Achieving AI at Scale: Cemex’s Learning Journey
Name
2024_0701_CemexScalingAI_WixomSomehBeath.pdf
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206.33 KB
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Adobe PDF
Checksum (MD5)
542d8f7ed0285e63c1036f18fedd26d0
Author(s)
Wixom, Barbara H.
Someh, Ida A.
Beath, Cynthia M.
Date Issued
July 18, 2024
Publisher
Cambridge, Mass.: Center for Information Systems Research, Sloan School of Management, Massachusetts Institute of Technology
Citation
Wixom, Barbara H., Ida A. Someh, and Cynthia M. Beath. “Achieving AI at Scale: Cemex’s Learning Journey.” MIT CISR Research Briefing Volume XXIV, no. 7 (July 2024). https://dspace.mit.edu/handle/1721.1/174932.
Series/Report no.
MIT CISR Research Briefing, Vol. XXIV, No. 7
Abstract
In recent years, large established organizations have been growing business value by increasing the volume of AI models they have in production, an activity we call scaling AI. MIT CISR research has identified that scaling AI is the result of a learning journey during which an organization learns how to deploy, proliferate, and industrialize AI models. Ideally, the organization builds data liquidity, develops workforce savviness, and leverages scarce resources along the way to achieve AI at scale, which is the state at which organizations cost effectively manage large volumes of interconnected models in production. In this briefing, we describe the AI scaling learning journey at Cemex, a large global construction materials company headquartered near Monterrey, Mexico.
Subjects
Data monetization
Information Technologies
Innovation and Strategy
Organizational Structure and Agility
Data, AI, and Analytics
Terms of Use
CC BY-NC 4.0 (Attribution-NonCommercial 4.0 International)
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