The future technical standard of sixth-generation (6G) technology for wireless communications has accelerated the arrival of interconnected autonomous systems and other sensing devices in a wide range of industrial zones, such as smart factories, smart farms, and cognitive cities, among others. The imminent digitalization of these ecosystems has created highly dynamic environments that demand real-time decisions, making it difficult for humans to keep up with all their details. These dynamic scenarios require planning and execution that is more precise and faster than the speed at which data is acquired. The use of Artificial Intelligence (AI) offers high potential to enable the monitoring and assessment of multi-modal sensor data at a superhuman level, leading to faster decisions with better precision, which reduces undesired automated behavior, while enabling new forms of interaction. This chapter describes techniques, software frameworks, compilation flows, and hardware infrastructure for achieving large-scale, energy-efficient, trustworthy, real-time, and distributed AI in the newly developed era of 6G ecosystems, which produce vast amounts of data. The chapter also describes an economic perspective on the challenges in achieving this vision.