Technology Roadmapping: Data Science Roadmapping of Networked Organizations’ Strategic Planning for Artificial Intelligence

With the increasing computational power and availability of scalable distributed technologies, big data has become a critical asset for for-profit and nonprofit organizations, which leverage data science to build artificial intelligence (AI) systems. The latest developments call for human-centric, iterative, continuous, and perhaps transparent planning actions to evaluate and align AI systems considering the interconnected data-related, political, technological, and societal viewpoints beyond the organizational level with the participation of multiple for-profit and nonprofit organizations or governments. The emerging data science roadmapping (DSR), developed by customizing technology roadmapping, can enable such initiatives because it provides a human-centric and agile platform incorporating data layers as strategic planning elements considering the data science life cycle. However, the technology management literature must exemplify its adaptations beyond the organizational level in more diverse planning scenarios for data and AI professionals to plan well-coordinated operations at the industrial and governmental divisions by considering the interconnected technological, political, and sociological perspectives. Accordingly, this chapter explores the pseudo case study of the networked organizations’ strategic planning for AI by customizing DSR beyond the organizational level. We synthesize technology management literature with experiment-based best practices from the industry in a human-centric process, revealing implications for research and practice.