The latest KDnuggets poll reconfirms today's dire industry buzz: Very few machine learning models actually get deployed. In this article, I'll summarize the poll results and argue that this pervasive failure of ML projects comes from a lack of prudent leadership. I'll also argue that MLops is not the fundamental missing ingredient – instead, an effective ML leadership practice must be the dog that wags the model-integration tail. Considering the growing chatter about ML's failure to launch, there's been relatively little concrete industry research – especially when it comes to surveys on model deployment in particular rather than ROI in general – so I proposed this poll to Gregory Piatetsky and Matthew Mayo of KDnuggets. They helped me formulate and wordsmith it.

It could be said that we humans have a strange, even somewhat strained, relationship with our technology. Even deep thought poster children like Plato fretted that a newfangled medium called "writing" would cause the end of intelligent debate. Today, of course, being literate is simply table stakes, with an estimated 86 percent of the world's population able to read and write. No doubt we could find a troll or two to advise (in writing) that literacy is the cause of society's ills, but overall, I'd say the introduction of that particular technology seems to have worked out alright in the end. This overarching question of whether technology will save or destroy us now includes many innovations that we now take for granted.