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But in solving this problem, it may be creating another one that could have a long-lasting impact.Log review. Alert triage. Drift detection. Basic investigation. These tasks were how generations of defenders traditionally learned the cybersecurity trade — how they built intuition, pattern recognition, and the "muscle memory" that senior leaders rely on during times of crisis. Now that AI is absorbing the grind, some say organizations risk accelerating efficiency at the cost of developing foundational expertise.The result is an emerging paradox. AI is elevating today's analysts, yet it may leave tomorrow's leaders without the hands-on experience they need. As Visa CISO Subra Kumaraswamy notes, even with AI doing the repetitive work, teams still have to learn about "the art and science of defense."That raises the strategic question security leaders now face: If automation is taking over the grunt work, who trains the next generation of defenders?The Apprenticeship Layer Is ErodingThe concern isn't limited to security. In a recent 60 Minutes interview, Anthropic CEO Dario Amodei warned that AI could "wipe out” many entry-level white-collar jobs—the very roles that traditionally develop future experts.Related:Learning Sales Skills Can Make Security Professionals More Effective"We are already seeing the reduction in entry-level roles," says Deidre Diamond, founder of recruiter CyberSN. "Where we used to see five hires, we see two, maybe three. It won't be long before all of these roles are eliminated due to automation and/or AI."An ISC2 survey earlier this year found 52% of cybersecurity professionals believe AI will reduce the need for entry-level staff, but another 31% believe it will also create new types of entry- and junior-level roles to offset these reductions.While efficiency gains are welcome, Diamond warns that the risk isn't purely in foundational skills."The gaps I worry about are not just technical. They're cultural and strategic," she says.Repetitive tasks like log review and alert triage are how analysts learn what normal and abnormal look like. Without that exposure, "future leaders may lack the intuitive sense of systems, data flows, and attacker behavior patterns that help senior leaders make quick, grounded decisions in crises," Diamond says.Organizations may also see a shrinking pool of "homegrown" talent, with fewer early-career analysts gaining the kind of pattern recognition that only repetition and exposure can teach.Related:Cyber Academy Founder Champions Digital Safety for AllAI Removes the Noise, but Not the Need for JudgmentGary Brickhouse, CISO of GuidePoint Security, sees the shift differently. In his view, AI is not removing essential learning — it's accelerating it."AI clears the noise," he says. "It elevates the talent that we have. It's not replacing their talent."Instead of staring at a million logs and searching for a single anomaly, junior analysts can now see the outcomes of investigations sooner and focus on higher-value thinking early in their careers, Brickhouse adds."From an entry-level perspective, it makes their job easier in the context that it takes away the noise," he says. "Now they can look at outcomes." Brickhouse also sees AI becoming a teaching engine. "They can query AI and say, 'Hey, you identified this thing. Why did you do that?'" he says. "I think it gets them up to speed faster."Still, he cautions that the entry-level path can't simply be left to chance. "We just have to be mindful about, OK, well, what does the right career path coming in look like now?" he says.Replacing Grunt Work With Deliberate PracticeVisa has already rearchitected how early-career analysts learn, Kumaraswamy says. Its model is built around three pillars: experience, exposure, and education, with curiosity as the core trait.Related:Capture-the-Flag Competition Leads to Cybersecurity Career"I believe 'experience' has the most impact on analyst growth," he says. To create that experience, Visa gives analysts hands-on opportunities through hackathons, CISO challenges, and intentional rotations across prevention, detection, and response. The company also uses a "90/10 model," where team members spend 10% to 20% of their time outside their home domain working with subject-matter experts. The goal is cross-pollination — a detection analyst gaining a prevention perspective or a responder seeing unfamiliar technologies firsthand.Simulated cyber ranges and tabletop drills are equally important. These environments "can repeat alert triage, patching, log review, and incident response at scale," helping junior staff build capability faster, Diamond says.Kumaraswamy describes the same philosophy: mixing offense and defense so analysts see how attackers bypass controls and how defenders close gaps. After every drill or real incident, Visa's teams analyze what was missed and why, turning each event into new playbooks and targeted exercises.New Entry-Level Role: Fewer Seats, More ComplexityDiamond believes junior roles will transform. Instead of clearing noise for senior analysts, they’ll step into complexity sooner, working alongside automation from the start."'Junior' will still exist, although less of them," she says.Diamond sees three areas rising quickly:Automation oversight: Validating AI/machine learning decisions and tuning tools.Threat hunting and anomaly detection: Running higher-value investigations earlier.Cross-disciplinary work: Improving cloud, identity, governance, compliance and privacy.Preparing future defenders also means starting earlier in the pipeline, Brickhouse adds, noting that his own son completed a four-year cybersecurity academy in high school, leaving him "two steps ahead" of other new college students.AI isn't hollowing out security careers, but it is hollowing out the work that used to train them. Organizations that embrace automation without redesigning how people learn risk developing future leaders with gaps in intuition and judgment.Employers "must own efficiencies with this innovation, and they must deliberately create leadership development pathways, or they will not retain talent," Diamond says.Read more about:CISO CornerAbout the AuthorJoan GoodchildContributing Writer, Dark ReadingJoan Goodchild is a veteran journalist, editor, and writer who has been covering security for more than a decade. She has written for several publications and previously served as editor-in-chief for CSO Online.See more from Joan GoodchildMore InsightsIndustry Reports2025 State of Threat Intelligence: What it means for your cybersecurity strategyGartner Innovation Insight: AI SOC AgentsState of AI and Automation in Threat IntelligenceGuide to Network Analysis Visibility SolutionsOrganizations Require a New Approach to Handle Investigation and Response in the CloudAccess More ResearchWebinarsIdentity Security in the Agentic AI EraHow AI & Autonomous Patching Eliminate Exposure RisksSecuring the Hybrid Workforce: Challenges and SolutionsCybersecurity Outlook 2026Threat Hunting Tools & Techniques for Staying Ahead of Cyber AdversariesMore WebinarsYou May Also LikeFEATUREDCheck out the Black Hat USA Conference Guide for more coverage and intel from — and about — the show.Edge PicksApplication SecurityAI Agents in Browsers Light on Cybersecurity, Bypass ControlsAI Agents in Browsers Light on Cybersecurity, Bypass ControlsLatest Articles in The EdgeSecuring the Win: What Cybersecurity Can Learn From the PaddockNov 20, 2025|5 Min ReadSame Old Security Problems: Cyber Training Still Fails MiserablyNov 20, 2025Learning Sales Skills Can Make Security Professionals More EffectiveNov 14, 2025|4 Min ReadHow CISOs Can Best Work With CEOs and the Board: Lessons From the FieldNov 13, 2025|5 Min ReadRead More The EdgeDiscover MoreBlack HatOmdiaWorking With UsAbout UsAdvertiseReprintsJoin UsNewsletter Sign-UpFollow UsCopyright © 2025 TechTarget, Inc. d/b/a Informa TechTarget. 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Artificial intelligence is fundamentally reshaping the landscape of entry-level cybersecurity work, prompting critical questions about the development of the next generation of security professionals. This shift, driven by the automation of repetitive, low-value tasks, presents a significant paradox: while AI elevates today’s analysts, it simultaneously risks diminishing the foundational expertise crucial for future leaders. Joan Goodchild, contributing writer for Dark Reading, details this evolving situation, highlighting the erosion of traditional apprenticeship models and the potential consequences for talent pipelines.

The core of the issue lies in the historical reliance on manual, laborious tasks – log review, alert triage, and drift detection – as the primary means by which junior analysts gained crucial “muscle memory” and intuitive understanding of systems and attacker behaviors. AI’s absorption of these tasks removes the opportunities for this kind of experiential learning. As Visa CISO Subra Kumaraswamy notes, even with AI handling the routine work, teams still need to understand “the art and science of defense.” This raises a strategic question for security leaders: if automation dominates the grunt work, who will train the future defenders?

The traditional “apprenticeship layer” is undeniably weakening. A recent 60 Minutes interview with Anthropic CEO Dario Amodei amplified these concerns, suggesting AI could “wipe out” many entry-level white-collar jobs. CyberSN founder Deidre Diamond reports a tangible reduction in entry-level roles, with recruiters observing a shrinking talent pool. While the 52% of cybersecurity professionals surveyed by ISC2 believe AI will reduce the need for these roles, a further 31% foresee the creation of new, specialized entry- and junior-level positions to offset the reductions.

Beyond technical skills, the shifting landscape emphasizes the importance of cultural and strategic understanding. Diamond stresses that the key gaps aren’t solely in technical proficiency but also in intuition, judgment, and the ability to make grounded decisions during critical incidents. Without exposure to the nuances of systemic behavior, future leaders may lack this essential “intuitive sense.”

Organizations are responding to these challenges with revamped training programs. Visa, for instance, has restructured its early-career analyst development around three pillars: experience, exposure, and education, with curiosity as a core trait. This model incorporates hands-on opportunities through hackathons, CISO challenges, and cross-domain rotations. The “90/10 model,” where analysts dedicate 10-20% of their time to projects outside their primary areas, facilitates cross-pollination and broadens exposure. Simulated cyber ranges and tabletop drills further accelerate learning by repeatedly replicating alert triage, patching, and incident response.

However, the transformation isn't solely about adopting new techniques. Gary Brickhouse, CISO at GuidePoint Security, sees AI not as a replacement for learning but as an accelerator. "AI clears the noise," he argues, "it elevates the talent that we have." Instead of sifting through massive datasets, analysts can leverage AI’s insights to focus on higher-level thinking and analysis.

To address these changes, organizations are beginning to explore new entry-level roles. Diamond predicts a transformation, with juniors becoming responsible for AI oversight, threat hunting, anomaly detection, and cross-disciplinary work – areas requiring a more strategic and nuanced understanding.

Ultimately, the shift underscores the importance of deliberate leadership development. As Visa’s Kumaraswamy emphasizes, creating “experience,” “exposure,” and “education” is central to analyst growth. Focusing on cultivating curiosity and intuition will be crucial to developing future-ready security professionals. Moreover, as Diamond warns, organizations must proactively address this shift, or risk losing valuable talent. The future of cybersecurity depends on organizations’ ability to purposefully shape the development of the next generation of defenders as AI becomes increasingly integrated into the security landscape.