MIT Sloan Center for Information Systems Research (CISR)

Abstract:
AI adoption is now widespread—but adoption is not the same as value creation. AI foundation models and agents are capabilities that every one of your competitors can also leverage. The winners, then, may not be the fastest adopters, but the …

Abstract:
AI adoption is now widespread—but adoption is not the same as value creation. AI foundation models and agents are capabilities that every one of your competitors can also leverage. The winners, then, may not be the fastest adopters, but the …

Abstract:
AI adoption is now widespread—but adoption is not the same as value creation. AI foundation models and agents are capabilities that every one of your competitors can also leverage. The winners, then, may not be the fastest adopters, but the …

Abstract:
How can midsize firms create and capture value within ecosystems dominated by technology giants? Belden’s transformation from a manufacturer of industrial networking components to a provider of data-powered solutions required the company to …

Abstract:
Over a decade of collaboration between MIT CISR researchers and the MIT CISR Data Research Advisory Board has produced a research model that explains how organizations translate data assets into financial performance. The model traces a caus…

Abstract:
This model explains the causal chain of how data monetization drives financial performance.

Publication date: 2026-07-16

Publication type: Framework

Publication authors:
Nick van der Meulen
,
Barbara H. Wixom

Abstract:
Over a decade of collaboration between MIT CISR researchers and the MIT CISR Data Research Advisory Board has produced a research model that explains how organizations translate data assets into financial performance. The model traces a caus…

Abstract:
Over a decade of collaboration between MIT CISR researchers and the MIT CISR Data Research Advisory Board has produced a research model that explains how organizations translate data assets into financial performance. The model traces a caus…

Abstract:
One of the biggest challenges companies face today is designing decision rights between humans and AI. For example, should AI be used in hiring, and if so, for which tasks? Should AI run marketing campaigns end to end, or augment human judgm…

Abstract:
One of the biggest challenges companies face today is designing decision rights between humans and AI. For example, should AI be used in hiring, and if so, for which tasks? Should AI run marketing campaigns end to end, or augment human judgm…

Abstract:
One of the biggest challenges companies face today is designing decision rights between humans and AI. For example, should AI be used in hiring, and if so, for which tasks? Should AI run marketing campaigns end to end, or augment human judgm…

Abstract:
One of the biggest challenges companies face today is designing decision rights between humans and AI. For example, should AI be used in hiring, and if so, for which tasks? Should AI run marketing campaigns end to end, or augment human judgm…