{"id":79794,"date":"2026-03-10T01:51:32","date_gmt":"2026-03-10T05:51:32","guid":{"rendered":"https:\/\/world.edu\/?p=79794"},"modified":"2026-03-10T01:51:32","modified_gmt":"2026-03-10T05:51:32","slug":"ai-and-work-an-expert-assesses-how-far-this-revolution-still-has-to-run","status":"publish","type":"post","link":"https:\/\/world.edu\/ai-and-work-an-expert-assesses-how-far-this-revolution-still-has-to-run\/","title":{"rendered":"AI and work: an expert assesses how far this revolution still has to run"},"content":{"rendered":"

\"\"<\/p>\n

Every week brings fresh claims about AI transforming the workplace. A CEO declares a revolution. A think piece predicts millions of jobs vanishing overnight. The noise is relentless.<\/p>\n

But strip away the hype and there is a simpler question. In developed economies, what has\u00a0AI<\/a>\u00a0actually changed about work so far? The answer turns out to be more interesting, and more uneven, than either side suggests.<\/p>\n

What\u2019s real<\/strong><\/h4>\n

Let\u2019s start with what the evidence supports. AI is delivering genuine productivity gains in specific kinds of knowledge-based and service work. An\u00a0experimental study<\/a>\u00a0found that professionals using ChatGPT for writing tasks took 40% less time to complete them, with an 18% improvement in quality (as evaluated by their colleagues in blind testing).<\/p>\n

And another study of more than\u00a05,000 customer service agents<\/a>\u00a0found a 15% increase in issues resolved per hour.\u00a0An industry experiment<\/a>\u00a0involving realistic, complex tasks done with management consultants found they completed the work 25% faster and produced results that were deemed to be 40% higher in quality (again, judged by experts in blind tests).\u00a0Randomised trials<\/a>\u00a0involving nearly 5,000 software developers documented a 26% increase in completed tasks.<\/p>\n

These are not small numbers. And adoption is moving fast. A\u00a0US survey<\/a>\u00a0found that nearly four in ten workers were using generative AI at work by mid-2025. This pace of adoption outstrips the early years of both the personal computer and the internet. Across countries in the Organisation for Economic Co-operation and Development (OECD), firms report that\u00a0AI integration<\/a>\u00a0into business functions is accelerating.<\/p>\n

So the productivity story is real, particularly in text-heavy, codifiable tasks across legal, finance, marketing and customer service. That much is not hype.<\/p>\n

What\u2019s overstated<\/strong><\/h4>\n

But the apocalyptic predictions have not yet materialised. Employment across OECD countries remains\u00a0historically robust<\/a>. A review of the\u00a0research-based evidence<\/a>\u00a0produced in the US in early 2026 found that despite rapid adoption, AI has so far caused little in the way of widespread job losses or pay cuts.\u00a0And a study<\/a>\u00a0(as yet unpublished) that tracked AI chatbot use in Danish workplaces found essentially zero effects on earnings or recorded hours, even among heavy users and early adopters.<\/p>\n

Why? Because many jobs still require tacit knowledge, physical presence, sound judgement and the kind of contextual awareness that AI cannot yet replicate. And adoption is far more uneven than the headline numbers suggest. While AI use among\u00a0firms in the US<\/a>\u00a0soared between\u00a02023 and 2025<\/a>, a\u00a0report found<\/a>\u00a0fewer firms had actually embedded it into their operations. The information sector, for example, adopted it at roughly ten times the rate of hospitality.<\/p>\n

One\u00a0economic modelling exercise<\/a>\u00a0estimates that AI might add somewhere between 1% and 1.6% to US GDP over the next decade. This is significant, but it is far short of the\u00a0transformative claims<\/a>.<\/p>\n

The gap between productivity gains in controlled studies and real transformation inside organisations remains enormous. The revolution, for most workplaces, has not yet arrived.<\/p>\n

What\u2019s under-reported<\/strong><\/h4>\n

Here is where the story gets more consequential and where the commentary falls short. The distributional effects of AI within developed economies deserve far more attention. Not everyone is experiencing this transformation the same way.<\/p>\n

The evidence on who benefits is strikingly consistent. Less experienced workers see the biggest gains from AI tools.\u00a0A study<\/a>\u00a0found that AI narrowed the gap between the most and least productive staff, with the largest improvements among lower-ability workers.<\/p>\n

In\u00a0customer service<\/a>, novice agents benefited most. The most experienced staff experienced little improvement and, in some cases, slight quality declines. The\u00a0industry experiment<\/a>\u00a0mentioned above found below-average performers improved by 43%, while top performers gained 17%. So the biggest gains go to the least experienced workers, narrowing the gap between top and bottom performers within firms.<\/p>\n

That sounds like good news. But there\u2019s a catch.<\/p>\n

While AI may compress skills inside firms, the broader labour market is telling a different story. Entry-level\u00a0roles are shrinking<\/a>\u00a0in AI-exposed occupations. The routine tasks that once justified hiring juniors \u2013 jobs which provided learning opportunities for those on the bottom rung \u2013 are the first to be automated.<\/p>\n

Economic theory<\/a>\u00a0has long warned that automation displaces workers from tasks, and the creation of new tasks to counterbalance this is neither automatic nor guaranteed. An estimated\u00a060% of jobs<\/a>\u00a0in advanced economies face some AI exposure.<\/p>\n

In most\u00a0realistic scenarios<\/a>, inequality worsens without deliberate intervention \u2013 partly because higher-income workers hold more capital assets and stand to gain from\u00a0rising returns<\/a>\u00a0on AI-related investments.<\/p>\n

The pattern that is emerging is this: AI helps those already inside the door while quietly narrowing the door for those trying to get in.<\/p>\n

Paying attention to the right question<\/strong><\/h4>\n

Sector matters. Firm size matters. Job type matters. The AI transition is not one story. It is many \u2013 unfolding at different speeds, with different consequences, depending on where you sit in the economy.<\/p>\n

The debate has been stuck between breathless optimism and existential dread. Neither is useful. The evidence points somewhere more uncomfortable: a transformation that is real but partial, fast in some corners and stalled in others \u2013 and distributing its costs and benefits in ways that are shaped by existing inequalities.<\/p>\n

If the productivity gains are genuine, the question is: who captures them? If entry-level work is disappearing, what replaces it? And if the gap between firms that adopt and those that cannot is widening, the focus should be on what we are building in response. Just talking about it won\u2019t be enough.<\/p>\n

Author Bio:<\/strong> Vivek Soundararajan is Professor of Work and Equality at the University of Bath<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"

Every week brings fresh claims about AI transforming the workplace. A CEO declares a revolution. A think piece predicts millions of jobs vanishing overnight. The noise is relentless. But strip away the hype and there is a simpler question. In developed economies, what has\u00a0AI\u00a0actually changed about work so far? The answer turns out to be […]\n… learn more→<\/a><\/p>","protected":false},"author":33,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[434804],"tags":[12148],"coauthors":[11733],"class_list":["post-79794","post","type-post","status-publish","format-standard","hentry","category-artificial-intelligence","tag-workplace"],"acf":[],"yoast_head":"\nAI and work: an expert assesses how far this revolution still has to run - World leading higher education information and services<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/world.edu\/ai-and-work-an-expert-assesses-how-far-this-revolution-still-has-to-run\/\" class=\"yoast-seo-meta-tag\" \/>\n<meta property=\"og:locale\" content=\"en_US\" class=\"yoast-seo-meta-tag\" \/>\n<meta property=\"og:type\" content=\"article\" class=\"yoast-seo-meta-tag\" \/>\n<meta property=\"og:title\" content=\"AI and work: an expert assesses how far this revolution still has to run - World leading higher education information and services\" class=\"yoast-seo-meta-tag\" \/>\n<meta property=\"og:description\" content=\"Every week brings fresh claims about AI transforming the workplace. 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