The increasing integration of artificial intelligence into Security Operations Centers (SOCs) is reshaping the cybersecurity career landscape, particularly for entry-level positions. While AI tools are largely welcomed by current security staff for automating repetitive tasks, concerns are emerging about their potential impact on skill development and the accessibility of junior analyst roles.
A recent survey of 500 security operations professionals, all working at organizations already utilizing AI, indicates that nearly nine out of ten respondents find their work more satisfying due to AI. However, approximately a quarter of these respondents also believe AI has hindered their ability to build essential security skills. Despite this, job satisfaction remains high across both groups, with 91% of those who feel their skill development is held back reporting satisfaction, compared to 92% of those who feel AI has helped them learn. This suggests that job satisfaction alone may not be a reliable indicator of skill growth, especially for junior analysts.
The survey found that only one percent of respondents expect the analyst career path to remain unchanged. The most common expectation, held by nearly half of respondents, is that entry-level jobs will become more difficult to secure. This difficulty is anticipated either through increased demands for prior knowledge and experience or a reduction in opportunities to gain that experience on the job. A significant portion of respondents foresee new roles emerging that focus on overseeing, verifying, and coordinating AI systems. These trends collectively suggest a squeeze on traditional entry-level positions, as the repetitive casework that historically served as foundational training for new hires is increasingly handled by AI.
Analysts report spending more of their day reviewing AI-generated output and express confidence in their ability to identify incorrect or incomplete recommendations, with over nine in ten believing they could do so. They also indicate a clear understanding of when to intervene, most often trusting their own judgment when AI recommendations conflict with available evidence or when acting on an AI suggestion could disrupt business operations or critical systems. Few respondents reported simply accepting AI outputs without scrutiny. The primary concern among analysts regarding expanded AI use is the risk of over-reliance on AI recommendations, closely followed by the potential for exposing sensitive data. This highlights a perceived risk that reduced direct engagement with problem-solving could diminish an analyst's ability to spot AI errors.
Differences in perspective were observed between leaders and practitioners. Three-quarters of leaders described AI as extensively deployed across multiple security functions, a sentiment shared by only about half of practitioners. Leaders also reported higher rates of role redesign, increased capacity, and greater satisfaction. These groups were drawn from different organizations, so the discrepancy does not necessarily indicate a misreading of teams by leaders, but it suggests that those setting investment priorities may perceive the AI transition as further along than those directly involved in daily operations. Larger organizations, with 10,000 or more employees, also reported a significantly smaller increase in satisfaction compared to mid-sized firms.
The formal redesign of job roles appears to correlate with higher analyst satisfaction. Approximately four out of ten respondents reported that their organizations formally redefined analyst roles to focus on higher-value work, while a similar proportion noted that duties shifted informally without official changes. Among those whose roles were formally redesigned, 71% reported a significant increase in satisfaction due compared to 29% in organizations without formal changes. While the survey cannot definitively establish causation, formal redesigns provide clear definitions of new responsibilities, performance metrics, and career progression paths, offering a structured way to track skill development independently of job satisfaction.
