Machine learning (ML) and artificial intelligence (AI) technologies can be used to address many of the identified targets of digital innovation, namely improved customer experience, security, efficiency, and sustainability, by complementing human abilities in a variety of areas, such as perception and understanding, reasoning and problem-solving, learning an, and interaction with the surroundings and with people. The fields of application range from robotic process automation (RPA) and robotic desktop automation (RDA) to expert systems, chatbots, assistants, and autonomous systems such as industrial robots and cars.
Nevertheless, despite the recent surge in new AI initiatives, companies often struggle to scale up solutions. Given the various current crises, organizations are expected to reduce costs, which is why the use of ML and AI tools to enable optimization and automation will accelerate in the short run. AI-enabled solutions can help to analyze large amounts of data from various sources and improve efficiency in processes related to supply chains or production and operation. This allows companies to reduce their energy and resource consumption. In addition, increased automation not only helps to increase efficiency and reduce failure rates, but also to mitigate the omnipresent skill shortage.