  The spread and rapid development of AI-related technologies are influencing
many aspects of our daily lives, from social to educational, including the
labour market. Many researchers have been highlighting the key role AI and
technologies play in reshaping jobs and their related tasks, either by
automating or enhancing human capabilities in the workplace. Can we estimate
if, and to what extent, jobs and related tasks are exposed to the risk of being
automatized by state-of-the-art AI-related technologies? Our work tackles this
question through a data-driven approach: (i) developing a reproducible
framework that exploits a battery of open-source Large Language Models to
assess current AI and robotics' capabilities in performing job-related tasks;
(ii) formalising and computing an AI exposure measure by occupation, namely the
teai (Task Exposure to AI) index. Our results show that about one-third of U.S.
employment is highly exposed to AI, primarily in high-skill jobs (aka, white
collars). This exposure correlates positively with employment and wage growth
from 2019 to 2023, indicating a beneficial impact of AI on productivity. The
source codes and results are publicly available, enabling the whole community
to benchmark and track AI and technology capabilities over time.
