As AI takes on more of the enrichment, correlation, and initial assessment inside the SOC, roles, skills, and KPIs still require deliberate redesign. Security leaders need to decide where automation is dependable, where human judgment should remain decisive, and how teams should be measured when alert handling is no longer the center of the operating model
The Gartner® report, The Roles Required for the AI-Enabled Security Operations Center (SOC), examines the roles and capabilities Gartner expects the SOC to require as AI becomes embedded in security operations. Rapid7 is offering complimentary access to the research, which we believe can help leaders plan their future workforce, operating model, and investment priorities.
Many analyst roles and performance measures remain closely tied to handling individual alerts. As organizations introduce AI SOC agents to support enrichment, correlation, and initial assessment, leaders may need to reconsider where human expertise creates the greatest operational value.
Gartner states, "Human analysts must transition from alert triage roles to end-to-end case ownership and effective response option communication." At Rapid7, we believe this shift creates an opportunity for analysts to focus their judgment on validating context, coordinating response, and communicating decisions clearly.
Gartner also recommends, "Stop recording alert metrics and run the SOC on cases and decisions." Robert Willis, VP of Managed Detection and Response at Rapid7, puts it plainly: "Alert volume is a distraction. The real measure of SOC value is decision quality, did you get the right answer, fast enough to act on it? MDR is built to deliver exactly that: answers, not alerts, so your team can focus on ownership and response rather than triage." MDR can help manage alert volume while adding investigation and response capacity, giving internal teams more space to focus on the cases that require their context and ownership.
Rapid7's experience applying agentic AI within our MDR SOC shows how this division of work can operate in practice. Our agentic workflows have saved more than 200 analyst hours each week and achieved 99.93% benign-disposition accuracy, reducing the repetitive work involved in initial triage and giving analysts more time for complex, ambiguous, and higher-stakes investigations.
We believe human judgment remains essential when a decision carries operational consequences. AI can gather evidence, correlate activity, and present a structured rationale, while analysts validate the conclusion, consider the organization's priorities, and determine the appropriate response. This human-led, AI-driven model combines machine-speed investigation with accountable decision-making.
As AI-enabled workflows expand, engineering discipline is likely to become increasingly important within security operations. Reliable processes require people who understand threats and security data, can test automated workflows, and can establish appropriate controls around AI-supported decisions.
The report includes the strategic planning assumption, "By 2028 there will be 50% more engineers in security operations teams than analysts." Gartner also advises organizations, "Redefine detection engineering role descriptions and hiring requirements. Expand them beyond rule writing to include prompt design, workflow testing, and AI output validation."
From Rapid7's perspective, detection engineering is developing into a broader operational discipline. Data quality, testing, version control, rollback procedures, documentation, and human approval paths all contribute to dependable AI-enabled workflows. Investing in these capabilities can help teams use automation confidently while keeping people central to consequential security decisions. The report also considers how security operations can identify and validate weaknesses before they contribute to an incident. Gartner states, "Exposure management is the emerging SOC capability to invest in before anything else."
At Rapid7, we believe exposure management should become a standing operational discipline that connects discovery, validation, prioritization, and remediation with detection and response. Exposure Command can help teams understand which exposures present the greatest risk and direct remediation accordingly, while MDR provides additional expertise and capacity to investigate and respond when threats emerge.
Together, these capabilities support a human-led, AI-driven operating model focused on informed decisions, continuous exposure reduction, and effective response. Access the complimentary Gartner report, The Roles Required for the AI-Enabled Security Operations Center (SOC), to explore how Gartner expects SOC roles and responsibilities to evolve.