Will Artificial Intelligence Automate Theory Building? Are there Lessons for Academia from Practice?

To stay competitive, organizations are being challenged to gather vast amounts of data generated from daily operations and customer interactions. Managers have shifted from making decisions that are supported by information systems reporting and intuition to making decisions that are driven by evidence from data. With the lower cost of acquiring data, the proliferation of easy to use data analytics tools and demands for rapid action, firms struggle whether to wait for academia to endorse scholarly theories or to adopt data-driven decisions. This panel serves as a conversation on a way forward for IS researchers. The panelists represent industry experts who can provide their perspective from large data driven companies in Silicon Valley and scholars that have both theoretical and practical research experience in theory development, IT value and adoption, big data and design science. [ABSTRACT FROM AUTHOR]