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This chapter provides the background and relevant policy context information necessary to understand the approach to development and implementation of tailored gender equality plans provided by the TARGET project. It describes the development of European gender equality polices in research and innovation (R&I) since the 1980s and experiences with early structural change projects. TARGET refers to these experiences and aims at providing an innovative approach to overcome challenges towards gender equality, especially for research organisations located in countries that have been classified as rather inactive when it comes to gender equality policies in R&I. The chapter closes with an outline of the structure of the book and its individual chapters.

The case of Africa is important in understanding the growth of research management as a profession. Africa has rapidly increased its research output in recent years, and its institutions are increasingly in demand as research partners. Yet research management structures have developed from a very low base, and need not be confined by past practice. Through the Southern African Research and Innovation Management Association (SARIMA), it has been represented since the origins of International Networks of Research Management Societies (INORMS). Several external donors have sought to help build research management structures on the continent, and the success (or otherwise) of these initiatives can tell us much about the potential for common research management structures globally.

This chapter does not provide a comprehensive account of progress over the past two decades, or a complete list of relevant initiatives. Rather, it reflects on whether international assistance and collaboration have made a meaningful contribution to the progress that has been made, and its strengths and limitations. It considers how far growth would have happened regardless of funder intervention, or indeed whether international partners have inhibited progress by prioritising their own norms and priorities. It asks uncomfortable questions for funders about the way in which they plan and evaluate their work.

This chapter insists that local cocreation projects need not only good intentions and the hard work of volunteers but also require funding and financing of the design and implementation of new solutions. It draws a conceptual distinction between funding and financing and explains who may help to provide funding and financing and why they may do so. As a part of this discussion, attention is drawn to the importance of writing good and persuasive funding applications and drawing up a strong and convincing business case to secure financing of new solutions. The new and emerging strategy for mobilizing private capital to help finance SDG projects is explained and illustrated, before closing the chapter with a discussion of the need to develop a proper system for fiscal accounting and auditing, which can prevent mismanagement and misconduct that eventually undermine popular support for local SDG projects.

Organizations across industries are increasingly using Artificial Intelligence (AI) systems to support their innovation processes, supply chains, marketing and sales and other business functions. Implementing AI, firms report efficiency gains from automation and enhanced decision-making thanks to more relevant, accurate and timely predictions. By exposing the benefits of digitizing everything, COVID-19 has only accelerated these processes. Recognizing the growing importance of AI and its pervasive impact, this chapter defines the “social value of AI” as the combined value derived from AI adoption by multiple stakeholders of an organization. To this end, we discuss the benefits and costs of AI for a business-to-business (B2B) firm and its internal, external and societal stakeholders. Being mindful of legal and ethical concerns, we expect the social value of AI to increase over time as the barriers for adoption go down, technology costs decrease, and more stakeholders capture the value from AI. We identify the contributions to the social value of AI, by highlighting the benefits of AI for different actors in the organization, business consumers, supply chain partners and society at large. This chapter also offers future research opportunities, as well as practical implications of the AI adoption by a variety of stakeholders.