The Revolutionary Impact of Agentic AI
Unifying Security Operations Through Agentic AI Solutions
Author: Trescudo vCISO Team • Reviewed by: Derick Smith (CEO) & Marçal Santos (CISM, CDPSE)
TL;DR
Agentic AI—autonomous, goal-driven agents working as a team—turns a fragmented SOC stack (SIEM, XDR, SOAR, IAM, GRC) into a coordinated defence mesh. The gain isn’t fancy prompts; it’s lower MTTR, fewer handoffs, consistent evidence, and measurable resilience for NIS2/DORA.
Why SOCs stall today
Tool sprawl: Alerts scatter across SIEM/XDR/EDR/SaaS logs.
Human bottlenecks: Repetitive Tier-1 triage consumes analysts.
Policy drift: IR/GRC steps vary by shift, hurting audit trails.
Supply-chain noise: Vendor incidents multiply decisions and data pulls.
What Agentic AI changes
Unified triage: One agent normalizes alerts, ranks risk, and dedupes cases across sources.
Evidence autopilot: A forensics agent collects timelines, PCAP/log slices, and artifacts—chain-of-custody intact.
Playbook execution: A SOAR agent runs conditional response (isolate host, rotate keys, revoke tokens) with rollback logic.
GRC glue: A compliance agent maps actions to policy (NIS2 Art. 21/23), drafts regulator-ready notes (24h/72h/1-month), and fills lessons-learned.
Vendor orchestration: A supplier agent checks IR SLAs, opens tickets, and requests IoCs from third parties.
Ops resilience: An SRE agent tests failover (DNS, region-out), tracks RTO/RPO, and reports gaps to the board.
Knowledge loop: Agents learn from closed cases and auto-tune detections, hunts, and playbooks.
7-step roadmap (90 days)
Pick 3 use cases: phishing triage, endpoint ransomware burst, suspicious OAuth token.
Unify data access: read-only connectors into SIEM, EDR/XDR, M365/Google, IdP, ticketing.
Define guardrails: who can quarantine/kill-process/rotate creds; human-in-the-loop thresholds.
Instrument playbooks: codify actions with pre/post checks, evidence capture, and rollback.
Pilot agents: start in shadow mode; compare agent vs human outcomes.
Promote safely: enable automation for low-risk actions; require human approval for invasive steps.
Measure weekly: publish KPIs; feed results into detection tuning and training.
Metrics the board understands
MTTD / MTTR: ↓ 30–60% in first quarter for targeted use cases.
Auto-closure rate: % alerts resolved with zero human touch (and no re-open).
Evidence completeness: playbook steps + artifacts present (>= 95%).
Supplier responsiveness: time to first vendor response; % with 1-hour SLA.
Patch/compensating control latency: KEV/Critical to mitigated.
RTO/RPO achieved: per Tier-1 service, quarter over quarter.
Risk & governance (make it safe)
Policy-backed autonomy: limit agent privileges; enforce just-in-time access.
Transparency: every agent action logged, reversible, and attributable.
Data minimization: segment secrets; redact PII in model contexts.
Red-team the agents: simulate prompt/command injection and tool abuse.
Regulatory fit: map outputs to NIS2/DORA evidence (timelines, decisions, supplier comms).
Quick wins you can do this month
Auto-triage phishing with enrichment + user notification + mailbox sweep.
Auto-contain high-confidence ransomware (isolate host, kill process, block hash, snapshot).
Vendor IR SLA bot: open supplier tickets with IoCs, request status hourly, log receipts.
Draft 24h/72h regulator notes from timeline + artifacts (human approves).
Common pitfalls (and fixes)
Hallucinated actions: enforce tool-verified outcomes; block free-form shell by default.
Runaway automations: require human confirmation for destructive steps; add kill-switch.
Bad data access: use scoped service accounts; rotate tokens; monitor agent activity in SIEM.
Bottom line
Agentic AI doesn’t replace analysts; it removes toil, standardizes response, and closes the audit loop. Start narrow, measure relentlessly, expand where the data proves ROI.
Want a 30-minute Agentic SOC readiness check and pilot plan? https://clients.trescudo.com/form1