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By John Thomas, IBM Distinguished Engineer
As they journey toward AI, most organizations establish data science teams staffed with people skilled in ML/DL algorithms, frameworks and techniques. Yet, many of those organizations struggle to make their AI projects truly relevant to the business, instead failing to get the projects into full production and integrated with existing applications and processes. It’s why so many line-of-business stakeholders consider only a small percentage of AI projects to be true successes.