# The Potential Impact of AI Innovations on U.S. Occupations

arXiv: https://arxiv.org/abs/2312.04714 · HTML: https://mlsanity.com/paper/2312.04714/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 Dec 2023.

## Built on by (most cited first, 5 of 5)

- [Working with AI: Measuring the Applicability of Generative AI to Occupations](https://mlsanity.com/paper/2507.07935/) (2025)
- [Rise of Generative Artificial Intelligence in Science](https://mlsanity.com/paper/2412.20960/) (2024)
- [Follow the money: a startup-based measure of AI exposure across occupations, industries and regions](https://mlsanity.com/paper/2412.04924/) (2024)
- [The Value of AI Advice: Personalized and Value-Maximizing AI Advisors Are Necessary to Reliably Benefit Experts and Organizations](https://mlsanity.com/paper/2412.19530/) (2024)
- [Will AI Agents Free Us From Meaningless Work? A Human-Centered Analysis](https://mlsanity.com/paper/2606.12430/) (2026)

## Abstract (arXiv)

An occupation is comprised of interconnected tasks, and it is these tasks, not occupations themselves, that are affected by AI. To evaluate how tasks may be impacted, previous approaches utilized manual annotations or coarse-grained matching. Leveraging recent advancements in machine learning, we replace coarse-grained matching with more precise deep learning approaches. Introducing the AI Impact (AII) measure, we employ Deep Learning Natural Language Processing to automatically identify AI patents that may impact various occupational tasks at scale. Our methodology relies on a comprehensive dataset of 17,879 task descriptions and quantifies AI's potential impact through analysis of 24,758 AI patents filed with the United States Patent and Trademark Office (USPTO) between 2015 and 2022. Our results reveal that some occupations will potentially be impacted, and that impact is intricately linked to specific skills. These include not only routine tasks (codified as a series of steps), as previously thought, but also non-routine ones (e.g., diagnosing health conditions, programming computers, and tracking flight routes). However, AI's impact on labour is limited by the fact that some of the occupations affected are augmented rather than replaced (e.g., neurologists, software engineers, air traffic controllers), and the sectors affected are experiencing labour shortages (e.g., IT, Healthcare, Transport).