Vaibhav Dutta, Associate Vice President and Global Head-Cybersecurity Products & Services at Tata Communications
The sophistication and continuous threat of cyberattacks have outpaced manual response times, and enterprises are confronting a pivotal truth: the era of reactionary cybersecurity is over. Traditional Security Operations Centres (SOCs) are no longer enough, while businesses are now requiring a new breed of cybersecurity capability – one that is predictive, adaptive, and fast, powered by automation and intelligent augmentation.
Autonomous SOCs are no longer a futuristic concept – they are emerging as a necessity. With cybercrime has costed the global economy $9.5 trillion (projected figure) in 2024 and attackers increasingly using generative AI to scale and sharpen threats, organisations cannot afford even a second of lag in their security posture.
The next-gen SOC integrates AI, automation, and real-time threat intelligence to monitor, detect, and respond with speed. The goal for enterprises today is to detect threats faster, contain them earlier, and reduce the blast radius of a breach.
This shift isn’t just about automating known responses. It’s about building intelligent workflows that combine the scale and speed of machines with the reasoning and strategic thinking of experienced analysts. The security challenge is too vast for either side to win alone. It’s the combination that matters.
The Problem with Legacy SOCs
Most traditional SOCs are built for a world that no longer exists. These command centres rely heavily on manual processes, siloed threat monitoring, and static playbooks. As enterprise environments become more fragmented – with data flowing between multi-cloud deployments, edge devices, and mobile workforces, the sheer volume of telemetry becomes unmanageable without intelligent augmentation.
On average, security teams use over 40 different cybersecurity tools. Correlating these fragmented signals and making decisions in real-time has become a near-impossible task. This operational sprawl does not just slow down response – it creates gaps. The result? Longer Mean Time to Detect (MTTD), longer Mean Time to Respond (MTTR), and lower overall resilience.
Why Augmented SOCs Change the Game
AI-augmented SOCs use SOAR (Security Orchestration, Automation, and Response) for predefined rules-based actions, but they’re now evolving to incorporate agentic AI – AI systems that are autonomous, adaptive, and context-aware.
Where traditional SOAR tools follow static playbooks and execute rule-based tasks-such as blocking IPs or enriching alerts-agentic AI can go several steps further. It not only analyses threat signals but also understands the broader context, proposes next steps, and explains its reasoning.
While SOAR is effective at automating repetitive actions, agentic AI brings flexibility and judgment into the equation. These systems behave more like intelligent assistants: they adapt to evolving threats, handle unstructured situations, and simulate human-like decision-making.
As a result, SOCs are no longer limited to automation alone, but can start to operate with goal-driven intelligence that is dynamic, explainable, and far more effective at managing advanced threats.
By fusing SOAR with Agentic AI, augmented SOCs reduce detection and response windows dramatically. Playbooks aren’t just triggered – they evolve. Systems can halt lateral movement, isolate infected endpoints, and even initiate recovery workflows based on contextual judgment, not just static rules.
The Real-World Impact
Before diving into the operational benefits, it’s important to frame the stakes. Cybercrime is projected to cost the global economy $10.5 trillion in 2025, making it the third-largest economy if measured by GDP. In such a high-stakes environment, enterprises cannot afford delays, false positives, or fragmented defence.
In practice, this evolution translates into three immediate benefits:
- Speed: Integrated automation shifts detection from minutes to seconds. AI can pre-analyse events before humans even see them.
- Accuracy: Contextual intelligence reduces false positives and prioritises what really matters.
- Continuity: AI ensures around-the-clock vigilance – even when human analysts are focused elsewhere.
From Analysts to Architects
This isn’t a story of replacement – it’s a story of elevation. Security teams evolve from reactive responders to architects of intelligent defence systems. They design detection logic, refine AI playbooks, and continuously train their systems using new threat intelligence.
AI doesn’t steal jobs – it changes them. And for forward-thinking enterprises, that’s an opportunity.
Conclusion
As the cyber threat landscape intensifies, success will come not from full autonomy but from thoughtful augmentation. Enterprises shouldn’t aim for an autonomous SOC, but for an intelligent one. The future belongs to AI-augmented operations where machines act faster and humans think deeper.
For organisations navigating increasingly complex digital ecosystems, the focus must shift from automation for the sake of scale to augmentation for the sake of resilience. AI-augmented SOCs represent that balance – and that future.
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