Some 78% of cybersecurity jobs now require AI skills—an indicator that AI literacy is quickly becoming a baseline expectation for hiring, according to the AI Workforce Consortium.
“Our research found that there are critical gaps in areas such as generative AI, large language models, prompt engineering, AI ethics, and AI security,” the consortium wrote in a new report,* AI Agents and the Impact on Cybersecurity*, that looks at how agentic AI is reshaping the threat landscape and the future of security operations.
“Only a few years ago, AI was present in the workplace but peripheral, a specialized tool operating largely out of sight. Today, it’s fundamentally changing how we learn, work, and lead. Nowhere is that shift more visible right now than in cybersecurity, where frontier AI models like Anthropic’s Mythos Preview and OpenAI’s GPT-5.5-Cyber have changed cybersecurity as we know it,” wrote Marci Paino, chief learning officer at Cisco and the leader of the multi-vendor AI Workforce Consortium, in a blog post.
The AI Workforce Consortium is focused on studying the impact of AI on the workforce. Members include Accenture, Cisco, Cornerstone, Eightfold AI, Google, IBM, Indeed, Intel, Microsoft, Pearson, and SAP, in partnership with global advisors such as Digitaleurope and the European Vocational Training Association.
The consortium’s report found that between October 2025 and March 2026, the share of G7 cybersecurity postings that require AI skills rose to 28.5%—which is twice the percentage (14.2%) from the year-earlier period. (G7, or Group of 7, refers to the intergovernmental forum that includes Canada, France, Germany, Italy, Japan, the United Kingdom and the United States.)
According to the report, “an ‘agentic skill stack’ is emerging as a baseline for high-volume cybersecurity roles such as security engineering, cloud security, and detection and response engineering. Five pillars recur in AI-integrated cybersecurity postings: Python, Prompt and context engineering, AI security, agent orchestration and machine learning operations (MLOps).”
“AI skills are not new to cybersecurity. What has changed in the last few years with the emergence of agents built on large language models (LLMs), is how pervasive they have become, and how demand has shifted from building models to directing and verifying them,” the report states.
Two cybersecurity jobs most clearly illustrate this AI-driven transformation: the SOC analyst role and AI forensics expert. According to the report:
“The SOC analyst role is being rapidly redefined as agentic AI systems assume high-volume, repetitive tasks such as triaging alerts, correlating threat intelligence feeds, and executing standard decision-tree workflows. This shifts the analyst’s primary function from manual processing to orchestration and oversight. Technical requirements are shifting from SIEM platform proficiency and query writing toward agent supervision and output validation, while durable skills remain more essential than ever.”
New skills required of SOC analysts in the agentic era should include: investigation using AI-layer telemetry; AI agent supervision; AI governance and compliance; AI-assisted threat hunting; risk-based decision making; AI output validation; security workflow orchestration; and prompt injection recognition and response. The report calls the AI forensics expert “an emerging role in cybersecurity.” This new role “investigate[s] artificial intelligence systems after they fail, cause harm, or come under legal challenge.”
According to the report: “The evidence is unfamiliar: training data, model weights, prompt histories and inference logs rather than a disk image or a packet capture, read for bias, poisoning, tampering and adversarial manipulation. Regulation is starting to guarantee it exists. The EU AI Act obliges high-risk systems to log events automatically across their lifetime so incidents can be reconstructed later.”
The skills required of an AI forensics expert include: digital forensics and forensic investigation; artificial intelligence platforms and applied AI; Python and SQL; data science and data analytics; incident remediation; cyber threat intelligence; machine learning; electronic discovery; legal and regulatory analysis; and regulatory compliance.
In the big picture, “the impact isn’t limited to individual roles,” according to Paino.
“As agents take on more of the work, teams themselves are being restructured around new combinations of human and machine effort, with flatter, more fluid reporting lines,” she wrote. “Increasingly, every worker will need to manage a portfolio of agents to get work done, not just those in technical leadership. This model only works if organizations invest in the right skills.”
“Those skills are becoming less technical and more human,” Paino wrote. “People remain the final check, validating outputs, assessing risk, and ensuring decisions are sound. Beyond core technical requirements, workers need ethical reasoning (+533% YoY), systems thinking (+251% YoY), and stakeholder engagement (+125% YoY) to manage autonomous systems and work effectively across teams.”
The industry needs to close the cyber-skills gap “so that workforce capabilities grow alongside AI,” Paino wrote. “A new Cisco survey found that cybersecurity leaders are placing big bets on AI but not in the skills people will need to manage it. More than a third plan to invest in AI-powered security capabilities in the next one to two years, while only 25% are prioritizing investments in people.”
AI is also affecting staffing in other areas, including wireless.
According to Cisco’s State of Wireless 2026 report, 86% of organizations are struggling to hire qualified wireless professionals as teams are being asked to support expanding AI-driven workloads, IoT growth, and increasingly sophisticated threat environments. Meanwhile, AI is driving a talent gap: 50% of respondents in the Cisco report said AI is the top domain that’s attracting professionals away from wireless, according to a Network World article on the survey.
Paino notes that AI will continue to change cybersecurity, and that employers have a role to play when it comes to investing in people, skills, and learning:
“Hiring needs to shift from traditional, experience-heavy models to skills-based, proactive talent development. Programs like Google’s Vantage Project, IBM’s AI Builders Challenge, Cisco’s Networking Academy Capture the Flag initiative and Pearson’s AI Skills for the Future are replacing theoretical learning with immersive environments that allow learners to solve complex, autonomous challenges in real-time,” Paino write.