Machine Learning at Enterprise Scale

Introduction

Machine learning. Seemingly everyone is doing it. And, if your company isn’t investing in the skilled people and specialized tools needed to develop and deploy machine learning models, you’re probably behind your competitors. Machine learning adoption was already high in 2017, at 58% according to a Deloitte survey of large enterprises, and it grew by five percentage points in 2018, to 63% of all respondents.

To get a sense of how fast businesses are adopting machine learning, IDC predicts that artificial intelligence (AI) spending (which encompasses machine learning) will grow to $52.2 billion by 2021. This represents a rather astounding compound annual growth rate (CAGR) of 46.2% within the 2016 to 2021 forecast period. This means that spending is increasing by nearly half again each year for five years.

Another sign that enterprise adoption of AI in general and machine learning in particular are increasing is that job titles specific to machine learning are already widely used at organizations with extensive experience in data science. According to O’Reilly’s 2018 survey “The State of Machine Learning Adoption in the Enterprise”, 81% of such businesses employ “data scientists.” Thirty-nine percent of enterprises employ “machine learning engineers.” And 20% employ “deep learning engineers.”

These activities seem to be paying off. A recent Deloitte study found that the linkage between the successful application of machine learning ...