The twin transition: AI use in manufacturing

The ILO recently released “AI in manufacturing: Challenges and opportunities for promoting decent work, productivity and a just transition” (10 March 2026), where they present their findings on the impacts of AI on manufacturing work - prepared for the latest meeting of the ILO’s Governing Body.

Human Level’s Take:

• So far, adoption of AI in manufacturing has been slow, but growth is coming. The market for AI in manufacturing is projected to grow more than sixfold, from US$23.4 billion in 2024 to US$155 billion by 2040. The speed of this transition will depend on access to data, computing power, connectivity and workers’ skills.
• As AI deployment moves to the factory floor, companies will need to start considering its positive and negative impacts on both business and the workforce. In particular, impacts on workers will begin to have human rights and sustainability implications, as workers face new and less visible risks, e.g., from algorithmic management and worker surveillance to job displacement and bias. These risks are likely to be most acute for vulnerable and informal workers.
• The ILO’s report is one of the first to assess what these impacts are looking like in the sector, and to propose how responsible business conduct standards can be applied to manage the AI transition’s impacts on manufacturing workers.
• Companies can begin with engaging suppliers to discuss how these technologies are being deployed, how decisions affecting workers are made, and whether workers or their representatives have a voice in these processes.
• This approach to the transition can benefit industry, as companies and manufacturers benefit from investing in re-skilling and up-skilling of workers – reinforcing productivity, resilience and decent work outcomes.
• At the same time – as the ILO recognises – many of these challenges cannot be addressed by individual companies. Industry collaboration, engagement with governments and alignment with worker representatives will be key to shaping an enabling environment for effective and ‘just’ AI adoption in production.

Some key takeaways

1. Manufacturing is changing globally, including because of AI. Manufacturing remains a cornerstone of the global economy, accounting for 16.5% of global GDP and over half of world trade in 2024. However, in recent years, the sector has been reshaped by intersecting changes: demographic shifts, climate transition demands (with manufacturing responsible for 25% of direct GHG emissions), rising geopolitical fragmentation (trade restrictions doubled between 2020 and 2024) and rapid technological advances in AI and automation. While still in its early stages of adoption, AI is already being used in manufacturing across design, production, logistics and supply chain management. So far, impacts on cost savings and revenues have been modest (10% and 5% respectively), but growth in its use – and its impacts – is coming. The market for AI in manufacturing is projected to grow more than sixfold, from US$23.4 billion in 2024 to US$155 billion by 2040. The speed of AI adoption will depend on the wider digital transformation, as well as on access to data, computing power, connectivity and workers’ skills.

2. Challenges and opportunities for workers and production. The ILO acknowledges that the AI transition in manufacturing, while in its infancy, is already creating new risks and opportunities for industrial development and for workers. On the one hand, while AI can be used to complement and enhance work, it can also substitute particular tasks, leading to job transformation and job displacement. Specifically, it is likely to displace workers in repetitive or manual roles, potentially initially leading to unemployment or worker displacement to lower-quality jobs. Also, there are reports of AI having other negative impacts for workers in manufacturing, such as: (1) higher worker intensity from algorithmic management, surveillance and data-driven performance systems (e.g., in the automotive sectors in Argentina and Malaysia); (2) impacts on wages from CV screening or work monitoring; (3) mental health risks linked to digital monitoring and algorithmic management; and (4) discrimination from biased data and algorithms. At the same time, AI can have positive impacts like new job creation (e.g., in maintenance, automation and data analysis), with better working conditions and higher pay. AI can also improve work safety by reducing repetitive tasks, increasing worker engagement, predicting workplace accidents, personalising training and enabling monitoring of workers’ health.

3. A just transition to AI use in manufacturing. Preventing risks and ensuring positive outcomes for the workforce in the deployment of AI in manufacturing will require deliberate focus on skills, worker participation and human-centred design to prevent widening inequalities and support fair transitions for affected workers. The ILO explicitly recommends that companies embed responsible business conduct principles at the core of AI adoption. This starts with assessing workforce impacts, including which roles are most exposed and how different deployment models (from task-specific to plant-wide systems) shape outcomes. Impacts will vary across geographies, genders and employment types - particularly for more vulnerable part-time workers, temporary and sub-contracted workers, self-employed workers and those with unclear employment relationships. Additionally, social dialogue and worker engagement is seen as crucial to shaping how work is reorganised, helping to protect job quality and build trust. Finally, rapidly shifting skills demands require that businesses coordinate efforts with governments and educational institutions to support lifelong learning, with a strong focus on inclusion, particularly for women and older workers, to ensure the benefits of AI are broadly distributed. The report also acknowledges the importance of the broader enabling environment, shaped by governments’ policy frameworks, social protection systems, access to finance and markets, infrastructure, education and business development services. Governments are specifically asked to apply ILO Convention No. 122 to the digital and AI transition by enacting employment policies to manage the transition with time-bound, measurable targets and coordination.