Abstract

The implementation of artificial intelligence poses new needs and challenges for organisations. For example, organisations need to create data pipelines, develop AI models, instil new mindsets in stakeholders, and derive new kinds of value, among others. And yet, organisational resistance, incompatible organisational habits, and technical hurdles abound. One way to advance the existing research on AI implementation is to simultaneously look at 1.) the differentiating characteristics of AI, 2.) how dynamics change depending on the stage of the implementation process and 3.) the multiplicity of actors who strategise and counter-strategise against each other through the various implementation stages. Addressing these three aspects, I embark on a rare, longitudinal study of several organisations in energy and healthcare that are trying to implement AI, thus revealing the process of AI implementation from beginning to end. The research shows that stakeholders (leaders, middle managers, and end users) develop several strategic practices in response to the hurdles that appear and evolve along the AI implementation journey.

About the Speaker

Dr. Godo Ramizo Jr. has a PhD on digital technologies from the University of Oxford. He is a scholar of the digital economy, AI and algorithmic systems, and a practitioner in the tech industry. He is currently a Nanyang Presidential Fellow, the most prestigious research fellowship in Nanyang Technological University (NTU). He is the Principal Investigator of a grant worth SGD 200,000 (RMB 1.1 million), which he uses to lead international research projects on AI transformation in organisations, and user behaviour on AI systems. He has published in international journals and has presented at top conferences on digital technologies. He has been a resource speaker on the implications of digital technologies and AI for businesses at top universities and influential industry events for business executives. He has worked in Oxford research groups on the platform economy, AI, and smart cities. He also has rich industry experience. He has worked at Meta (formerly Facebook), one of the most influential technology companies in the world. At Meta’s European headquarters in London, he helped develop several innovative technology products, including machine-learning products, for Fortune500 companies. He also has experience in investment banking and as a university lecturer.