Will AI Take Over Cybersecurity?

AI in cybersecurity is transforming how we defend against threats—but it’s also creating new risks. According to IBM’s 2024 Cost of a Data Breach Report, companies that use AI and automation extensively saved an average of $2.22 million per breach compared to those that didn’t. These organizations also responded to incidents much faster, showing how AI and machine learning in cybersecurity are improving detection and reducing damage.

But cybercriminals are also getting smarter. A 2024 Harvard Business Review study found that 60% of people clicked on AI-generated phishing emails, showing that attackers now use AI to launch more convincing and successful scams.

These two trends raise a critical question: Is AI for cybersecurity the ultimate defense—or could it become part of the problem?

In this blog, we’ll explore how AI and cybersecurity are evolving together, the benefits of AI in cybersecurity, its limitations, and whether AI will replace or complement human cybersecurity professionals.

The Role of AI in Cybersecurity

AI in cybersecurity helps detect threats that are hard for humans to catch. It looks at things like login activity, network traffic, and user behavior to spot unusual actions—such as someone accessing files they normally wouldn’t. AI also helps reduce alert fatigue by sorting through thousands of security alerts and showing analysts which ones matter most.

In day-to-day operations, AI is used to stop phishing emails, detect malware, and even predict which users are most at risk. By using AI and ML in cybersecurity, companies can act faster, make better decisions, and stay ahead of attacks.

To see how AI boosts employee efficiency in managing human cyber risk, check out Keepnet’s article: Harnessing AI to Increase Full-Time Employees' Efficiency in Managing Human Cyber Risk.

AI for Defensive Security

AI is transforming cybersecurity defense by making it more targeted, adaptive, and behavior-driven. Instead of using generic training or simulations, AI analyzes each user’s role, behavior, and past interactions to deliver security actions that are personalized and effective.

For example, Keepnet’s Phishing Simulator uses AI to launch hyper-personalized phishing campaigns that reflect the threats each employee is most likely to face—based on their department, seniority, or history with past simulations. This realistic, tailored approach reveals genuine vulnerabilities and helps build long-term awareness.

Keepnet Human Risk Management Platform adds another layer by assigning each user a risk score through continuous behavioral analysis. This lets security teams quickly identify who’s at higher risk and intervene before a real breach occurs.

Meanwhile, Keepnet’s Adaptive Security Awareness Training personalizes learning content in real time. If an employee fails a smishing simulation, the platform automatically shifts focus to mobile-based threats. This AI-driven, context-aware training boosts engagement and helps employees build stronger, threat-specific defenses.

AI for Offensive Cyber Threats

​​AI is also being weaponized by attackers to make cyber threats more convincing and harder to detect. Cybercriminals now use AI to generate deepfake audio for vishing attacks, craft highly targeted spear phishing emails, and develop polymorphic malware that constantly changes to bypass traditional security tools.

As these tactics become more advanced and automated, organizations need to test their defenses more thoroughly. Tools like Keepnet’s Smishing Simulator and Quishing Simulator help evaluate how well employees can spot AI-driven threats delivered through SMS or QR codes.

A recent case in Hong Kong showed how dangerous AI-powered scams have become. A finance employee at a multinational company was tricked into transferring $25 million after joining a video call where deepfake versions of the company’s CFO and colleagues appeared. The scammers used AI to mimic their faces and voices so convincingly that the employee believed the meeting was real and approved the transaction. (CNN)

Challenges and Limitations of AI in Cybersecurity

While cyber security and AI bring significant advantages, they also come with critical limitations. AI systems can only be as effective as the data they are trained on—and poor data can lead to inaccurate or biased outcomes. Additionally, the lack of transparency in how AI makes those decisions can create trust and accountability issues in sensitive security environments.

Ethical and Privacy Concerns

AI systems depend on large volumes of sensitive data—like user behavior, emails, or access logs—to function effectively. If not properly secured, this data can expose users to privacy risks.

Another major challenge is transparency. When AI flags an employee as high-risk, it’s often unclear why. This “black box” decision-making makes it hard for organizations to validate outcomes or explain them to affected users.

Bias is also a risk. If the data used to train AI models is unbalanced, the system may make unfair or inaccurate judgments—such as incorrectly targeting certain users or missing real threats. That’s why ethical design, clear auditing, and human oversight must be built into every AI-based cybersecurity strategy.

Will AI Replace Human Cybersecurity Experts?

As AI for cybersecurity becomes more advanced, many wonder if it will eventually replace human experts. The short answer: no. AI is a powerful tool, but it still needs people to guide and manage it.

The Need for Human Oversight

AI can detect unusual activity—like a login from a new location—but it doesn’t understand context. A human analyst can tell whether that login is a real threat or just an employee working while traveling.

Even advanced tools like Callback Phishing and Incident Responder still require human input to set rules, investigate alerts, and take appropriate action. Without oversight, AI can misjudge threats or overlook subtle signs of an attack. AI supports the work of cybersecurity teams, but it cannot replace human judgment and expertise.

Collaboration Between AI and Human Experts

The most effective cybersecurity strategies combine human expertise with AI capabilities. Experts train and fine-tune AI systems, define ethical boundaries, and make final decisions. AI, in turn, handles large-scale tasks—like scanning logs, detecting patterns, and flagging suspicious behavior in real time.

This collaboration is especially valuable in areas like Threat Intelligence and Threat Sharing, where AI can quickly process vast amounts of data to uncover emerging threats, while analysts use those insights to plan targeted responses and strengthen defenses.

The Future of AI in Cybersecurity

The role of AI in cybersecurity is expanding rapidly across all areas of defense. It’s no longer just about detection—AI is helping organizations predict, prevent, and adapt to evolving threats. As adoption grows, new trends are reshaping how businesses secure their systems and train their people.

Emerging Trends and Innovations

In 2025, AI in cybersecurity is shifting from passive detection to proactive defense. Key trends include:

• Predictive analytics that use AI to forecast attacks before they happen by identifying patterns in large datasets. This allows organizations to stop threats early instead of just reacting afterward.
• AI-powered deception technologies that create realistic traps—like fake credentials or decoy systems—to confuse attackers, gather intelligence, and protect real assets. These tools adapt in real time, making it harder for hackers to tell what’s real.
• Adaptive phishing simulations that mirror real-world attack techniques. These simulations are personalized based on employee behavior, helping organizations test and improve their human defenses continuously.

A major innovation gaining traction is Agentic AI—AI systems that can take initiative, make decisions based on context, and work independently while staying aligned with human oversight. For a more detailed look, check Keepnet’s article: Agentic AI in Cybersecurity: The Next Frontier for Human-Centric Defense.

AI is also shaping how organizations design and deliver employee training. It personalizes content based on real-time threats and user behavior, making learning more relevant and effective. To learn more, read How AI Shapes Security Awareness Training Content.

The Balance Between AI and Human Control

AI cybersecurity jobs are not going away—they're evolving. Instead of performing routine tasks, professionals will focus on supervising AI systems, fine-tuning their performance, and ensuring they operate ethically and responsibly.

Organizations that balance automation with human oversight will be better prepared for future threats. Success depends on combining intelligent technologies with skilled experts who can guide, manage, and make critical security decisions when AI alone isn’t enough.