Study: Artificial intelligence is Now Essential in Modern SOCs

Security Operations Center (SOC) teams are drowning in noise. For CIOs, CISOs, and tech leaders tasked with digital resilience, the strain is mounting not just from the volume of alerts, but from the human limits to triage, analyze, and act. Prophet Security’s “State of AI in Security Operations 2025” report reveals that SOC workloads are reaching a breaking point unless AI becomes a strategic amplifier rather than a speculative add-on.

Under the microscope are not just efficiency gains, but decisions about trust, transparency, and AI governance. As AI begins to shoulder repetitive investigation tasks, how one blends human judgment with autonomous systems becomes a core design challenge. Below is a core excerpt capturing Prophet’s findings and context.

As reported by Rodney Bosch in “Prophet Security Report Highlights Urgent Need for AI in SOCs” on SecurityInfoWatch:

“Security Operations Centers (SOCs) are facing unprecedented strain. The newly released ‘State of AI in Security Operations 2025’ report from Prophet Security highlights an industry under siege by data overload, talent shortages and an escalating ‘alert problem.’

The survey of nearly 300 security leaders found that 40% of alerts go uninvestigated and 60% of teams have experienced breaches tied to ignored alerts. With average alert dwell time hovering near an hour, traditional approaches are faltering against increasingly agile adversaries.

Against this backdrop, Grant Oviatt, Co-founder and Head of Security Operations at Prophet Security, discussed the report’s findings with SecurityInfoWatch and what they mean for security teams.

Alert Fatigue and Analyst Burnout

Oviatt emphasized the toll alert overload is taking on SOC teams. Analysts are often trapped in a cycle of triaging and investigating repetitive alerts, most of which are false positives. ‘SOC team members’ morale is at an all-time low, many analysts feel like they’re a hamster on a wheel constantly triaging, investigating alerts, many of them false positives, which leads to burnout and attrition,’ he said.

The average analyst tenure, once two years, has now dropped to just 12 months.

He sees artificial intelligence (AI) as a critical turning point. Instead of analysts spending hours on low-value tasks, AI can take on the scale and speed of investigations. ‘The analyst’s role is not to echo the machine, but to guide and challenge it,’ Oviatt explained.

He added that AI serves as a force multiplier, investigating at scale, surfacing hidden patterns and accelerating response. Analysts contribute the judgment, contextual awareness and adversarial mindset that machines lack.

‘Together, this partnership elevates investigations from quick pattern matching to meaningful, outcome-driven security decisions,’ he said.”

Continue reading “Prophet Security Report Highlights Urgent Need for AI in SOCs” by Rodney Bosch on SecurityInfoWatch.

Why It Matters to You

This report nails a central truth for TechEDGE leaders: AI is no longer a speculative advantage in security—it’s a capacity multiplier you can’t ignore. When 40% of alerts go uninvestigated, your blind spots become liabilities, not just inefficiencies. The fusion of automation and human oversight is central to credibly scaling security operations.

At the same time, the barriers to adoption—such as trust, compliance, and data integrity—are not just technical knobs but strategic choices. How you phase the prompt in AI (read-only first? human approval gates?) will ripple into governance, incident escalation, and even board-level risk narratives. For cloud, identity, and hybrid deployment contexts, this report gives momentum to AI-centric architectures in security operations.

Next Steps

• CISO/Security Lead: Run a small pilot AI-assisted investigation engine on low-risk alert flows; measure triage time and analyst effort savings. 
• Security Ops/Incident Team: Embed read-only AI modules first; establish auditability and transparency mechanisms to gain trust. 
• Compliance/Risk Teams: Define data privacy, logging, and retention policies tied to AI usage; bake in fallback rules (human review) for sensitive cases. 
• Architecture/Engineering: Ensure telemetry, logging, identity, and context data are feedable into AI models with traceability. 
• Executive/Strategy: Build a dashboard translating AI-driven SOC gains (reduced dwell time, human hours reclaimed, breach risk mitigated) into business outcomes.