Foreword

New digital technologies, including artificial intelligence, robotics and information and communication technologies are reshaping the way people live, work and learn. These new technologies can enhance the way people learn, where, when and how they work, and spur their engagement in society by extending everyone’s ability to gather, interpret and analyse information and communicate with others around the globe seamlessly.

While technologies are constantly evolving, those changes are poised to replace some of the tasks in jobs that are currently carried out by humans and, in turn, freeing time to produce more innovation, eventually leading to further changes and even more radical shifts in the way humans interact with machines in society and labour markets. This report presents the most recent trends in the demand for digital occupations using the information contained in millions of job postings collected from the internet. Results highlight where labour market bottlenecks are emerging and policy action is – and will be – needed to support individuals to acquire digital skills to thrive in rapidly evolving labour markets and societies.

The report is organised as follows: Chapter 1 provides an overview of the main results of the report. Chapter 2 presents the new challenges for the labour market and the demand for digital skills. Chapter 3 discusses the data that underpin the analysis, providing details on how job postings are collected from the internet and processed using machine learning techniques. The chapter also discusses the representativeness of the data, its advantages and limitations in the context of the current analysis. Chapter 4 analyses the evolution of online job postings at the deepest occupational disaggregation level available in job postings, by focusing on a selection of key digital occupations across different sectors and countries. The analysis compares the evolution of the demand for workers in occupations within the same country while also providing a cross-country snapshot showing differences in the demand for digital occupations across the geographies covered in the report. Chapter 5 uses novel machine learning techniques to analyse the skill information contained in the text of online job postings in order to assess the relevance of new technologies, digital tools and skills for the digital occupations covered in this report. Chapter 6 assesses the diffusion of digital skill demands over time by investigating the speed with which a variety of digital technologies have been permeating labour markets over time. The analysis compares the diffusion of digital skills with the average of the economies under consideration with the intent of identifying areas where the demand for digital skills and technologies have been particularly strong across the countries analysed. Chapter 7 concludes the report by leveraging the granular information on skill demands at the occupation level to compare the skill profiles of occupations in decline with those of occupations that are growing in the labour market and to suggest potential the key skill needed to retraining and move from traditional jobs to thriving digital ones.

This report was prepared by Fabio Manca and Ainhoa Osés Arranz from the OECD Directorate for Employment, Labour and Social Affairs. Useful comments were provided by the team in Randstad Research Italy: Alessandro Ramazza, Daniele Fano, Rossella Fasola, Luca Paiusco, Federica Romano, Francesca Lettieri, Jaap Buis as well as from Mark Pearson (Deputy Director, Directorate for Employment, Labour and Social Affairs, OECD), Glenda Quintini (Senior Economist, Skills and Employability Division, Directorate for Employment, Labour and Social Affairs, OECD), Francesca Borgonovi (Senior Economist, Skills Analysis team, Centre for Skills, OECD) and Vincenzo Spiezia (Senior Economist, Digital Economy Policy Division, Directorate for Science, Technology and Innovation, OECD). Editorial support was provided by Natalie Corry.

This report is published under the responsibility of the Secretary General of the OECD, with the financial assistance of Randstad N.V. The views expressed in this report should not be taken to reflect the official position of OECD member countries.

Metadata, Legal and Rights

This document, as well as any data and map included herein, are without prejudice to the status of or sovereignty over any territory, to the delimitation of international frontiers and boundaries and to the name of any territory, city or area. Extracts from publications may be subject to additional disclaimers, which are set out in the complete version of the publication, available at the link provided.

© OECD 2022

The use of this work, whether digital or print, is governed by the Terms and Conditions to be found at https://www.oecd.org/termsandconditions.