Humans vs. Machines? The Real Future of Work

Wed Oct 15 2025
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Key points

  • Automation transforming education, healthcare, and transport
  • New hybrid roles emerging in AI era

ISLAMABAD: In a rapidly changing labour market, artificial intelligence is now reshaping professions across the spectrum—from teaching and journalism to medicine and transport. According to a 2025 update from the International Labour Organization, many occupations face varying degrees of exposure to generative AI, leading to potential disruption in tasks that can be automated or augmented.

In the United Kingdom,  a government-commissioned report suggests that 10–30% of jobs are at risk of automation as AI continues its advance into routine and cognitive tasks.

While that doesn’t mean wholesale job loss, the trend signals a shift in how work is organized—and who benefits.

What’s changing on the ground?

Teachers and journalists may find some administrative, grading, or fact-checking duties increasingly handled by algorithms, pushing them toward oversight, analysis, or niche reporting.

Doctors and other medical professionals could see diagnostic tools, imaging analysis, and preliminary patient assessments aided by AI, allowing them to focus more on complex care, ethics, and patient interaction.

Truck drivers and logistics operators are among the most visible roles under threat, as autonomous vehicle systems and smart routing gain traction in controlled environments.

New hybrid roles will emerge—think “AI trainers,” “algorithm explainers,” “augmentation engineers,” and “ethics auditors”—jobs that bridge technical, creative, and human dimensions.

What skills will matter most?

Soft skills—empathy, critical thinking, judgment, adaptability—will become ever more valuable. Expertise in data literacy, human-AI collaboration, ethics, and domain knowledge will distinguish workers from machines.

The future of work isn’t so much a battle of humans vs. machines as a question of integration. Organizations and governments must invest in reskilling, lifelong learning, and inclusive transition strategies so that automation becomes a partner—not a threat—in building tomorrow’s work.

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