It feels like everyone and anyone has something to say about AI creeping up on repetitive, routine tasks – and maybe even stealing our jobs with the press of a single magic button.
But how much of that is true today? Let’s take a look at eight popular roles in the tech industry and separate myths from truths.
Who’s this article for?
Let’s be honest – if you’ve ever been hit with the “sell me this pen” question during a first-round screen, you probably wanted half the recruiting world replaced by an AI that just checks skills and spits out an unbiased summary. But is it really that simple?..
Myth: Recruiters are outdated. AI agents scan resumes faster, filter candidates better, and overall make the hiring process smoother and smarter.
What do experts say:
AI can handle the workflow, sure – but it’s terrible at empathy. It can’t sense culture fit, understand team dynamics, or read between the lines of a candidate’s story. For now, these elements remain important in a company’s life, and AI can act as an assistant, relieving recruiters or hiring managers of routine tasks.
You’ve got policies, onboarding, payroll, performance reviews, and one million Slack pings about “can I take next Friday off?” Honestly, if an AI could handle half of that, why not let it? But here’s the catch.
Myth: AI will fully replace HR generalists by automating admin tasks, tracking performance, and keeping everything in line with labor law – faster and cheaper.
What do experts say:
AI’s great at reminders, reports, and policy enforcement. But when it comes to real human needs like navigating messy team dynamics, managing emotions, or mediating tough conversations – it’s still painfully robotic. HR generalists don’t just execute tasks; they hold the culture together. Besides culture, there are other aspects, like team check-ins, compliance, whistleblowing, and more – nuances that AI cannot handle, as it simply can’t make the right ethical decisions.
AI is not a replacement, but a powerful augmentation tool. Those who recognize this early and integrate AI into their workflows will gain a significant competitive advantage.
Automated tests, visual regression tools, AI-powered bug detectors… At this point, it feels like even your toaster could run a smoke test. But here’s what’s really going on.
Myth: AI testing tools will fully replace QA engineers – they’re faster, more precise, and can cover 10x more test cases without lunch breaks.
What do experts say:
AI can run tests, sure. But it doesn’t understand business logic, user expectations, or weird edge cases that happen only in production. Good QA isn’t just checking boxes – it’s critical thinking, curiosity, and asking, “What if the user does something stupid?”
Why write code from scratch when Copilot can build the whole page layout – and even throw in some Tailwind classes while it’s at it? Tempting, right?
Myth: With AI coding assistants, frontend devs are obsolete. You describe a component, and it builds it. Done.
What do experts say:
AI can help build, but it doesn’t design for experience. It doesn’t understand trade-offs in performance, accessibility, or UX flow. And let’s not forget: debugging weird browser behavior still takes a human with grit and Google-fu.
AI can write user stories, analyze metrics, summarize customer feedback, and even create roadmaps. Do we still need PMs, or can we just ask ChatGPT what to develop next?
Myth: AI will make product managers irrelevant by automating strategy, planning, and team coordination.
What do experts say:
AI can suggest, but can’t decide. It doesn’t sit in meetings, negotiate priorities, or translate founder chaos into a roadmap engineers will follow. PM work is 80% communication, alignment, and intuition – not just feature descriptions.
Drag, drop, prompt, boom – Figma plugin generates the whole dashboard UI. Who needs designers when Midjourney or Galileo can do the job?
Myth: AI tools can generate UIs faster and prettier than human designers, making the role redundant.
What do experts say:
A good-looking screen isn’t the same as a good user experience. Designers think in flows, systems, user behavior, and accessibility. AI lacks empathy, intent, and understanding of how and why people interact with interfaces. It also cannot anticipate the team’s vision, the subtle nuances of interaction, or the multiple iterations needed to refine a product – no matter how sophisticated the AI is, these aspects require human insight and collaborative decision-making.
AI can suggest, but can’t decide. It doesn’t sit in meetings, negotiate priorities, or translate founder chaos into a roadmap.
AI already handles FAQs, responds instantly, and never loses patience. Sounds like a dream… until someone’s integration breaks on a Friday night.
Myth: Chatbots and AI assistants will handle 100% of support tickets – no humans needed.
What do experts say:
AI handles routine, but when things get messy – bugs, billing errors, emotional clients – it falls apart fast. Great support requires calm under pressure, product understanding, and knowing how to say, “I hear you,” like a real person. Often, support cuts happen not because of workload alone, but because AI or impersonal systems can’t build real relationships with clients, which humans do naturally.
ChatGPT writes blog posts in seconds, rewrites landing pages, and even throws in a call to action that sounds... kinda okay. So why keep a human around?
Myth: AI can generate high-quality content faster, cheaper, and in any tone. Writers are just middlemen now.
AI can generate text. But it doesn’t know your audience, brand voice, context, or strategy. It can’t interview a customer, craft a narrative, or say something truly original. Great content isn’t just readable – it’s relevant, insightful, and human. You can’t automate nuance. Besides, in an era where companies aim not just to operate but to build relationships with customers and tell their brand story, consistency, a human approach, and attention to detail are essential.
AI is not a replacement, but a powerful augmentation tool. Those who recognize this early and integrate AI into their workflows will gain a significant competitive advantage.
While AI excels at automating repetitive tasks, analyzing large datasets, and accelerating processes, it still lacks:
While AI shows great potential, it is unlikely to replace the majority of tech professionals completely anytime soon. Significant advancements – particularly in emotional intelligence, contextual understanding, and complex decision-making – are required before such a shift becomes feasible.
Until then, AI remains a powerful tool that highlights human capabilities by automating routine tasks and analyzing data at scale.
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