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How do you move from computers and IT into cybersecurity—and eventually AI security? Treat it as a progression of choices, not a single ladder: identify what your IT experience has taught you, choose a cybersecurity work direction that fits, and build the knowledge needed for that work. AI security then adds risks tied to AI systems, their data, and their lifecycle.
Start by recognizing what your IT experience can carry forward
Working with computers and IT can provide a useful starting point, but the experience varies by role. Take inventory of what you have actually done: troubleshooting systems, supporting users, configuring access, working with networks or software, handling data, or helping keep operations running.
For each area, note a concrete example and what you learned. For instance, resolving a recurring access issue may have taught you how permissions affect users and systems. That experience can help you understand security work, while also revealing what you still need to learn. Do not assume that every IT job provides the same exposure—or that time in IT alone qualifies someone for a particular security role.
Choose a cybersecurity direction by looking at the work
Cybersecurity includes different kinds of work, with different tasks and skill profiles. A job title alone may not tell you what the day-to-day work involves. NIST’s NICE Framework describes cybersecurity work through work roles and their tasks, knowledge, and skills; a work role is not necessarily the same thing as a job title, and the framework does not prescribe a single career ladder.
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Use the framework to explore the activities that interest you and compare them with what you already know. CISA’s Career Pathways Roadmap, based on NICE Framework Components version 2.0.0 and last published July 29, 2025, can help you examine shared skillsets, mobility between selected roles, and possible stepping-stone roles.
- What tasks would you like to do regularly?
- Which tasks can you already demonstrate through work, study, or practice?
- What knowledge or skills appear in the target role that you have not yet developed?
- Does the target role or a prospective employer ask for a particular credential?
Build skills for your chosen role, not a universal checklist
Once you have a direction in mind, use its tasks and skill requirements to decide what to study and practice. NIST’s Cybersecurity Career Pathway Resources collects education, training, and certification resources. It includes options such as CompTIA Security+ and SANS training, but these are possibilities—not a mandatory sequence or universal endorsement.
Compare routes by the work they prepare you to do, how much they build on your existing skills, the gaps they address, and their learning format. Time and cost depend on the specific offering and your circumstances. A credential may be useful where a target role requests it; the available guidance does not establish one credential as best for everyone.
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Move into AI security by extending core security practice
AI security is connected to foundational cybersecurity, not separate from it. NIST identifies overlapping concerns involving confidentiality, integrity, availability, data, and the software and hardware underlying AI systems. Understanding how those components are protected gives you a base for examining risks introduced by AI.
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From there, expand your focus to how AI risks arise and change across design, development, use, and evaluation. NIST’s AI Risk Management Framework (AI RMF) provides voluntary risk-management guidance. NIST released AI RMF 1.0 on January 26, 2023, and says the framework is being revised. Its Generative AI Profile, published July 26, 2024 and updated April 8, 2026, is a cross-sector companion with suggested actions for managing generative AI risks.
Another NIST document, IR 8596, the Cybersecurity Framework Profile for Artificial Intelligence (Cyber AI Profile), was published December 16, 2025 as an initial preliminary draft—not a final standard. Its page says the public comment period is closed and references virtual working sessions in 2026. Check the document’s status before relying on it as final guidance.
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- Write down your IT experience. Record tasks you have performed and the systems, data, or users involved. Separate demonstrated experience from areas you have only read about.
- Select a work direction to investigate. Use NICE work roles and their tasks, knowledge, and skills to identify work that interests you; consult the NICCS roadmap to examine role overlap and possible stepping stones.
- Choose learning based on the gaps. Find training, education, practice, or a credential that addresses the needs of the role you are targeting. Treat named resources as options, not required steps.
- Add AI-specific risk knowledge. After building a security foundation, learn to assess the AI system’s data, software, hardware, and operation, as well as risks across its lifecycle. Use NIST AI RMF materials as voluntary guidance and distinguish published profiles from preliminary drafts.
Your route will depend on the work you want to do and the skills you already have. Revisit current framework components and guidance as you plan, because career resources and AI risk documents can change.
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