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This chapter focuses on common business challenges where intelligent choices and behaviors may lead to new and different outcomes. The business stories represent a wide range of economic sectors, types of organizations, and challenges. Each story highlights the role the framework plays in deriving and realizing an intelligent solution.

Energy production and distribution is undergoing a revolutionary transition with the advent of disruptive technologies such as the Internet of Energy (IoE), 5G and artificial intelligence (AI). IoE essentially involves automating and enhancing the energy infrastructure: the power grid from grid operators to energy generators and distribution utilities. The IoE also relies on powerful connectivity networks such as 5G, big data analytics and AI to optimise its operation. By incorporating the technology that employs ubiquitous devices such as smartphones, tablets or smart electric vehicles, it will be possible to fully exploit the potential of IoE using 5G networks. 5G networks will provide high speed connections between devices such as drones, tractors and cloud networks, to transfer huge amounts of sensor data. Additionally, there are many sources of isolated data across the main energy production units (generation, transmission and distribution), and the data is increasing at phenomenal rates. By applying AI to these data, major improvements can be brought at each stage of the energy production chain. Tying renewable energy to the telecommunications sector and leveraging on the potential of data analytics is something which is gaining major attention among researchers and industry experts. This chapter therefore explores the combination of three of the most promising technologies i.e. IoE, 5G and AI for achieving affordable and clean energy, which is SDG 7 in the UN Sustainable Development Goals (SDGs).

The contemporary dynamics impose companies to both innovate and internationalize at the same time while remaining competitive in the international marketplace. With this context in mind, Industry 4.0 technologies have the potential to increase the competitiveness of companies, leading to a new era of “Manufacturing Renaissance.” Recently, conceptual studies have speculated on possible impacts of the adoption of Industry 4.0 technologies in terms of international business. However, empirical studies on this topic are still lacking. Through a multiple case study approach, this study presents exploratory qualitative research investigating the relationship between Industry 4.0 and the internationalization of companies. The analysis of 16 Italian manufacturing exporting companies, which have adopted some of these technologies, has revealed a more intriguing relationship compared to the one presented in current literature, and thus has opened avenues for future research on this issue.

This chapter provides an overview of the potential use of Intelligent Transport Systems (ITS) and associated artificial intelligence (AI) techniques in the land transport sector in an attempt to achieve related United Nations Sustainable Development Goals (SDGs) targets. ITS applications that have now been extensively tested worldwide and have become part of the everyday transport toolkit available to practitioners have been discussed. AI techniques applied successfully in specific ITS applications such as automatic traffic control systems, real-time image processing, automatic incident detection, safety management, road condition assessment, asset management and traffic enforcement systems have been identified. These methods have helped to provide traffic engineers and transport planners with novel ways to improve safety, mobility, accessibility and efficiency in the sector and thus move closer to achieving the various SDG targets pertaining to transportation.