The International Labour Organization (ILO) has cautioned that indicators used to measure how exposed jobs are to artificial intelligence (AI) should not be interpreted as direct predictions of job losses. The organisation made this clear in a new research brief explaining how AI exposure tools are applied, as global concern grows over the impact of generative AI on employment.
In the report, the ILO noted that such indicators are widely used to estimate which tasks and occupations could be altered or automated by AI. However, it stressed that these measures reflect only potential exposure and should not be taken as definitive forecasts of labour market outcomes. Policymakers, it added, must combine these indicators with real employment data before drawing conclusions.
According to the report, earlier approaches centred on automation suggested that lower-skilled and routine roles were most at risk. However, newer methodologies based on AI capabilities indicate that higher-skilled occupations — including roles in business, finance, computing, and education — are also significantly exposed.
The report further highlighted that AI’s impact extends beyond individual roles. Highly exposed occupations are often linked to others through shared skills and career pathways, meaning that disruption in one area can ripple across the broader labourmarket.
Outlining the limitations of current exposure indicators, the ILO said the tools rely on fixed descriptions of existing tasks, do not account for the economic feasibility of adopting AI, and often depend on subjective assumptions. Crucially, the organisationemphasised that these indicators show what AI can do, not what it will necessarily do in practice.
The ILO advised that exposure indicators should be treated as early warning signals rather than definitive outcomes. For effective policymaking, it said they must be combined with data on employment trends, wages, job mobility, and other economic and institutional factors that shape AI adoption.
The organisation added that its objective is to support more responsible use of AI-related data and to guide the development of policies that promote fair and sustainable labour market outcomes as technology continues to reshape work.
