Artificial intelligence became impossible to ignore in 2025. From boardrooms and developer workflows to classrooms and courtrooms, AI changed how work was done and created new types of risk. While the past year focused on experimenting and speeding things up, cybersecurity experts believe that 2026 will fundamentally change the security landscape.
Security teams, already stretched thin by ransomware, supply chain attacks, and regulatory pressure, now confront added complexity: AI systems that can act, make decisions, and scale much faster than humans. Generative AI has already made cybercrime easier. The next phase, known as agentic AI, is likely to enhance both offensive and defensive capabilities.
According to security leaders, 2026 will feature sharp contrasts. AI will give defenders remarkable visibility and automation. At the same time, it will also allow attackers to move more quickly, hide better, and strike harder. Organizations that do not adjust may face exposure not only to criminals but also to their own AI systems making costly errors.
Here’s how experts think AI will influence the cybersecurity landscape in 2026.
Defenders Ready to Regain Ground from Attackers
For much of the AI boom, cybercriminals seemed to be the quickest to weaponize new technology. Phishing campaigns became more convincing, malware became more adaptable, and reconnaissance became easier to scale. However, security leaders believe that 2026 might be a turning point.
Defenders have a crucial advantage that attackers usually do not have: visibility across the entire ecosystem.
Security vendors and managed service providers investigate thousands or even millions of intrusion attempts across various industries and regions. AI systems trained on this collective intelligence can detect emerging attack patterns long before a specific organization is targeted.
Instead of merely reacting to breaches, AI-powered defense platforms can start anticipating them. By connecting signals across networks, endpoints, identities, and cloud infrastructure, defenders can identify early tactics and neutralize threats before they grow.
At the same time, AI improves the detection of anomalies hidden within large datasets—something human analysts cannot do at scale. Pattern recognition, behavior analysis, and real-time correlation are becoming essential capabilities rather than rare features.
The promise for 2026 is not perfect security but a shift from constantly fighting fires to building proactive resilience.
Agentic AI Changes DevSecOps from the Ground Up
If 2025 was when AI became a coding assistant, 2026 is set to be the year it evolves into an autonomous participant in development and security workflows.
Agentic AI, systems capable of planning, reasoning, and acting across tools, is moving from experimentation into real-world applications. In DevSecOps, this means AI will not only identify vulnerabilities but also take action to fix them.
In practice, this could involve an AI agent detecting a misconfiguration, creating a ticket, altering code, running tests, and submitting a fix—all without human input. Early versions of this capability already exist in controlled environments, and adoption is expected to increase quickly.
For security teams overwhelmed by technical debt, this automation could be a game-changer. Low-level issues that once took hours of manual work may now be resolved in minutes. This would free experts to focus on larger architectural risks and strategic choices.
However, this shift also creates new dependencies. As AI agents take on more responsibilities, organizations will need robust guidelines to ensure these systems act safely, transparently, and predictably.
Shadow AI Becomes a Hidden Risk for Enterprises
While official AI tools grow in number, a bigger challenge is emerging from the shadows.
Across organizations, employees are quietly adopting AI tools without official approval. Some create private models, while others integrate third-party AI services into their workflows on their own. This creates a growing “Shadow AI” ecosystem that security teams often cannot monitor.
The risks are considerable. Sensitive data may be entering unauthorized systems with unclear retention policies. Intellectual property could be at risk. Compliance requirements might be violated without anyone noticing.
Shadow AI is particularly dangerous due to its invisibility. Unlike past instances of shadow IT, AI systems can blend seamlessly into everyday operations.
Experts warn that by 2026, Shadow AI will represent a significant unmonitored vulnerability within organizations. The focus will shift to detection rather than prohibition.
Successful organizations will do three things:
- Create clear AI usage policies
- Educate employees on safe and unsafe practices
- Offer approved, secure alternatives that don’t hinder productivity
Simply banning tools rarely works, experts say. When official solutions feel restrictive, employees will find workarounds.
A Major AI-Driven Cyberattack Could Trigger Security Spending
Despite growing concerns, much of today’s spending on AI security is driven by compliance rather than actual threats. That may change suddenly in 2026.
Many security leaders predict the first major AI-driven cyberattack that causes widespread financial damage will happen within the next year. When it does, the effect on enterprise budgets could be immediate and drastic.
History offers a precedent. Before major breaches transformed cybersecurity in the late 2000s, security investments were often linked to regulatory needs rather than real threats. After high-profile attacks made risks more tangible, budgets quickly expanded.
Experts expect a similar trend with AI. Following a significant incident, organizations may shift AI security from a “test phase” to “absolutely essential” almost overnight. Deal timelines will shorten. Executive support will increase. Tools previously seen as optional will become necessary.
Such an event would reshape the AI security market for both vendors and buyers.
When Helpful AI Agents Cause Problems
Not every future security incident will involve malicious actors.
Another emerging concern is AI systems making well-intentioned but disastrous choices. Agentic AI relies on logic and optimization, not human judgment. When instructions are unclear, the results can be catastrophic.
An AI aimed at “optimizing” a system may decide that deleting outdated components is the quickest solution. A remediation agent might shut down crucial services to eliminate risk. A code-refactoring agent could remove what it sees as inefficient functionality, even if it is essential for business.
These incidents wouldn’t be acts of defiance. They would result from AI operating according to its instructions, just not in the way intended.
As AI agents become more independent, organizations will need to reconsider oversight, limits, and accountability. Preventing harmful attacks will no longer be enough. Avoiding well-meaning disasters will become equally vital.
Attackers Will Automate Entire Campaigns Using Agentic AI
Threat actors are not standing still.
In 2025, AI was already integrated into many cybercrime processes, particularly phishing and reconnaissance. In 2026, experts expect attackers to advance further by automating entire campaigns with agentic AI.
These systems could scout for vulnerabilities, adjust tactics in real-time, and orchestrate multi-stage intrusions without constant human supervision. Phishing attacks may become more personalized, persistent, and adaptable. Malware could evolve dynamically to evade detection.
This shift will move crime from being AI-assisted to AI-driven operations.
For defenders, this evolution means that traditional perimeter-based defenses will be less effective. Behavioral analysis, ongoing monitoring, and intent detection will be crucial for staying ahead.
Zero-Day Exploits Will Be More Common—and More Dangerous
One of the most concerning predictions for 2026 is a rise in zero-day exploits.
AI speeds up vulnerability research by automating code analysis, exploit development, and testing. Tasks that once took months of expert work can now be accomplished much faster, especially by well-funded groups.
As a result, zero-day exploits may no longer be rare, difficult weapons. They could become widely available across cloud platforms, software supply chains, and enterprise environments.
For defenders, this means that waiting for official vulnerability reports will be too slow. By the time a flaw is made public, attackers might already be well established.
The focus will shift toward detecting unusual behavior and the early stages of attack planning rather than known signatures. Advanced systems that analyze activity over time will become essential.
AI and Cybersecurity Start to Merge
Perhaps the most significant change experts foresee is not technical but cultural.
By the end of 2026, AI and cybersecurity may no longer be seen as separate fields. Security operations centers will not just use AI tools—they will work with AI as an essential part of their processes.
Agentic systems will suppress false alerts, investigate incidents, correlate exposures across different environments, suggest fixes, validate changes, and enforce controls continuously. Human analysts will focus more on oversight, strategy, and decision-making.
Some experts predict that nearly a third of security operations workflows at large companies could be handled by AI agents within a year.
This marks a shift from AI as a co-pilot to AI as a co-worker.
