AI is not “wiping out jobs overnight”, it is removing task bundles inside roles, and entry-level jobs are hit first because junior work is more standardised and easier to automate. In the UK, roles most exposed to AI are seeing job posting growth 4x slower than lower-risk roles, a quiet hiring shift rather than a sudden collapse. The early impact is already measurable: freelance writing and coding demand fell 21% within months of ChatGPT’s release. The net effect is likely reallocation, not just loss, with projections showing 92M jobs displaced and 170M new jobs created by 2030, while 17% of employers expect headcount reductions due to AI in 2026 and 14% of workers may need to change careers by 2030.

GDPval is OpenAI’s “real-work” evaluation: instead of exam questions, it measures whether AI can produce economically valuable deliverables professionals would actually ship. It spans 44 knowledge-work occupations across nine U.S. GDP-leading sectors, selected using BLS wage data and O*NET task analysis with a 60% digital-work threshold. The benchmark includes 1,320 expert-designed tasks (plus a 220-task open gold subset) requiring artifacts like legal briefs, nursing care plans, financial spreadsheets, sales decks, and multimedia. Outputs are graded with blind, head-to-head expert preference judgments, complemented by an experimental automated grader. OpenAI notes models can be faster and cheaper on inference, but human oversight and integration matter. In this guide, you’ll get the full list of jobs, the methodology, what the early results imply for AI productivity and AI search, and what comes next: more roles, more multimodal context, and more iterative, ambiguity-heavy workflows. (integrated.social)

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