Career Catalyst Chronicles

  Let me throw this question to all of you first: have you noticed that "entry-level" no longer feels like entry-level? "Every job wants experience, but where do we get that experience if starter roles are vanishing?" is a common statement I hear from candidates. This goes beyond simple annoyance. AI is subtly changing the fundamentals of early-career jobs, according to research and actual hiring trends, and many of us are directly at fault line. What the Data Is Telling Us - and Why It Matters to Us One finding in particular caught my attention when I began looking into recent studies. In positions most susceptible to AI, such as junior coding, customer service, content moderation, and administrative tasks, entry-level hiring has decreased by double digits , according to a Stanford-affiliated investigation. Here is where I would appreciate your opinion: Does this imply that AI is "stealing jobs," or does it highlight the precariousness of our conventional...

Based on my own experience and interactions with professionals from many industries, AI has firmly entered the workplace - but so have misgivings. Almost everyone I speak with agrees that AI can make work faster and more efficient, but there's a quiet scepticism beneath the surface. These concerns are not about opposing technology; they are about what AI means for our responsibilities, skills, privacy, and value as humans at work. The lingering fear: “Will AI replace me?” One of the most common concerns I encounter is fear of job loss. Even when organisations say AI is meant to “support” employees, many workers quietly wonder if that’s just a temporary phase. Research backs this up - global surveys show a significant portion of employees worry that AI will eventually make their roles redundant or reduce their importance. What’s interesting is that the fear isn’t always about being fired; it’s about becoming irrelevant. From my experience, this fear grows stronger in environme...

Artificial intelligence (AI) is rapidly changing the way we work, think, and make decisions. As enterprises implement AI at scale, a serious challenge arises: How can we effectively cooperate with AI while keeping human judgment central? The solution goes beyond mastering tools; it involves deliberate training, cultural alignment, and a mindset that combines human capabilities with machine efficiency. In this piece, I will go over the training components that enable effective AI cooperation, supported by research findings, expert comments, real-world examples, and actionable takeaways for professionals wishing to succeed in an AI-rich workplace. Why Human Oversight Matters Before we unpack training, it’s critical to recognize why human oversight is non-negotiable . AI systems can process massive data, spot patterns, and generate outputs with impressive speed. But they lack the deeper understanding of context, ethics, values, and nuance that humans bring. Experts underline that human...