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AI Product Research Series: Avoiding AI Fails

#AIFails are everywhere and, while there's a lot of technical talk online, very few resources are available for software product leaders.  [From our whitepaper] “Humorous and sometimes frightening examples like these are a regular sighting on social media:


With all these pressures on software product companies, it’s not surprising that agile and lean methodologies are such hot topics. What many of us practitioners have realized is that there is no one process that works for every organization. And, different processes are more effective for different software product efforts.  

Herein lies our challenge... instead of adopting all the practices of a single methodology, real-world execution is about understanding the morphology of the software product we plan to launch and applying the right practices; either:

  • Choosing off-the-shelf practices that work best for our organization, or

  • Inventing practices that leverage our company’s unique capabilities and culture.

Our experience in the past two decades as product and technology leaders at software companies and as consultants has shown that AI products are a unique lot. Since there are few off-the-shelf methodologies that apply directly to data science projects, we hope our practices will help you avoid mistakes before you make them.”

Keep your eyes on this blog to continue this story, or better yet, download our whitepaper, Research & Validation for AI Products today!