Many enterprise leaders have taken a “Field of Dreams” approach to AI ROI — “If we build it, profits will come.” While it’s one thing to take that approach for smaller pilot projects, it’s another thing when you’re consistently being asked to fund initiatives with seven-figure price tags.
Few are able to answer basic questions such as “What’s the ROI of our AI investments?” or “What’s the exposure to our AI compliance risks?”
Is the best practice for Enterprise AI to keep ModelOps independent from data science in both practice and platform?
Welcome to the next post in the series about living life off the grid in the mountains of Colorado while working as the CTO of ModelOp.
Through ModelOps, teams can be positioned to fully unleash the value of their AI investments, while addressing requirements to boost trust and minimize risk.
This article shares some insights and recommendations on how to manage AI programs in a way that improves performance and profitability.
Many enterprise leaders have taken a “Field of Dreams” approach to AI ROI — “If we build it, profits will come.” While it’s one thing to take that approach for smaller pilot projects, it’s another thing when you’re consistently being asked to fund initiatives with seven-figure price tags.
Few are able to answer basic questions such as “What’s the ROI of our AI investments?” or “What’s the exposure to our AI compliance risks?”
Is the best practice for Enterprise AI to keep ModelOps independent from data science in both practice and platform?
Welcome to the next post in the series about living life off the grid in the mountains of Colorado while working as the CTO of ModelOp.
Through ModelOps, teams can be positioned to fully unleash the value of their AI investments, while addressing requirements to boost trust and minimize risk.
This article shares some insights and recommendations on how to manage AI programs in a way that improves performance and profitability.
