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Working Paper: Research Summary

Explanation: A New Enterprise Data Monetization Capability for AI

AI’s opaqueness, malleability, iffiness, and unproven nature require that companies build an enterprise data monetization capability termed “explanation.”
RESEARCH SUMMARY

A summary of a research project with preliminary findings

Abstract

Artificial intelligence (AI) offers huge potential benefits for companies around the world. Companies that learn how to develop and deploy AI effectively will be positioned to maximize value creation in the emerging algorithmic economy, where algorithms will enable key business activities. Uptake of AI has been limited, however, and there are mounting associated concerns. This report explores what companies need to better understand about AI so they can make the most of this transformational phenomenon. The report describes distinct AI characteristics and their implications for enterprise data monetization capabilities, including a new requisite capability termed explanation.

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About the Authors

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Ida Someh, Lecturer in Business Information Systems, UQ Business School at The University of Queensland, Australia

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Angela Zutavern, Managing Director, AlixPartners

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Cynthia Beath, Professor Emerita, University of Texas at Austin

MIT SLOAN CENTER FOR INFORMATION SYSTEMS RESEARCH 

Founded in 1974 and grounded in the MIT tradition of rigorous field-based research, MIT CISR helps executives meet the challenge of leading dynamic, global, and information-intensive organizations. Through research, teaching, and events, the center stimulates interaction among scholars, students, and practitioners. More than ninety firms sponsor our work and participate in our consortium. 

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