Will AI replace Information Security Analysts?

Overall automation risk is moderate because while AI excels at parsing threat intelligence and generating policy drafts, the high liability and evolving adversarial landscape require human oversight. Documentation and threat telemetry monitoring drive the highest exposure, whereas vendor coordination and high-stakes stakeholder discussions remain durable. This quarter, analysts should master security orchestration, automation, and response (SOAR) platforms that integrate LLMs to augment threat analysis while learning how to audit AI systems for vulnerabilities.

Partially. Information Security Analysts scores 54/100 — some core duties are highly automatable, but enough durable human work remains that the occupation is transforming rather than disappearing overnight. This is a task-exposure index, not a guarantee that hiring stops.

The score is an importance-weighted average of automation probabilities across the top 11 O*NET tasks for SOC 15-1212.00. 1 task score at or above 80% automatable; 1 fall into the safer band (under 30% or labeled physical). Roughly 95% of scored tasks are primarily digital.

None of the top 11 tasks currently clear the ≥80% automation threshold — exposure is more diffuse across mid-range probabilities.

Few tasks in this profile clear the “safe” threshold, which is why the aggregate score skews higher and why adjacent lower-risk careers deserve serious consideration.

Official BLS data places median pay for this occupation family at $129,180. with projected employment change of +21.0% over the latest 10-year outlook window. Typical entry education: Bachelor's degree. Related work experience usually required: Less than 5 years. Wage and growth context ($129,180, +21.0%) should be read alongside the AI score — not as a substitute for it.

Information security analysts should pivot away from routine log monitoring, basic compliance documentation, and standard script generation toward strategic threat modeling and incident response leadership. Workers should cultivate advanced skills in securing AI architectures, governance of autonomous agents, and cross-functional incident communication where human accountability is mandatory.

We pull Core O*NET task statements for Information Security Analysts, score each for Generative AI automation probability, weight by O*NET importance, and merge the result with BLS wages and employment projections on the SOC code. Full methodology, limitations, and prompt versioning are documented on the methodology page.

Information Security Analysts demonstrates a hybrid defense profile (53/100, verdict: "Moderate Hybrid Moat"). While its digital and documentation workflows are exposed to generative AI compression, direct human-in-the-loop engagement (87/100) and contextual real-world adaptability provide a durable defensive moat against complete end-to-end automation. Interpersonal & Face-to-Face Interaction is the primary barrier (87/100), protecting human workers from algorithmic displacement.

Federal OEWS data reveals an earning spread of $113,160 from the 10th percentile ($69,210) to the 90th percentile ($182,370). The middle 50% of practitioners earn between $90,050 and $153,550. Compensation for Information Security Analysts reflects a hybrid balance of cognitive judgment and physical/interpersonal execution. Top-tier compensation ($182,370) is driven by complex problem-solving and domain mastery that resists routine software automation.

Research identifies substantial augmentation dynamics for Information Security Analysts. While standalone language models show direct exposure of 35/100, coupling AI models with domain-specific software tools and APIs drives exposure to 65/100 (+30 point uplift). This indicates that AI acts as an efficiency amplifier rather than a standalone replacement. Software tooling expansion increases exposure by +30 points (from 35/100 to 65/100), demonstrating that integrating AI into existing software suites significantly expands automated task throughput.