How Exposed Are UK Jobs to Generative AI? Developing and Applying a Novel Task-Based Index

Golo Henseke, Rhys Davies, Alan Felstead, Duncan Gallie, Francis Green and Ying Zhou

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Abstract: We draw on Eloundou et al. (2024) to develop the Generative AI Susceptibility Index (GAISI), a task-based measure of UK job exposure to large language models (LLMs), such as ChatGPT. GAISI is derived from probabilistic task ratings by LLMs and linked to worker-reported task data from the Skills and Employment Surveys. It reflects the share of job activities where an LLM or LLM-powered system can reduce task completion time by at least 25% beyond existing productivity tools. The index demonstrates high reliability, strong alignment with AI capabilities, and superior predictive power compared to existing exposure measures. By 2023-24, nearly all UK jobs exhibited some exposure, yet only a minority were heavily affected. Aggregate exposure has risen since 2017, primarily due to occupational shifts rather than changes in task profiles. The price premium for AI-exposed tasks declined relative to 2017, measuring approximately 12% lower in 2023-24. Job postings fell following the release of ChatGPT, with job postings 5.5% lower in 2025-Q2 than if pre-GPT hiring patterns had persisted. GAISI offers a robust framework for assessing AI's impact on work, providing early evidence that displacement effects may already outweigh productivity gains.

Date: 2025-07, Revised 2025-08
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