AI is being used by over 80% of Ethical Hackers for greater Precision
AI is being used by over 80% of Ethical Hackers for greater Precision
Publish Date: 2026-01-27 10:32:00
Source Domain: www.cybersecurity-insiders.com
In recent months, much of the conversation around artificial intelligence has focused on its potential to replace human jobs and disrupt traditional roles, particularly in the cybersecurity sector.
Concerns about automation, workforce displacement, and overreliance on machines have dominated headlines. However, new research suggests a more nuanced reality. Rather than replacing ethical hackers, AI is increasingly being adopted as a powerful support tool that enhances their effectiveness, precision, and productivity.
According to a recent study conducted by Bugcrowd and published in its report “Inside the Mind of a Hacker,” more than 80% of ethical hackers now use artificial intelligence in their work. The research highlights a significant surge in AI adoption, with usage increasing by 64% compared to figures recorded in 2023. This growth reflects how AI is becoming an integral part of modern cybersecurity practices, enabling both individuals and teams to deliver higher-quality results at a faster pace.
The study, which gathered responses from over 2,000 participants, reveals that one of the primary benefits of AI lies in its ability to automate repetitive and time-consuming tasks. Ethical hackers often spend large portions of their time on routine activities such as scanning systems, sorting vulnerabilities, and validating basic findings. AI-powered tools can handle much of this groundwork, allowing hackers to free up valuable time and redirect their efforts toward more complex and strategic security challenges.
In addition to automation, AI has proven especially useful in analyzing large volumes of code. Tasks such as reviewing extensive JavaScript files or inspecting complex application logic can be tedious and error-prone when done manually. AI tools help streamline this process by quickly identifying anomalies, patterns, or potential vulnerabilities within massive codebases. This not only reduces human fatigue but also improves…
