Security leaders accept AI for triage, detection engineering, and threat hunting as alert volumes and burnout hit points.
A comprehensive survey of 282 security leaders from businesses across the industry reveals the harsh reality facing modern security operations centres. The alert volume reaches unsustainable levels, leaving the team uninvestigated critical threats. You can download the full report here. Research conducted primarily among US-based organizations shows that adoption of AI in security practices has shifted from experiments to critical ones as they struggle to meet the ever-growing stream of security alerts.
The findings portray the industry at a turning point where traditional SOC models are buckling under operational pressure and solutions that drive AI are emerging as the main path.
The alert volume reaches its limit point
Security teams own alerts, and organizations handle an average of 960 alerts per day. Large companies face even more challenging reality, processing over 3,000 alerts per day from an average of 30 different alert generation security tools.
This volume creates a fundamental operational crisis in which security teams need to make difficult detection and investigation decisions under extreme time pressures. Research reveals that alert fatigue evolves beyond the emotional burden and becomes a measurable operational risk.
The investigation is slow and remains manual
Pure mathematics of alert processing expose the scale of the problem. The findings revealed that it takes an average of 70 minutes to fully investigate an alert, meaning that someone can find time to see it. Research shows that on average there is a full 56 minutes of pass before everyone acts on an alert. This impossibility forces difficult choices about which alerts will attract attention and which will be ignored.
The findings clearly demonstrate important and well-known challenges within the Security Operations Center (SOCS). The vast amount of alerts that occur every day far outweigh the ability of human analysts to thoroughly investigate them. If the problem gets worse, the latest security stacks and data sources continue to increase in number and complexity, resulting in longer investigation times.
For high-priority incidents that require immediate attention, these time frames represent unacceptable delays that could violate the severity level. According to the latest CrowdStrike Cyber Threat report, cyber threats like business email compromises only take 48 minutes on average to lead to incidents.
The hidden costs of an overwhelming SOC
This overwhelming influx creates an impossible dilemma, forcing SOC teams to make difficult and often dangerous choices about which alerts will attract attention and which will inevitably be ignored. The consequence of this impossible situation is that the risk of missing out on a real threat amidst the noise, ultimately undermining the organization’s security attitude.
40% of security alerts are not fully invested due to volume and resource constraints. Even more troublesome, 61% of security teams admitted to ignore alerts that were later proven to be a critical security incident.
This statistics represent a fundamental breakdown of security operations. Teams designed to protect their organizations are unable to systematically examine nearly half of the potential threats they detect. The investigation revealed that this was not a negligence, but a forced adaptation to impossible workload requests.
SOC teams struggle with operation 24/7
The study reveals key gaps in 24-hour security coverage. Many organizations do not have enough staffing to maintain an effective 24/7 SOC operation. Create a vulnerability window outside of business hours that handles the same alert volume as the skeleton crew overwhelms full-stright day shifts.
Analyst burnout is not just a HR concern, it has become a quantifiable issue. The team reports that suppressing detection rules has become the default coping mechanism when alert volumes become unmanageable. This approach reduces immediate workloads, but can create blind spots in security coverage.
Staffing challenges are exacerbated by the special nature of security analysis work. Organizations cannot easily scale their teams to grow as alert volumes grow, especially given the lack of experienced cybersecurity experts in the current job market.
AI moves from experiments to strategic priorities
Security operations AI has rapidly risen its priority ladder and is now ranked as the top three initiatives along with core security programs such as cloud security and data security. This illustrates a fundamental shift in the way security leaders view them as key enablers for operational success today.
Currently, 55% of security teams have already deployed AI co-pilots and assistants in production, supporting alert triage and research workflows.
The next wave of adoption is coming quickly. Among teams that are not yet using AI, 60% plan to evaluate AI-powered SOC solutions within the year. Research shows that 60% of future SOC workloads will be processed by AI over the next three years.
Organizations are seeking AI for core research tasks
The security team is identifying where AI can make the biggest difference. Triage is 67% above the list, followed by detection tuning (65%) and threat hunting (64%).
These priorities reflect the growing desire to apply AI to the early stages of the investigation and surface meaningful alerts, while providing repeated analysis of early context and offloading. It’s not about automating human judgment, it’s about speeding up workflow and sharpening human focus.
The barrier remains, but the momentum is clear
Despite strong recruitment intent, security leaders identify meaningful barriers to AI implementation. Data privacy concerns, integration complexity, and explainability requirements are at the top of the organization’s hesitancy list.
Future SOCs will become a reality
Research data reveals a clear trajectory for hybrid security operations where AI handles everyday analytic tasks and human analysts focus on complex research and strategic decision-making. This evolution promises to address both volume issues and analyst burnout at the same time.
The success metrics of this conversion may focus on improving operational efficiency. In addition to traditional warning closure rates, organizations measure progress through average time (MTTI) and average time (MTTR). Other meaningful success metrics include using AI to raise and train new SOC analysts to dramatically accelerate ramp up times.
Ensuring comprehensive alert coverage through AI augmentation allows organizations to reduce the risk tolerance currently enforced by volume constraints. Future SoC investigates more alerts more thoroughly, while reducing manual effort from human analysts.
How Prophet Security Helps Customers
Prophet security helps organizations move beyond manual investigations, automate triage, accelerate investigations, and pay attention to fatigue with the Agent AI SOC platform, which ensures that all alerts will draw the attention they deserve. By integrating existing stacks, Prophet AI improves analyst efficiency, reduces incident dwell time, and provides more consistent security results. Security leaders use Prophet AI to maximize the value of people and tools, strengthen security attitudes, and turn daily SOC operations into measurable business outcomes. Access Prophet Security to learn more or request a demonstration and see how Prophet AI can enhance your SOC operations.
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