Understanding Opinions and Emotions of Generative Artificial Intelligence Assets Using the Gartner Hype Cycle and the Kübler-Ross Change Curve

Asset management today encompasses not just on-premises properties but also cloud services. Companies have been adopting software services like Office 365 or Google Apps and managing them as assets for over a decade. Adopting those assets into their organisations often requires time, technically, managerially and psychologically. It is well known that for digital transformation projects to be successful, organisations and their workers must be ready in advance. It is now the age of Generative Artificial Intelligence (AI) assets such as ChatGPT, Bing AI Enterprise, and Microsoft Office Copilot. Understanding the opinions and emotions about such assets in organisations will aid in the consolidation of our theories of technology acceptance and will guide businesses in their technology adoption. Based on the Gartner Hype Cycle and the Kübler-Ross Change Curve, this study hypothesises that the process of adopting generative AI assets into organisations will go through stages of technology trigger, the peak of inflated expectations, the trough of disillusionment, the slope of enlightenment, and the plateau of productivity, while at the same time passing through the feelings of shock, denial, frustration, depression, experiment, decision and integration. Using the sentiment and emotion analysis approach, this study collected a significant number of tweets from X (formerly Twitter) and then quantised their contents into sentiment scores and emotions to validate these hypotheses. Prior research has shown the binary sentiment landscape at a single point in time but not the range of sentimental scores and multilevel emotions over some time, and consequently could not demonstrate the complete process of hyping and adopting as envisioned by the Gartner Hype Cycle and the Kübler-Ross Change Curve. Additionally, previous research examined the adoption of new technology from the perspective of information seekers, but not from that of information creators. Furthermore, because generative AI services have just recently been released for public use, there is still a gap in our knowledge of their receptive and adaptive responses. Theoretically, this study contributed to the empirical confirmation of the Gartner Hype Cycle and the Kübler-Ross Change Curve in adopting generative AI assets. In practice, it aids organisations in the process of planning the technical implementation of new generative AI assets together with their managerial and psychological training to increase company-wide productivity.