How to Avoid an AI Project Failure

February 25, 2022

When AI projects are successful, they provide enormous value through business insights. But many AI projects fail—why? In this episode of Data Chats, host Chris Richardson interviews Harish Krishnamurthy about the mechanics of successful AI projects. Harish Krishnamurthy is president at Sciata and has held leadership roles across P&L, sales, marketing and strategy during his tenure at IBM, Insight Enterprises and Spear Education.

The two discuss:

Early mistakes when companies begin data projects
The ideal people to include on a data team
5 Reasons why AI Projects Fail
Difference between AI projects and other data projects

Additional Resources:
Harish has written a series of white papers to help data professionals begin leveraging AI effectively in their businesses:

Continued Learning:

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Author

Pragmatic Institute

Pragmatic Institute is the transformational partner for today’s businesses, providing immediate impact through actionable and practical training for product, design and data teams. Our courses are taught by industry experts with decades of hands-on experience, and include a complete ecosystem of training, resources and community. This focus on dynamic instruction and continued learning has delivered impactful education to over 200,000 alumni worldwide over the last 30 years.

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Author:

Pragmatic Institute

Pragmatic Institute is the transformational partner for today’s businesses, providing immediate impact through actionable and practical training for product, design and data teams. Our courses are taught by industry experts with decades of hands-on experience, and include a complete ecosystem of training, resources and community. This focus on dynamic instruction and continued learning has delivered impactful education to over 200,000 alumni worldwide over the last 30 years.

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