{"id":120176,"date":"2026-10-29T14:45:06","date_gmt":"2026-10-29T09:15:06","guid":{"rendered":"https:\/\/www.mygreatlearning.com\/blog\/cybersecurity-to-ai-security-roles\/"},"modified":"2026-10-29T15:09:35","modified_gmt":"2026-10-29T09:39:35","slug":"cybersecurity-to-ai-security-roles","status":"publish","type":"post","link":"https:\/\/www.mygreatlearning.com\/blog\/cybersecurity-to-ai-security-roles\/","title":{"rendered":"From Cybersecurity to AI Security:\u00a0 Emerging Roles and the Skills Behind Them"},"content":{"rendered":"\n
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TL;DR<\/strong><\/p>\n\n\n\n

AI is changing cybersecurity by introducing new risks across AI models, agents, RAG systems, and automated workflows. This shift is creating eight emerging AI security specializations across engineering, offensive security, threat intelligence, security operations, and governance. Professionals in cybersecurity, cloud, software development, and risk management already have transferable skills. Choosing the right career path depends on your existing expertise, coding proficiency, and the AI security skills you want to develop.<\/p>\n<\/blockquote>\n<\/div>\n\n\n\n

How AI Is Changing Cybersecurity and Creating New Career Paths<\/strong><\/h2>\n\n\n\n

AI is changing cybersecurity in two distinct ways: attackers are using AI to scale malicious activities, and organizations are deploying AI systems that need protection. According to IBM's Cost of a Data Breach Report 2026<\/a>, one in four malicious breaches examined in its research was AI-enabled. These breaches cost organizations an average of $6 million.<\/p>\n\n\n\n

At the same time, AI models, agents, and automated workflows introduce security considerations involving sensitive data, system permissions, and interactions with external tools. <\/p>\n\n\n\n

For professionals in cybersecurity, cloud engineering, software development, machine learning, and risk management, understanding these risks can open new areas of specialization.<\/p>\n\n\n\n

Professionals looking to strengthen their core security expertise can explore the Cybersecurity course from Johns Hopkins University<\/a>, which covers network and infrastructure security, cloud and data security, risk management, and AI-powered cyber defense.<\/p>\n\n\n\n

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<\/div>\n Johns Hopkins University<\/span>\n <\/div>\n

\n JHU Cybersecurity Certificate Course<\/a>\n <\/p>\n

Build in-demand cybersecurity skills with JHU experts. Learn AI, cloud, and network security. Hands-on projects. Flexible online format.<\/p>\n

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<\/div>\n 24 Weeks<\/span>\n <\/div>\n
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<\/div>\n Hands-on Projects<\/span>\n <\/div>\n <\/div>\n \n Get Program Details\n
<\/div>\n <\/a>\n <\/div>\n <\/div>\n\n\n\n

AI is changing what Cybersecurity teams need to protect<\/strong><\/h2>\n\n\n\n

Traditional cybersecurity focuses on securing networks, applications, endpoints, infrastructure, identities, and data. Those responsibilities remain important, but AI introduces additional systems and behaviors requiring security oversight.<\/p>\n\n\n\n

Consider an organization deploying an AI-powered customer support agent. The agent retrieves internal documents, accesses customer records, and interacts with business applications.<\/p>\n\n\n\n

Securing this environment involves more than protecting servers and APIs. Security teams must establish which information the agent is authorized to retrieve, which actions the agent is permitted to perform, and how to prevent untrusted content from manipulating its behavior.<\/p>\n\n\n\n

These concerns introduce several AI-specific security risks:<\/p>\n\n\n\n