Lessons Learned from AI Project Failures

Tue. November 16, 2021 @ 11:30 ET

Featured Speakers: Kathleen Walch and Ron Schmelzer, Managing Partners and Principal Analysts at Cognilytica

Far too often, organizations are running data and AI projects without following established best practices and taking the right steps to ensure their success. Decades ago, we learned how to run application development projects using best-practice agile and iterative approaches. However, many organizations are failing to apply similar best practices to their data-centric projects. Without a proper approach that standardizes steps for data preparation, data identification, and data protection, it’s hard to achieve the success you’re expecting.

 

In this presentation we’ll walk through a data and AI best-practice methodology to provide you with the foundation needed for project success, especially as you incorporate advanced analytics and AI projects. The CPMAI methodology is the industry’s best practice for AI & ML projects.

About Data for AI:

The Data for AI Community is geared toward innovative companies pushing the boundaries of what’s possible with Artificial Intelligence and cognitive technologies. This community is focused on the data side of AI including: Data Engineering, Data Preparation, Data Labeling & Annotation, Sourcing and Generating Data, and All Other Topics Data-Related for AI. Join us at this monthly event for high-quality content with compelling & informative speakers and opportunities to network and connect with fellow like-minded individuals. ​

Featured Presenters

Kathleen Walch

Kathleen Walch, Executive Director, GovFuture Kathleen is a serial entrepreneur, savvy marketer, AI and Machine Learning expert, and tech industry connector. She is an executive

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Ronald Schmelzer

Ronald Schmelzer, Executive Director, GovFuture Ron is an Executive Director at GovFuture, a community of government innovators. He is also principal analyst, managing partner, and

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