2026: The Year Cybersecurity Becomes Autonomous

This guest article was contributed by Scott Richards, SVP of AI & Discovery and Cybersecurity at OpenText

Enterprises are under growing security pressure in 2026. Data volume continues to multiply. Identity sprawl is expanding across hybrid and cloud environments. Threat actors increasingly use AI to find new attack vectors. And at the same time, AI powered security tools have matured and can now provide context aware, automated protection rather than alarm overload. This creates new opportunities but also adds to the pressure to get it right.

The new year marks a turning point. Security will become less about manual intervention and more about seamless risk orchestration. Companies that lean into automation, identity first protection, unified platforms and proactive risk management will move ahead. Others risk falling behind as complexity increases sharply.

Here are four predictions for how this shift will unfold.

AI Detection and Proactive Data Posture Take the Lead

Security teams struggle to keep up with millions of alerts each day. False positives waste time and increase alert fatigue. This year, many organizations will turn to AI driven threat detection and data security posture management.

These tools quiet the noise and surface only real risks across structured, unstructured and cloud data. Early adopters are already seeing three to five times return on investment within eighteen months. This is also helping to reduce audit preparation time, attack surfaces, and give smaller teams the ability to operate with the precision of much larger ones.

As such, organizations will reduce breach risks, lower operational load, increase response speed, and enable their security teams to focus on what matters most.

Identity Becomes the Center of Security

As hybrid environments grow, credential sprawl grows with them. More human and machine identities appear, and attackers target identity weakness with increasing success. The most important security investment this year will be AI driven identity threat detection and response to combat this challenge.

These tools uncover hidden identities, surface risky privileges and identify unusual access activity. They help block the most common breach vectors. Organizations will see success through fewer credential-based incidents, faster response and reduced workload for analysts.

Identity management will become the foundation of supporting the greater security program.

Automation Expands Across Discovery and AppSec

Routine discovery, classification and low risk remediation will no longer be manual tasks. Automated tools will handle most of this work by the end of next year. On the application side, AI agents will scan new code, highlight vulnerabilities, generate patches, test them and submit pull requests for human review.

However, humans will continue to play a critical role in this process. They will review exceptions, make judgment calls and approve agentic decisions. This hybrid model will bring shorter remediation cycles, fewer open vulnerabilities and a high percentage of routine work completed without human intervention.

People will remain central to security, but the work will shift from tedious triage to thoughtful oversight.

Unified Platforms Replace Point Tools

AI performs best when it can access broad and consistent context. When data, identity, applications and threat signals are separated across tools, automation remains shallow and unreliable. For this reason, organizations will continue to consolidate solutions. They will replace point tools with unified platforms that bring identity, data security, application security and threat detection into a connected system.

A unified platform lightens administrative burden, strengthens compliance and cuts down on dashboard complexity. Most importantly, it gives AI the shared context it needs to make reliable and safe decisions. In this way, security management will become an integrated discipline rather than a set of disconnected tools.

Leaders Will Move First

Security leaders who invest in AI for detection, identity protection, discovery and application security, along with platform consolidation, will shift from reacting to threats to proactive risk management at scale.

And the organizations that begin this transition now will be the ones that lead this year and beyond.