30 Jan Cybersecurity Predictions for 2026

– Subo Guha, Senior Vice President, Product Management, Stellar Cyber

San Jose, Calif. – Jan. 30, 2026

Agentic AI as applied to the cybersecurity market is expected to grow from $738.2 million in 2024 to an estimated $1.73 billion in 2034, reflecting a CAGR of 39.70%. This kind of massive transformation will happen gradually, as 59% of CISOs say their agentic AI initiatives are still a “work in progress.” 

Beyond that, what’s next? Here are six predictions for the future of the AI-powered security operations center, starting in 2026 and continuing through 2028.

1. Rise of Human-Augmented SOCs

In the coming year, the enterprise security landscape will be defined by the transition from a primarily human-led response to a human-augmented, AI-driven security operations center (SOC). A human-augmented SOC is built on the foundation of agentic AI tools, designed to address one of the most significant pain points facing human security analysts today: security alert fatigue. Throughout 2026, security teams will transition from costly, inefficient manual triage to human-supervised AI systems. AI agents in the SOC will monitor and detect security anomalies, flag and investigate them. In the human-augmented SOC, AI handles repetitive, time-intensive tasks, while humans focus on high-value decisions. This model only works properly if the AI has a balanced data foundation. Extracting data from multiple sources, such as SIEM logs, network traffic, and endpoint activity, is essential to a well-trained AI assistant in the SOC. It gives AI a three-dimensional view into the environment and eliminates any potential bias towards one source.

2. Foundational AI Integration for Context and Correlation

There’s been a lot of talk in 2025 about Agentic AI vs. other types of AI. However, in 2026, multiple types of AI will come together to achieve specific goals. Machine learning, correlation AI, and agentic AI systems will become the standard for performing context-aware triage and correlation. The primary role of these unified, multiple layers of AI will be to enrich data across diverse telemetry sources (endpoints, networks, and cloud) and build a clear picture of attack patterns. This will take a great deal of the heavy lifting off the human security analysts, who currently spend hours on investigation. With more comprehensive data and context around security alerts and other incidents, human analysts and AI agents alike will be able to make better informed decisions about what steps to take to thwart potential attacks. Agentic triage agents will continuously evaluate new alerts as they arrive in the SOC, not just on rule severity, but on context: entity criticality, blast radius, past behavior, current campaigns, and ATT&CK technique combinations. Using context-based criteria, low context alerts about low-value assets may get auto-closed after quick checks. High-risk combinations, such as a privileged account signing in from a new geography while creating new cloud keys, will receive instant promotion and a full investigation.

3. Deeper Integration of Open XDR Platforms into Cloud-Native Ecosystems

In 2026, Open XDR platforms will achieve deeper integration into cloud-native environments, helping the autonomous SOC to gain greater visibility across the attack surface, working with any endpoint system. Security teams are already realizing that proprietary, closed XDR is too restrictive and requires vendor lock-in. The Open XDR approach utilizes adaptive connectors (APIs) and AI-driven enrichment to unify data from hybrid cloud architectures, establishing the necessary data foundation for automated defense. This will allow enterprises and SMEs to maximize the value of existing tools and facilitate greater interoperability. This “better together” concept will require more security vendors to cooperate rather than compete. 

4. Security Analysts as AI Supervisors

Here’s the truth about agentic AI: you can’t automate everything unless the automation is learning from someone. In the case of cybersecurity, that “someone” is still the analyst. And their job is not just to babysit the machine, but to influence it in meaningful ways. In the autonomous SOC of the future, the professional role of the security analyst will evolve from an incident responder to an AI supervisor. Analysts’ core function will be to oversee autonomous actions, validate automated responses (such as quarantines), tune AI rules, and rely on human judgment for final escalation decisions. In 2026, this will become the hot new job role in security operations.

5. Human-Augmented SOC Shifts to an Autonomous, Intelligent System

What’s beyond 2026? AI, through LLMs, behavioral analysis, and autonomous agent design, bring the capacity to remove the human operator from the loop entirely. Today’s AI-based platforms already outperform humans in detecting and classifying malicious activity. The mistake is assuming that SOC processing tasks will always require a human interface. Autonomous decision-making is already happening at the endpoint. The SOC is next. Fighting this trend is a losing game. But, there will be massive opportunities for humans to participate – but at a higher-level context, including governance, curation, and monitoring of progress in day-to-day operations. They will select the vendors, swap out automated tools, diagnose problems, and generally ensure that the defensive AI is working as expected. 

The SOC will fundamentally change from a collection of disconnected, siloed tools into a single, cohesive, intelligent system supervised by human experts. While not yet fully autonomous, this system will actively learn, experiment, and establish the trust mechanisms required for future autonomous “bot versus bot” defense capabilities. By the end of 2026, the SOC will no longer be a collection of tools; it will be an intelligent system supervised by skilled humans. It won’t yet fight back autonomously, but it will be able to learn and experiment, much like the early phases of training a defensive AI to distinguish between friends, foes, and false positives. 

6. Next-Generation Honeypots

By 2028, the security ecosystem will be fully adaptive and autonomous. AI-driven agents will defend digital assets at machine speed without waiting for human approval. This is the phase where we’ll see “defender” bots begin fighting “attacker” bots. Attackers are already using AI to create highly convincing deepfakes. Within the next three years, defenders will be able to fight fire with fire. Static honeypots will be replaced in the autonomous SOC by dynamic, data-driven decoys and digital twins. These intelligent decoys will use reinforcement learning to mimic user behavior and actively learn threat intent, providing analysts with proactive, real-time insights into adversary strategies.

Prepare Now

The evolution of the SOC from a human-centric response team to a human-augmented and eventually autonomous, intelligent system is not just a technological shift but a strategic imperative. The predictions outlined here-from the rise of human-augmented SOCs and foundational AI integration to the deep embedding of Open XDR and the emergence of next-generation honeypots-all point toward a cybersecurity environment defined by speed, context, and coordinated action. By 2028, the enterprise defense posture will rely heavily on autonomous learning systems that transform the role of the security analyst into a high-level supervisor, ensuring the integrity and effectiveness of the defensive AI. For organizations planning their strategy today, the focus must be on building the unified data foundation and embracing the Open XDR architecture necessary to support these powerful, contextual, and ultimately autonomous defensive capabilities. The future of security is intelligent, and the time to adapt is now.

– Subo Guha serves as Senior Vice President of Product Management at Stellar Cyber, where he spearheads the development of their award-winning AI-driven Open XDR solutions. With more than 25 years of experience, Subo has held senior leadership roles at industry-leading companies like SolarWinds, Dell, N-able, and CA Technologies.

About Stellar Cyber

Stellar Cyber’s Open XDR Platform delivers comprehensive, unified security without complexity, empowering lean security teams of any skill level to secure their environments successfully. With Stellar Cyber, organizations reduce risk with early and precise identification and remediation of threats while slashing costs, retaining investments in existing tools, and improving analyst productivity, delivering an 8X improvement in MTTD and a 20X improvement in MTTR. The company is based in Silicon Valley. For more information, visit https://stellarcyber.ai.