Jobs of Tomorrow

The World Economic Forum and Accenture provide a toolkit for businesses to navigate the impact of Large Language Models (LLMs) on the workforce. The guide identifies three primary areas of concern: job change and displacement risk, job quality, and skilling and learning. For each area, it proposes strategies based on promoting worker awareness, facilitating organizational change, and shifting workplace culture. The document highlights that while LLMs may automate routine tasks, they also offer significant potential for augmenting complex problem-solving roles and creating new job categories.

• Large language models (LLMs) have a significant transformative potential for the global workforce, with an estimated 40% of working hours potentially transformed through either automation or augmentation.
• The impact of LLMs varies by job type: roles involving routine and repetitive language tasks are most susceptible to automation, while roles requiring critical thinking, complex problem-solving, and STEM skills are most likely to be augmented.
• To mitigate job displacement risks, businesses are encouraged to use predictive analytics for forecasting, establish internal job marketplaces to facilitate mobility, and foster a culture of workforce agility, such as through 'side project time'.
• LLMs present risks to job quality, including the potential for systemic discrimination and bias in decision-making, particularly if models are trained on Anglocentric texts or biased hiring datasets.
• Job quality can be improved by using LLMs to automate monotonous tasks, thereby freeing workers for more creative and independent decision-making work, which can boost overall fulfillment.
• There is a critical need for urgent reskilling, as business leaders estimate that 44% of workers' skills will be disrupted within five years, with AI and big data skills becoming a top priority for large companies.
• The document advocates for a 'skills-first' approach to hiring and talent management, which prioritizes competencies over formal degrees or job titles to reduce talent shortages and democratize job access.

APA

World Economic Forum (2023). Jobs of Tomorrow. https://www3.weforum.org/docs/WEF_Jobs_of_Tomorrow_Large_Language_Models_and_Jobs_2023.pdf

Chicago

World Economic Forum. Jobs of Tomorrow. 2023. https://www3.weforum.org/docs/WEF_Jobs_of_Tomorrow_Large_Language_Models_and_Jobs_2023.pdf.

Wikipedia

{{cite report |author=World Economic Forum |title=Jobs of Tomorrow |date=December 2023 |url=https://www3.weforum.org/docs/WEF_Jobs_of_Tomorrow_Large_Language_Models_and_Jobs_2023.pdf |access-date=23 October 2026 |via=Climate Insights Directory}}

BibTeX

@techreport{worldeconomicforum2023jobs, author = {{World Economic Forum}}, title = {{Jobs of Tomorrow}}, institution = {World Economic Forum}, year = {2023}, month = dec, url = {https://www3.weforum.org/docs/WEF_Jobs_of_Tomorrow_Large_Language_Models_and_Jobs_2023.pdf}, urldate = {2026-10-23}, note = {Indexed by Climate Insights Directory} }