Industry 4.0 technology (I4.0) is inescapable. It transforms the way businesses and customers interact and revolutionizes how organizations produce goods and services (SAP Insights, 2020). It requires a level of agility that many organizations do not possess. Defending against disruptive business models is no longer enough. Organizations must be nimble to optimize assets and resources in response to adversity. In March 2020, the coronavirus (COVID-19) pandemic ushered a devastating blow to the U.S. economy and job market with pervasive shocks that continue to be a business threat. In response, many organizations are accelerating automation, digitization, and communication capabilities to close the gap and connect with customers.

This dissertation examined the cross-industry adoption of the nine most common Industry 4.0 technologies: big data, artificial intelligence, cloud computing, the internet of things, cybersecurity, 3-D printing, autonomous technology, augmented reality, and blockchain. This descriptive study explored factors of I4.0 adoption across industries and organizational sizes during a national pandemic.

The study sought to reveal “what” factors contributed to the adoption of Industry 4.0, “what” industry patterns exist, “what” effect COVID-19 had on these concepts. A quantitative method was used to examine the relationship between factors. An online survey was administered to a Qualtrics panel of 520 business owners and executives to capture perceptions, knowledge, and insights. A binary logistic regression analysis was performed. The results of this study inform a cross-industry framework of I4.0 technology adoption, which includes contributing factors. The findings also showed COVID-19 was less an accelerant of adoption but rather, the industry sector was a greater influencer.