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AI Skills Command a Premium as Talent Shortage Deepens
AI skills have moved from a specialized advantage to a baseline expectation across much of the technology job market. Employers are now seeking AI expertise in roughly three times as many job postings as they were just two years ago, while demand for generative AI skills has surged from virtually nonexistent levels in 2021 to thousands of openings today. The challenge for employers is that demand continues to outpace supply. According to IDC, AI skills are now the most sought-after enterprise capability, yet only about one-third of organizations consider themselves fully prepared to adopt AI-driven ways of working. The consequences are significant: IDC estimates AI-related skills shortages could cost the global economy as much as $5.5 trillion by 2026 through delayed projects, missed revenue opportunities, quality issues and reduced competitiveness. Meanwhile, the competition for talent is only intensifying, with a ManpowerGroup 2026 survey finding 72% of employers struggle to fill ope
The Skills Driving Health IT Careers
Tech skills are a hot commodity in healthcare, whether you’re working in a large health system or a small healthcare practice, especially amid burnout for both tech professionals and healthcare workers. From strong data analytics skills to clinical informatics, database management and cybersecurity, many critical skills are in demand. Health IT professionals who combine both business skills with tech expertise will have an edge, according to Mara Daiker, senior director of professional development at the Healthcare Information and Management Systems Society (HIMSS). “Cross-functional skills such as communication, collaboration, change management, and the ability to translate technical concepts for clinical and executive teams are also becoming essential,” Daiker said. “Professionals who can combine technical expertise with healthcare domain knowledge and strategic thinking are most likely to be successful.” In addition, skills such as data analytics, data visualization and predictive a
Entry-Level Tech Jobs AI Can't Touch
Landing an entry-level job in tech has become exceptionally challenging as companies increasingly use AI-powered assistants and tools to handle routine tasks such as writing boilerplate code or unit tests, resetting passwords or responding to basic support inquiries. In fact, surveys show a 73% decline in hiring rates for traditional entry-level tech roles in the past year. However, not all entry-level jobs have disappeared. Some positions are surviving the rise of AI automation because they require more advanced skills like human judgment, critical thinking, problem solving and written communication. In fact, entry-level workers who have the ability to build, manage, and audit AI systems are becoming more valuable. To land one of these former low barrier to entry roles, however, you may need to stack some complementary skills on top of your baseline technical experience. Here’s a look at some entry-level tech jobs that AI has impacted…but not replaced. Help Desk Technician Instead of
Stop Chasing Tools. Start Owning the Stack.
IT Careers Are Moving Toward Simplification and Strategic Execution Tool sprawl, support complexity and shifting work models are pushing IT teams to rethink how they operate, not just what they buy. That gives professionals an opportunity to grow by focusing on simplification, standardization and resilient support practices across distributed environments. In this evolving environment, the strongest career move may be less about chasing every new tool and more about becoming the person who makes the stack work better together. Michael Morris, global head of platform and talent at Randstad Digital, says as technology advances, professionals now have virtually every tool at their disposal. He cautions that Tool sprawl creates operational risk as organizations continue to layer on new solutions, increasing complexity across teams and workflows, and making it harder to ensure tools are fully aligned to business needs or consistently adopted. “To rationalize their stacks, leaders need to be
Add Context, Get Interviews: A Smarter Resume Strategy
If peppering your resume with keywords isn't getting results, it is likely because employers are using AI-powered semantic screeners to evaluate the context, meaning and intent behind your experience, rather than counting keyword frequency. As these screeners become standard, creating a resume that can pass muster with both human and automated semantic AI screeners is critical to securing an in-person interview. But how do you do that when semantic models and human reviewers differ in how they interpret language, context and meaning? For example, AI-powered screeners use natural language processing (NLP) to evaluate skills, job titles, accomplishments and experience to determine a "match score" against job descriptions. In contrast, human reviewers read language holistically to evaluate cultural fit, performance potential, skill application and authenticity. The solution is context. Adding quality, impactful context to your work experience, projects, and accomplishments helps you trans