How to stop AI project failure! | CXOTalk #840

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AI Summary

Episode 8840 of CXO Talk Summary

Host: Michael Krigsman

Guest: Saul Rashidi

Background:

• Saul Rashidi has held various executive roles, including Chief Analytics Officer at Estee Lauder, Chief Data and Analytics Officer at Merc, Chief Digital Officer at Sony Music, and Chief Data and Cognitive Officer at Royal Caribbean.
• Saul has authored a new book titled “Your AI Survival Guide: Scraped Knees, Bruised Elbows, and Lessons Learned from Real-World AI Deployments.”

Key Points:

• AI projects often follow a standard flow: establish an AI strategy, identify use cases, form a team, design, and deploy.
• Common mistakes include poor strategy, wrong use case selection, and inability to scale Proof of Concepts (POCs) to production.
• Saul’s book outlines how to avoid these mistakes and provides a framework for AI project success.
• Selecting use cases based on business value alone is flawed; other factors like competitive threats, regulations, and market conditions should be considered.
• AI projects require a different approach than traditional IT projects, including top-down leadership due to resistance and fear.
• AI is not suitable for solving every problem; discernment is needed to apply AI appropriately.
• AI applications are a “live wire,” requiring ongoing tuning and human oversight post-deployment.
• Pilot Purgatory is a common issue where AI initiatives fail to move beyond the POC stage.
• The book introduces a criticality vs. complexity framework to help select the right AI use cases.
• AI projects require a cultural and mindset shift within organizations, emphasizing the need for active participation and management of AI applications.

Audience Interaction:

• Viewers engaged with Saul through questions on Twitter and LinkedIn, discussing topics like overcoming organizational tensions, managing pilot purgatory, and the importance of data in AI projects.

Conclusion:

• Saul emphasizes the importance of informed decision-making, realistic expectations, and strategic planning in AI initiatives.
• The discussion highlighted the unique challenges of AI projects and the need for a practical approach to ensure successful deployment and scaling.

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