Artificial Intelligence & Machine Learning,
Next-Generation Technologies & Secure Development,
Recruitment & Reskilling Strategy
But There’s No Consensus Way to Assess Levels of Skill
Recent analyses have revealed that the landscape of cybersecurity employment is evolving dramatically, with an increasing number of job vacancies now demanding substantial expertise in artificial intelligence (AI). This shift highlights the growing importance of AI skill sets in the cybersecurity sector, necessitating more than just a basic understanding of AI tools; rather, a deep knowledge and proficiency in AI technologies are becoming essential for many roles within the field.
Rob T. Lee, the Chief AI Officer and Chief of Research at the SANS Institute, provided insights into these findings, which were derived from a comprehensive analysis of job vacancies within cybersecurity. Lee indicated that the data collection was conducted using application programming interfaces from job posting sites, employing artificial intelligence agents for individual validation rather than relying on traditional web scraping methods. The analysis covered 6,193 active job vacancies over a period of just two days, from September 15 to 17, representing a real-time snapshot of the job market.
Lee asserted that this methodology yields reliable and precise data, suitable for tracking trends over time. He emphasized that while it may not give a complete picture of the total number of AI-related cybersecurity positions available, it does provide a valid framework for conducting trend analysis, as it consistently examines the same data set as it evolves.
According to the findings from SANS, employers are currently seeking candidates for four primary AI-centric roles: AI/ML Security Engineer, AI Security Architect, AI Governance and Security Risk Lead, and AI Red Team Engineer. Lee articulated that these positions are likely to become essential in virtually every organization that integrates AI into their operations, noting that cybersecurity engineering is a critical component of this integration.
Additionally, Lee highlighted four other positions that, while described in non-AI labels, are increasingly focused on AI-related responsibilities. These roles include the Agentic AI Security Engineer, AI Security Operations Center Orchestrator, AI Incident Response Orchestrator, and AI Threat Intelligence Analyst. An orchestrator, as described, is a coder tasked with managing a fleet of AI agents, which are specialized AI programs capable of interacting with corporate applications and executing various tasks. Lee predicts that these orchestrator roles will become more prevalent in the coming year as organizations adapt their workflows to incorporate AI agents into their cybersecurity strategies.
The analysis identified a total of 1,654 vacancies specifically tied to AI, determined through a thorough examination of job posting content and the skills sought after, rather than merely the job titles. This data revealed that major corporations such as JP Morgan Chase, Leidos, Amazon, Mastercard, and PepsiCo are among the hiring entities. Lee noted that the demand for these skilled professionals doesn’t just stem from traditional cybersecurity firms; it’s also coming from diverse sectors including energy, healthcare, and oil and gas.
Reflecting on the current job landscape, Lee expressed optimism about the recognition of new roles emerging within cybersecurity focused on AI. He likened the specialized skills required in this domain to those needed for industrial control systems (ICS) and operational technology (OT), which also demand specific knowledge and expertise.
To further support this analysis, SANS has made the collected data publicly accessible online, with ongoing commitments to regular updates. Lee noted that the prevailing trends indicate a divergence from the common narrative suggesting that AI would fully replace human roles in cybersecurity. Instead, he argued, AI is poised to augment human capabilities, allowing professionals to operate more efficiently.
Lee utilized an apt analogy to explain the potential of AI in cybersecurity, stating, “The analogy I like to use is, you could swim through a pool, but if you put flippers on, you’re going to be able to swim it faster. That’s what AI is going to enable you to do, but you’re still hiring a swimmer.” This perspective encapsulates the concept that while AI can enhance productivity and efficiency, human oversight and expertise remain indispensable.
Despite the rising demand for AI-focused roles, Lee also mentioned that the anticipated decline in entry-level cybersecurity positions due to AI automation has not yet materialized, with entry-level job availability remaining stable. This observation suggests that the cybersecurity job market continues to present opportunities even as it evolves.
Contrastingly, a different report released by CyberSN indicated a notable decline in overall cybersecurity job postings, which had dropped to a four-year low of 235,786 openings between January and September 2026. This decline represented a 26% decrease compared to the same timeframe in the previous year. However, within this context, demand for AI Security Engineers surged dramatically, increasing by 268%, and requirements for Cyber Data Scientists more than doubled, up 203% over the previous year.
While CyberSN did not provide salary data, Lee emphasized the importance of various factors affecting compensation, particularly for in-office roles, suggesting a competitive environment for filling these AI-centric positions. Many roles reported starting salaries of $120,000 or higher, primarily targeting senior or expert-level candidates.
However, the rising demand for AI expertise has brought to light a significant issue: the lack of consensus regarding what constitutes true expertise in AI within the cybersecurity community. JC Vega, a cybersecurity strategist and retired U.S. Army colonel, voiced the complexities surrounding this topic. “I put a call out to my community… How could I establish my expertise in AI?” he shared, illustrating the diverse opinions on the criteria for being deemed proficient in AI.
Despite the emergence of AI frameworks and competency standards established by organizations like NIST, Vega argued that there is still confusion regarding the specific knowledge, skills, and practical experience necessary to secure AI systems and defend against AI-enabled threats. While training organizations such as ISACA and GIAC SANS offer certifications, these represent just the starting point for building a more comprehensive understanding of AI in the cybersecurity realm.
As AI literacy begins to approach a baseline expectation for cybersecurity professionals, Vega recalled a time when fluency in Microsoft Office tools was simply assumed rather than explicitly stated on resumes. The industry must collectively establish standards for what it means to be proficient in AI as cybersecurity continues to adapt and evolve in this technology-driven landscape.