Global Economic Futures: Productivity in 2030

The report examines a global productivity slowdown, noting that more than half of the deceleration in global economic growth since 2008 is attributed to this trend. It proposes four scenarios for 2030 based on the acceleration or slowdown of technology and human capital: 'Productivity Leap', 'Automation Overload', 'Human Advantage', and 'Productivity Drought'. The analysis highlights that while AI and disruptive technologies offer significant potential, their impact is hindered by skills gaps, lack of visionary leadership, and geopolitical fragmentation. Sectoral analysis identifies varying exposure, with information technology and financial services highly sensitive to these drivers, while agriculture remains more resilient but with limited upside. The document concludes with strategic recommendations for governments and businesses to synchronize technology adoption with workforce development.

• Global productivity growth has significantly declined since the 2008-2009 financial crisis, with the International Monetary Fund estimating that over 50% of the deceleration in global economic growth since that period is due to a productivity slowdown.
• There is a profound disparity in labour productivity based on income; high-income economies were nearly 15 times more productive than low-income economies between 2010 and 2024.
• The adoption of AI for productivity is uneven globally; executives in high-income economies rate its use nearly 40% higher than those in low-income economies, with Norway, the USA, and Finland identified as global leaders.
• Human capital is identified as the primary bottleneck for AI adoption, with nearly 50% of business leaders citing a lack of skills and 43% citing a lack of visionary leadership as the main obstacles.
• The report outlines four distinct futures for 2030: 'Productivity Leap' (acceleration of both technology and human capital), 'Automation Overload' (technology outpaces human capital), 'Human Advantage' (human capital outpaces technology), and 'Productivity Drought' (slowdown of both).
• In the 'Automation Overload' scenario, the economy is characterized by a 'winner-takes-all' dynamic where wealth and power concentrate, and productivity gaps widen between leading and lagging firms and regions.
• The information technology and digital communications sector is highly vulnerable to geopolitical tensions, specifically data localization requirements which nearly doubled between 2017 and 2021.
• The financial services sector has high automation potential, with over 53% of work time potentially automatable, and generative AI could save up to $158 billion in annual work hours in the US.
• In the energy and materials sector, AI is projected to significantly increase power demand, specifically increasing data centres' global power consumption by 160% by 2030.
• The education sector is seen as a primary enabler of productivity, with AI adoption alone projected to generate $200 billion in value by 2025.

APA

World Economic Forum (2025). Global Economic Futures: Productivity in 2030. https://reports.weforum.org/docs/WEF_Global_Economic_Futures_Productivity_in_2030_2025.pdf

Chicago

World Economic Forum. Global Economic Futures: Productivity in 2030. 2025. https://reports.weforum.org/docs/WEF_Global_Economic_Futures_Productivity_in_2030_2025.pdf.

Wikipedia

{{cite report |author=World Economic Forum |title=Global Economic Futures: Productivity in 2030 |date=January 2025 |url=https://reports.weforum.org/docs/WEF_Global_Economic_Futures_Productivity_in_2030_2025.pdf |access-date=23 October 2026 |via=Climate Insights Directory}}

BibTeX

@techreport{worldeconomicforum2025global, author = {{World Economic Forum}}, title = {{Global Economic Futures: Productivity in 2030}}, institution = {World Economic Forum}, year = {2025}, month = jan, url = {https://reports.weforum.org/docs/WEF_Global_Economic_Futures_Productivity_in_2030_2025.pdf}, urldate = {2026-10-23}, note = {Indexed by Climate Insights Directory} }