How AI Is Changing Cyber Attacks and Cyber Defense

How AI Is Reshaping the Cybersecurity Landscape

AI-enabled attackers and security teams are moving faster. But speed alone doesn't determine who comes out ahead.

Attackers can rapidly launch attacks and scale effective techniques, and security teams use AI to analyze threats and speed response. Meanwhile, employees are adopting AI tools faster than policies can keep up.

The challenge is understanding where the risks lie to address the weaknesses that matter most. Then it’s making sure someone can respond when a threat gets through.

AI Is Giving Attackers More Ways to Find Weaknesses

The 2026 SANS AI Survey found that 95% of organizations believed threat actors were already using AI. 78% reported confirmed or suspected AI-enabled attacks. As attackers quickly scale familiar and new attacks, they overwhelm security teams.

Take social engineering. Attackers use AI to create convincing messages tailored to a person's role, imitate familiar writing styles, and generate fraudulent content that looks legitimate.

AI also changes how attackers find weaknesses in software. Gartner ranked AI-driven discovery of cyber vulnerabilities as the biggest risk around the world. AI finds vulnerabilities quickly, so organizations have less time to address them. This leaves openings for attackers to exploit.

The takeaway isn't that every cyberattack now involves AI. Attackers can work faster, reducing the time defenders have to react.

Uncontrolled AI Adoption Creates New Security Risks

Attackers aren't the only ones experimenting with AI. Businesses have introduced AI-powered applications and agents into their workflows. Employees use AI tools to analyze information, automate tasks, and solve everyday problems. It's a pattern worth examining closely — AI adoption is outpacing security governance, much like what happened during the early rush to the cloud.

Verizon’s 2026 Data Breach Investigations report shows that 67% of employees use personal accounts on their work devices to access AI services. In fact, shadow AI was the third most common non-malicious insider action detected–-up fourfold from the previous year.

Whether the tools are approved or unsanctioned, their use creates problems for security teams. How can they protect tools and data when they don't clearly understand how AI is being used?

Shadow AI and Agentic Risks Inside Your Organization

The risks extend beyond employees entering sensitive information into public AI tools. AI agents can interact with business applications, retrieve data, and act through APIs. An agent might be granted excessive permissions. Or it might be integrated into a workflow without proper safeguards. Either situation could expose sensitive data or allow the agent to take unintended actions.

In ISACA's 2026 AI Pulse Poll, only 38% of respondents are confident in their board's understanding of AI risks. They also doubt the board's ability to manage risks effectively. Just 45% say AI risks are an immediate priority.

To secure agentic AI, security teams need to see which AI tools and agents are used. They also need to know what data these tools can access and which systems they connect with. Clear policies, access controls, and shared ownership help IT, security, and business leaders agree on acceptable risk. This way, they can build security into AI deployments from the start.

AI Strengthens Cyber Defense, but Critical Gaps Persist

The 2026 SANS AI Survey also found that active AI use in cybersecurity rose from 50% to 78% in one year. AI enables security teams to analyze large volumes of activity. By correlating alerts, it helps them investigate potential threats effectively. It also helps teams find weaknesses before attackers do.

Traditional methods, like signatures and known indicators of compromise, are still useful for spotting familiar threats. AI-assisted threat hunting can reveal suspicious activity that automated alerts miss. Behavioral analysis sets baselines for normal endpoint and network activity. It also flags deviations for further investigation. For example, it can spot an app that talks to unknown systems or acts differently than usual.

But adding AI to a security workflow doesn't always lead to better results. AI can sometimes flag safe actions as threats or overlook real dangers. In the 2026 SANS AI Survey, 63% of respondents noted major gaps in AI threat detection and response. This is an increase from 45% in 2025. Closing those gaps requires shared ownership of AI outcomes across security teams — not just better tooling.

Find and Fix the Weaknesses That Matter Most

AI is accelerating vulnerability discovery for both attackers and defenders. To stay ahead, organizations need to understand which vulnerabilities pose the greatest risk and address them before attackers can exploit them.

Start with visibility. Teams need an accurate inventory of all systems, applications, and other assets. From there, a practical vulnerability management program should:

• Validate findings. Decide whether vulnerabilities affect the organization's environment.
• Prioritize by risk. Consider exploitability, exposure, asset criticality, and potential business impact instead of treating every finding as equally urgent.
• Remediate the highest-priority issues. Assign responsibility, set deadlines, and address the weaknesses that pose the greatest risk.
• Verify the fix. Confirm that remediation worked and reduced exposure.

AI can help speed up discovery and assessment. It can't replace the process needed to turn findings into meaningful risk reduction.

The same principle applies to AI systems. Unapproved tools and excessive permissions can create problems. Exposed data and unsecured integrations add to these issues. Regular asset inventories and security reviews may miss them. Organizations must identify and assess these systems as part of their security program. For a closer look at how organizations can approach AI deployment security, it helps to understand the specific risks these systems introduce and the controls needed to manage them.

Threat Detection Requires Response Capabilities to Match

Finding and fixing known vulnerabilities helps reduce risk, but it can't guarantee that every threat will be prevented. When a security tool flags suspicious activity, teams must figure out what it means and how to respond.

AI correlates events and speeds up investigations. Clear procedures and ongoing monitoring help teams contain incidents, recover affected systems, and address the root cause.

For many organizations, maintaining these capabilities around the clock is difficult. Building an internal security operations center requires more than buying the right tools. However, skilled security professionals are in high demand.

Why Managed Security Services Fill the Expertise Gap

The Cloud Security Alliance's 2026 research found that 85% of surveyed security leaders preferred managed security service providers (MSSPs) for security operations center services rather than relying solely on in-house teams. A managed security partner can provide ongoing monitoring, investigate potential threats, and support incident response. The right model complements internal teams and adds expertise when needed.

Build a Defense That Can Keep Up

AI is changing both sides of cybersecurity. Attackers can use it to discover weaknesses and scale their efforts. Defenders can use it to analyze threats and improve security operations.

Organizations can gain an edge with a better view across their environments and by governing AI use. Complement this by prioritizing vulnerabilities by risk and having the expertise to investigate and respond. That requires using security tools and processes that keep up with the pace of emerging threats.

How SecureOps Helps You Stay Ahead of AI-Driven Threats

SecureOps helps organizations strengthen their security posture through managed security services, continuous monitoring, incident response, and risk-based vulnerability management. By combining security technology with experienced professionals, organizations can turn threat detection into practical action.