As artificial intelligence (AI) continues to become more embedded in various industries, employers and jobseekers alike are looking for the right skills to succeed in an evolving labour market. This article examines the AI education policies of several countries, as well as their systemic approaches to teaching their citizens about AI and providing relevant training.  

The authors conducted a systemic literature review of government reports, policies and frameworks and selected countries of various population sizes based on the Government AI Readiness Index (GAIRI) compared to the Global AI Index (GAI).  

They found that every studied country acknowledged the presence of a skills gap and the significant impact of AI on the labour market, but that much of the reviewed documents were focused on high-level data. At times, analyses were vague, and there was an overall lack of comprehensive and granular data. Further, consensus, clarity and specificity were missing with respect to which skills should be prioritized for success in AI-powered industries. There is a need for great efforts in the evaluation of new skills, policies and practices connected to AI.  

The authors identify two distinct approaches that governments have taken:  

• a more comprehensive, nationwide approach to building transferable AI skills at varying levels across the broader workforce (e.g., in the United States and Singapore) 

• a narrower approach centred around creating a smaller field of highly educated individuals rich in knowledge and proficient in advanced skills (e.g., in Canada, Sweden, and China) 

This dichotomy was also observed outside the workforce training context, with broader strategies applied at the K–12 level and narrower approaches in post-secondary.  

The authors found that talent and skills pipelines are still catching up with the implementation of AI across industries and that employers are struggling to find AI-skilled workers.  

They also concluded that countries taking a broader approach to AI-skill development, a strategy that emphasizes building more transferable skills across a wider range of skill levels, rank higher in AI readiness than those that focus on expertise and world leadership.