What Will the AI Impact on Cybersecurity Jobs Look Like in 2025?

The editors at Solutions Review summarize some of the most significant ways AI has impacted cybersecurity jobs, hiring, skillsets, and more.

Regardless of your job title or industry, artificial intelligence (AI) has likely impacted your company’s internal and external processes. This can be especially true for cybersecurity professionals, as AI has changed how threat actors plan and execute attacks and introduced new ways to combat potential and active threats. What is less clear is the specific impact AI has had on cybersecurity and whether these professionals have cause for concern.

As AI is integrated into cybersecurity operations at unprecedented levels, the form and function of a company’s cyber team will continue to undergo rapid changes. To keep track of those changes, the Solutions Review editors have outlined some of the primary ways AI has changed cybersecurity, what professionals can do to remain agile during those evolutions, and what the future may hold for them and the technologies they use.

Note: These insights were informed through web research using advanced scraping techniques and generative AI tools. Solutions Review editors use a unique multi-prompt approach to extract targeted knowledge and optimize content for relevance and utility.

How Has AI Changed the Cybersecurity Workforce?

In just a few years, the impact of AI on cybersecurity has dramatically restructured the industry’s roles, responsibilities, and required skill sets. This transformation has been freeing for many, as AI technologies have streamlined user workloads and empowered teams to focus on more specialized, high-value tasks and projects. For comparison’s sake, consider how the global market for AI in cybersecurity is estimated to reach a market value of USD 133.8 billion by 2030, compared to its reported USD 14.9 billion in 2021. These technologies are exploding, and they’re not going anywhere.

However, it’s not uncommon for cybersecurity professionals to feel uneasy about the rapid adoption of these technologies, as they have already proven capable of rendering some tasks and roles nearly obsolete. Here are some of the job roles and processes that have been impacted the most by AI:

AI-Powered Automation and Analysis

AI is reshaping how cybersecurity analysis happens by expanding its scope and compressing its cognitive overhead. Traditionally, analysis involved hours of log inspection, correlation of alerts, and cross-referencing of threat intel feeds. However, with AI, especially those using machine learning (ML) and natural language processing (NLP), companies can automate those time-consuming processes to reduce alert fatigue and allow analysts to focus on the highest-risk threats.

For example, consider how leading cybersecurity platforms like Microsoft Defender XDR or IBM QRadar use ML models to correlate log entries and contextualize hundreds of alerts into real-time attack narratives. These streamlined analyses can dramatically reduce workloads by streamlining the process of identifying probable causes, unlocking cross-functional insights, and deploying that data to defend against future threats.

AI might be evolving what “analysis” looks like in cybersecurity, but it’s not ready to fully replace the necessity of human intervention. With AI handling the workload of detecting and aggregating information, human analysts will commit their time and expertise to interpretation, intent modeling, and escalation decision-making.

Threat Hunting and Adversarial Behavior Modeling

For years, traditional threat hunting has been hypothesis-driven: an analyst suspects that a particular tactic—e.g., credential stuffing or lateral movement—is occurring and searches logs or telemetry for artifacts that confirm or debunk that suspicion. However, this process is often narrow and human-biased, which is where AI can help. With its unsupervised learning and clustering capabilities, AI can identify and track patterns without preconceptions.

AI has essentially made “continuous hunting” possible. Some of the leading cybersecurity tools already use AI and behavioral models to proactively surface deviations, such as beaconing new domains or unusual SMB shares accessed at odd hours. Since AI can run 24/7, threat hunts no longer have to be ad hoc. It also adds a new data engineering dimension to threat hunting, as cybersecurity professionals are now encouraged (if not outright expected) to have AI-specific skills around curating telemetry, labeling behavior, and tuning features.

There’s no denying that AI is a double-edged sword for cybersecurity—cyber-criminals launched 36,000 malicious scans per second in 2024, according to Fortinet, and there’s been a 1,200 percent surge in phishing attacks since the rise of GenAI in late 2022. However, if companies want to keep up with the volume of attacks, they need the support that AI-boosted cybersecurity tools provide.

The Emergence of AI-Centric Cybersecurity Roles

The rise of AI in cybersecurity has not only affected existing workflows—it has spawned entirely new job categories, restructuring the profession around data-centric and model-centric competencies. These AI-centric cybersecurity roles represent a convergence of disciplines: traditional security, data science, ML operations (MLOps), and even behavioral psychology. Other roles like “blue team analysts” or “SOC engineers” are supplemented or outright replaced by titles like AI Threat Analyst, ML Security Engineer, and Adversarial ML Red Teamer.

It’s also possible that the future of cybersecurity jobs will start to resemble AI safety roles more than traditional InfoSec. This would involve an increased focus on validating agent boundaries, applying RLHF to constrain behavior, and building sandboxed testbeds for threat simulations. While there’s potential in that future, active and aspiring professionals should be wary, as that trend could result in a skills bar that leaves traditional network defenders behind unless they retrain aggressively.

The meta-trend here is becoming clear: Cybersecurity is evolving into a data science problem, and the workforce is shifting accordingly. The people who can reason statistically, build or probe AI systems, and think adversarially will define the next generation of cybersecurity leadership. Conventional roles will likely persist but may increasingly resemble operational support for AI-first tooling. Regardless, like LinkedIn’s Skills on the Rise report says, AI literacy will continue to be the skill that “professionals are prioritizing and companies are increasingly hiring for.”

Upskilling for the Future

AI isn’t a new technology, but it’s hitting the cybersecurity job market fast and hard. According to Cybersecurity Ventures, there will be 3.5 million unfilled jobs in the cybersecurity industry through 2025, a 350 percent growth from the one million open positions reported in 2013. If professionals want to keep their jobs—or future-proof themselves from potential displacement—they must equip themselves with AI-centric skills as soon as possible.

To reinforce that urgency, look at IBM’s Cost of a Data Breach Report, which shows that half of the organizations encountering security breaches also face high security staffing shortages. Even with 1 in 5 organizations using some form of generative AI, that skills gap remains a real challenge. Companies across industries need professionals fluent in adversarial and algorithmic logic, as that expertise will empower them to stay relevant regardless of the future. Mike Arrowsmith, the Chief Trust Officer at NinjaOne, puts it like this: “The best way to rein in AI risks is with more employee training. People have to know what to look out for, especially as AI technology evolves.”

One area professionals can focus on is soft skills. A recent study by Skiilify demonstrated that 94 percent of tech leaders believe soft skills—like curiosity, resilience, tolerance of ambiguity, perspective-taking, relationship-building, and humility—are more critical than ever. Soft skills can also help cybersecurity professionals understand how models can fail, how attackers exploit statistical assumptions, and how to wrap AI systems in resilient human oversight.

With Gartner predicting that, by 2028, “the adoption of GenAI will collapse the skills gap, removing the need for specialized education from 50 percent of entry-level cybersecurity positions,” it’s more crucial than ever for cybersecurity professionals to find and refine the skills that make them unique.

Will AI Replace Cybersecurity Professionals?

“AI won’t replace cybersecurity professionals, but it will transform the profession,” says Chris Dimitriadis, the Chief Global Strategy Officer at ISACA. The cybersecurity marketplace is already changing in response to AI tools and threats, but the transformation is far from finished. Even if the profession itself doesn’t go away, there’s a chance that current cybersecurity practitioners will be left behind as their job evolves into something they’re no longer equipped for.

In the longer term, AI will likely reshape cybersecurity professionals into decision supervisors. Their responsibilities will be less focused on making decisions and instead emphasize overseeing, calibrating, and intervening in AI-driven decision-making as necessary. It’s a subtler shift, but if the current workforce doesn’t upskill themselves in preparation, they may find that their expertise isn’t quite as valuable as it used to.

According to Sam Hector, Senior Strategy Leader at IBM Security, AI will “fundamentally shift the skills we require. Humans will focus more on strategy, analytics, and program improvements. This will necessitate continuous skills development of existing staff to pivot their roles around the evolving capabilities of AI.” The future of cybersecurity will be charted by practitioners who expand their perspective, prioritize their professional growth, engage with their peers, and collectively learn how to improve their AI-centric skills and literacy.

Want more insights like this? Register for Insight Jam, Solutions Review’s enterprise tech community, which enables human conversation on AI. You can gain access for free here!