-to-end? If the answer is "we integrate with X and Y," ask what happens when an issue spans X, Y, and Z. Fragmented visibility limits what agents can do, regardless of how sophisticated the AI is.
The complete Gartner report covers their framework for AI adoption in security operations, the long-term impacts on SOC skill development, and the hidden costs vendors won't tell you about.
Download: Cybersecurity Trend: AI-Driven SOC Solutions Destabilize Operational Norms →
The report includes: