The next NDR will be autonomous, the co-pilot of tomorrow’s SOC

In a world where every digital dependency becomes an attack surface, the question is no longer if a company will be targeted, but how quickly it can detect and contain the incident. Yet most SOCs are still built for yesterday’s world: massive alert streams, overwhelmed analysts, and manual procedures. The rise of AI Agents changes the equation. Acting as software teammates, they prioritize, correlate, and orchestrate responses within minutes while documenting every step for auditing and continuous improvement. The challenge is not merely technical: it’s strategic for the executive board, operational for SOC leaders, and profoundly human for the teams who live and breathe security every day.

For an executive, cybersecurity is not a cost line; it’s a direct variable of business continuity, reputation, and increasingly, competitiveness. 2025 data confirms a major turning point: organizations that make extensive use of AI and automation in security reduce the average cost of a breach by about $1.9 million and shorten its lifecycle by roughly eighty days, compared to those with limited adoption. The global decrease in the average breach cost to $4.44 million – the first decline in several years – can be directly attributed to this improved ability to detect earlier and contain faster. In other words, investing in AI within the SOC is not a technological gamble; it’s a quantifiable insurance against avoidable losses, minimized regulatory penalties, and preserved market trust.

Digital transformation has multiplied connections with vendors, software providers, and service partners; and the number of attack paths has grown accordingly. In 2025, the share of breaches involving a third party has doubled, now accounting for nearly one in three incidents. This reality places governance and orchestration back at the center of the equation: an AI-augmented SOC must be able to monitor, prioritize, and act beyond its direct perimeter while staying aligned with increasingly specific regulatory requirements.

Under NIS2, affected entities must issue an early warning within 24 hours, a notification within 72 hours, and a final report within one month. In the financial sector, DORA came into effect on January 17, 2025, mandating demonstrable operational resilience especially regarding critical suppliers. By automating the collection of indicators, report generation, and action traceability, AI Agents make these requirements achievable without adding organizational burden.

On the ground, AI Agents absorb the repetitive work that traditionally overwhelms Level 1 teams: initial triage, indicator enrichment, log correlation, and execution of standardized actions. Within seconds, they can isolate a machine via the EDR, block an outbound communication at the firewall, revoke an access token, or open a richly contextualized ticket. Analysts, in turn, can focus on threat hunting, investigation, and detection improvement. This shift in workload enables organizations to handle the growing volume of logs, network flows, and cloud telemetry without hiring proportionally: making scalability finally economical. Most importantly, mean time to detect (MTTD) and mean time to respond (MTTR) shrink to minutes for known scenarios, directly reducing the extent of damage and thus the financial impact of incidents.

Imagine a Friday at 11:07 a.m. A spike in file writes on an SMB share, unusual extensions, and high entropy trigger a suspicion of active encryption. Instead of a flood of unqualified alerts, the AI Agent powered by a possible NDR-based network detection flags a coherent pattern: the sequence is abnormal, the data volume is spiking, and the host matches a high-risk profile. It takes action: the host is isolated through the EDR, the route to the share is blocked, and the team receives a ticket with all artifacts and a suggested internal communication. By 11:24 a.m., the malicious activity has stopped. The weekend can begin, no emergency recovery plan required.

A different scene: a quiet workstation, but one that “talks” at regular intervals. The AI Agent links a high DGA (Domain Generation Algorithm) score to a pattern of beaconing and the execution of an obfuscated PowerShell script. In context, the hypothesis of a C2 (Command and Control) channel becomes credible. The response is orchestrated: outbound blocking, quarantine, retro-hunting through historical flows, and automatic consultation of threat intelligence sources. False positives are contained through business-domain exclusion lists and fine-tuned sensitivity settings. The incident is closed in under an hour, and analysts spend the rest of the day studying the artifact and hardening detections.

What seems spectacular at the scale of a single incident becomes decisive over the course of a fiscal year. When Level 1 operations are handled by intelligent automation, FTEs can be reallocated to threat intelligence, proactive hunting, and detection posture improvement. The combined outcome – fewer incidents that escalate and more analysts focused where they create the most value – delivers the kind of structural savings every SOC leader seeks: the cost curve is no longer linear with volume growth. The ROI model then becomes clear: avoided breach losses (with a reference differential of roughly $1.9 million and eighty days), operational savings, fewer fines and compliance costs, all balanced against the initial investment and required integrations.

A high-performing SOC is not just an architecture and a set of tools, it’s a team that stays, communicates, and grows together. By delegating noise management to AI Agents – correlation, mechanical checks, and standardized response actions – organizations reduce monotony and on-call fatigue. Analysts develop new skills, pursue more complex investigations, and help formalize more robust playbooks. Each incident feeds institutional memory: decisions made, contexts, artifacts, IOCs, reports, and API exports become a living knowledge base. This knowledge capitalization ensures consistent responses despite staff turnover and smooths onboarding. It’s also a strength during audits, where traceability and explainability matter just as much as execution speed.

Operational success requires discipline. As use cases become industrialized, governance becomes the key to scaling safely. Access controls, role separation, logging, model supervision, and management of “ignore lists” are all safety nets that prevent drift and reduce the attack surface of the AI systems themselves. The 2025 reports highlight a critical issue: ungoverned AI, or “shadow AI”, increases breach costs and makes incidents harder to control. Adopting AI Agents therefore also means investing in governance – your own governance – so that automation serves your policies, not the other way around.

In the coming years, the threat landscape will continue to evolve toward greater stealth, industrialization, and supply-chain exploitation. SOCs that successfully combine AI Agents, NDR, EDR, and threat intelligence under strong governance will follow a different trajectory: detection times measured in minutes, orchestrated and auditable responses, demonstrable compliance with NIS2 and DORA, and teams continuously learning from real-world incidents. This measurable resilience is a true asset: it reduces losses, reassures regulators, strengthens customer trust, and above all frees management time for innovation and growth. Investing now means securing the future while already improving everyday performance.

The global average cost of a data breach is around $4.44 million, down about 9% compared to 2024. Organizations with extensive AI and automation capabilities save up to $1.9 million and shorten the incident lifecycle by eighty days. At the same time, third-party-related breaches account for roughly 30% of all cases. The median attacker dwell time is estimated at around eleven days, with significant variations depending on how the breach is detected. On the compliance side, NIS2 requires early reporting within 24 hours, notification within 72 hours, and a final report within one month, while DORA has been in force since January 17, 2025, across the financial services sector.

Sources

• IBM – Cost of a Data Breach Report 2025
• IBM – IBM — Quantitative Summary (Savings: $1.9M, – 80 days) via Baker Donelson (PDF)
• Verizon – Data Breach Investigations Report 2025
• Mandiant/Google Cloud – M‑Trends 2025
• NIS2 – guides & analyses (Timelex, RadarFirst, CCB Belgium)
• DORA – Official EIOPA site and ACPR FAQ