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The emergence of technologies such as (AI) AI refers to systems that display intelligent behaviour by analysing their environment and taking actions – with some degree of autonomy – to achieve specific goals. AI-based systems can be purely software-based, acting in the virtual world (e.g. voice assistants, image analysis software, search engines, speech and face recognition systems) or AI can be embedded in hardware devices (e.g. advanced robots, autonomous cars, drones or Internet of things applications). , Machine learning is a branch of artificial intelligence dealing with how computers can learn, grow and improve on their own from data without human intervention. , Wearables are electronic devices with sensors and computational capacity (e.g. smart watches, data glasses, or other devices with embedded sensors or tags), which can be placed on different body parts to gather data to be fed into other digital systems for processing purposes. They can be used to analyse physiological and psychological data such as feelings, sleep, movements, heart rate, body temperature and blood pressure, via applications either installed on the device itself or on external devices, such as smartphones connected to the cloud. , and Datasets characterised by volume (large size), velocity (constantly growing), and variety (structured and unstructured form such as texts), which are often used by artificial intelligence machines. applications, among others, and their increasing uptake in the workplace are changing the landscape of OSH monitoring. 

The overall success of new OSH monitoring systems will rely on the effective communication of available research and data, sustained efforts towards standardisation across the EU and inclusive implementation processes. Worker privacy and data protection are key priorities in the broader discussions on ensuring OSH safety at the national and EU levels.