Submitted by Siddhartha Ray Barua.
Abstract: Many companies are increasing their focus on Artificial Intelligence as they incorporate Machine Learning and Cognitive technologies into their current offerings. Industries ranging from healthcare, pharmaceuticals, finance, automotive, retail, manufacturing and so many others are all trying to deploy and scale enterprise Al systems while reducing their risk. Companies regularly struggle with finding appropriate and applicable use cases around Artificial Intelligence and Machine Learning projects. The field of Artificial Intelligence has a rich set of literature for modeling of technical systems that implement Machine Learning and Deep Learning methods. This thesis attempts to connect the literature for business and technology and for evolution and adoption of technology to the emergent properties of Artificial Intelligence systems. The aim of this research is to identify high and low value market segments and use cases within the industries, prognosticate the evolution of different Al technologies and begin to outline the implications of commercialization of such technologies for various stakeholders. This thesis also provides a framework to better prepare business owners to commercialize Artificial Intelligence technologies to satisfy their strategic goals.
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