Artificial intelligence in the form of deep learning continues to be one of the most important developments in machine vision in recent years. Using artificial neural networks to imitate the way the human brain works for recognition and decision-making, deep learning can enhance quality inspection in manufacturing environments by addressing problems that are difficult or impossible to handle with conventional rule-based machine vision algorithms. Deep learning is particularly good at object classification and the detection and segmentation of defects and has been deployed in many industries including automotive, aerospace, logistics, pharmaceuticals, semiconductor and traffic. It is also especially effective in sectors such as food and agriculture, since organic products have many natural variations that must be taken into account when assessing potential defects and classification issues. Deep learning is now more user-friendly and practical than ever and together with other vision technologies opens up new application areas, making the inclusion of vision inspection as part of Industry 4.0 even more beneficial.