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What Cyber Pros Should Learn from Recent Frontier AI Disclosures
Since the release of the first commercially available large language models (LLMs) three years ago, organizations have sought to balance enthusiasm for deploying artificial intelligence within their networks with concerns about the added risks and cybersecurity challenges that come with adopting these technologies. A recent slate of disclosures from OpenAI, Meta and other AI firms and researchers shows that concerns about risk and cybersecurity should prompt organizations to exercise greater caution when testing and deploying AI, even when considering the benefits the technology offers. Consider the following four items announced between late July and early August: OpenAI disclosed in late July that two of its frontier AI cybersecurity models broke out of sandboxed testing environments and accessed the network of a different AI company – Hugging Face – using at least one and possibly more zero-day exploits in third-party applications. Following the OpenAI disclosure, Anthropic released
The AI Skills Premium Is Rising—But Which Skills Will Last?
Although AI proficiency is becoming a requirement across technology roles, employers are not paying a premium simply for experience with a popular model, coding assistant or prompt interface. The greatest demand is for professionals who can turn AI prototypes into secure, reliable production systems and demonstrate how those systems improve the business, which requires technical foundations, knowledge of AI-specific architecture and the judgment to recognize when a model’s output cannot be trusted. Draup analyzed approximately 2.85 million active job descriptions across nine engineering, data and AI-related roles between June 2025 and June 2026. The findings indicate employers are placing greater value on production experience, model oversight and senior-level decision-making than on familiarity with any single platform. “The skills drawing the biggest premiums aren’t tied to one model or platform,” says Vishnu Shankar, chief data officer at Draup. “They’re the skills involved in putti
How Red Teams and Pen Testers Are Remaking Themselves in an AI Era
With 96% of senior cybersecurity leaders reporting that attacks driven by artificial intelligence have become a persistent threat to networks and infrastructure, penetration testing and red teaming remain important tools for identifying vulnerabilities, strengthening defenses, protecting data and reducing risk. At the same time, AI is altering the nature of pen testing, changing the types of skills and abilities that successful red teamers need, as virtual chatbots and frontier AI models change the cybersecurity landscape by increasing the size of the attack surface organizations need to defend. Consider a recent Microsoft announcement focusing on the company’s AI Red Team and detailing new ways to address security issues that come with the development and release of frontier AI large language models (LLMs) that can quickly uncover vulnerabilities in applications that attackers could theoretically exploit more quickly. To counter this, Microsoft announced an External Red Team Alliance
How to Identify and Avoid “Ghost Jobs”
If you keep applying for jobs that seem like a fit but rarely hear back, you may be falling for so-called “ghost jobs” or advertisements for roles that companies are not actively trying to fill. A recent survey of over 1,000 hiring managers by Resume Genius confirms that the ghost job problem has surged. In fact, 47% of respondents admit that companies intentionally post jobs they do not plan to fill immediately. What’s their motive? Companies often post fake jobs to build resume pipelines for future openings or signal growth or financial stability to investors, clients or competitors. Nearly a third of hiring managers point to internal HR policies requiring a role to be advertised externally before an internal candidate is appointed. Sometimes hiring managers post fake jobs to gather salary and market data and then leverage the research to justify a new role, or secure budget approval or higher salary before opening a job requisition. Their motives are not always malicious – some comp
From Compliance to Code: How AI Governance Is Reshaping IT Careers
Organizations continue to move AI systems and autonomous agents into production, with governance becoming a more technical discipline rather than solely a legal or compliance function. AI governance professionals must identify which systems exist, determine what data and tools they can access, measure whether they behave as intended and produce evidence that risks are being controlled. They must also develop procedures for responding when a model produces biased results, exposes data or takes an unauthorized action, resulting in a combination of skill sets opening a new career path for IT professionals who can connect organizational policy with the technical realities of operating AI. Which IT Roles Are Moving into AI Governance? AI governance teams are drawing professionals from cybersecurity, risk management, compliance, platform engineering, data science and machine learning evaluation. “We are seeing people come into AI governance from security, compliance, platform engineering and