Jobs of Tomorrow Technology and the Future of the Worlds Largest Workforces 2025

The agriculture workforce is by far the world’s largest, making up a quarter of total global employment. This workforce is far more prominent in lower-income economies, comprising 57% of workers in low-income economies and 39% of workers in lower-middle-income economies, compared to 20% of workers in upper-middle- income economies and just 3% of workers in high-income economies. The four workforce transformation technologies could reform the way this workforce operates. Technology is already transforming demands on the agriculture workforce, although its impact varies significantly between regions and activities. For example, agricultural drones are being used in South America to transport cut banana bunches from steep hillside plantations. This technology enables drastic increases in the number of bunches a worker can harvest, with resulting increases in productivity and improvements in safety. Precision agriculture, meanwhile, is being applied to a variety of cropping operations. Powered by drones, network technology and AI-driven analytics, it allows farmers to monitor soil health, water use and crop conditions in real time. This reduces reliance on manual labour for routine monitoring and creates demand for new roles, such as drone operators, data analysts and agritech technicians. Automation and robotics are also redefining on-farm labour by reducing dependence on seasonal and manual workers. Autonomous tractors, robotic harvesters and automated irrigation systems are being deployed across regions such as Europe and North America to address labour shortages and enhance productivity. These technologies have significant productivity potential for farming operations with the resources to fund capital investment and could significantly change the expertise required of the workforce operating these systems. A significant proportion of this workforce, however, are smallholder farmers in lower-income countries where investment capacity is likely to be limited. Enabling global benefits of technology, therefore, requires interventions to support global technological diffusion, although this too comes with risks of displacing employment for vulnerable populations. Manufacturing represents the world’s second- largest workforce, making up 14% of total global employment. This employment is particularly prominent in some Asian countries, including China, Viet Nam, and Taiwan, China, and European countries, including Czechia, Slovenia and Hungary. The type of manufacturing differs substantially by industry and region. Textiles, automobiles and pharmaceuticals form distinct manufacturing hubs in different countries and regions around the world. These manufacturing hubs also differ significantly in demographic makeup.10 These differences have implications for the types of technology adoption possible and the current levels of infrastructure. Robotics systems incorporating AI are especially relevant for the manufacturing workforce, with the potential to significantly enhance human capability alongside the possibility of eliminating significant amounts of work through automation. The path of technology development and adoption will determine whether this technology leads to repetitive low-value tasks being replaced by higher-value activities or a reduction in total employment.While robotics has been adopted in manufacturing processes for a long time, physical AI is increasingly enhancing the capabilities of these systems. Several cutting-edge use cases illustrate how this technology, combined with robotics, could transform the manufacturing workforce.11 For example, AI- enabled visual quality control inspections, combined with autonomous root cause analysis and process mining, identify factory line issues much faster than current quality control processes. Similarly, integrated mobile robots, AI-based sorting and genAI-guided manipulators to fulfil e-commerce orders can enable faster delivery, increase the demand for skilled roles and create efficiency gains.12 These AI incorporations into existing manufacturing processes could transform jobs into higher-productivity roles with higher expertise requirements. The amount of productivity enhancement, and whether this is accompanied by an increase or decrease in demand for workers, will depend on several factors, including methods of adoption, investment capacity and existing manufacturing infrastructure.2.2 Manufacturing Integrated mobile robots, AI-based sorting and genAI-guided manipulators can enable faster delivery, increase the demand for skilled roles and create efficiency gains.2.1 Agriculture Jobs of Tomorrow: Technology and the Future of the World’s Largest Workforces 9