«  Return to all blog entries

Sentiments, Deployments, and Adoption Plans for Data Science and Machine Learning

Data science and machine learning technologies include statistics, modeling, machine learning, and data mining to analyze facts to make predictions about future or otherwise unknown events.

In general, these technologies are fairly new to most organizations and the market for them remains nascent. Most respondents report using data science and machine learning for two years or less.

But the perceived overall importance of data science and machine learning increases rapidly. Significant pockets of adoption exist, especially in the largest organizations, and respondents report increasing planned adoption rates during the next two years.

Executive Summary

1. Industry importance of data science and machine learning technologies is very high in anticipation of future use. User-perceived importance lags this level of “importance.” The gap between these two perceptions reflects the nascent nature of the market.

2. Deployments of data science and machine learning technologies slowly gain traction, especially in large organizations. R&D is most involved.

3. Executives represent the second-largest group of current users of these technologies. With the ability to influence future investments and deployments significantly, executive use represents an interesting barometer to watch in coming years. 

4. More than half of non-adopters plan to adopt this year or next. Over time, planned adoption among those that haven’t yet deployed data science and machine learning remains fairly flat.

5. The largest organizations are most likely to have both implemented data science and machine learning already or have plans to do so within a year.

6. More new initiatives emerged in 2019 than in 2018. Most respondents report using data science and machine learning technologies for two years or less.

7. Among non-users, business intelligence competency center (BICC) respondents show twice the likelihood of any other group to adopt data science and machine learning this year or next.

Subscribe and read our detailed analysis at: http://www.researchsubscription.com

Signoff ac76b40517b7cc2ba93d8063981d746be69ffc8e8ae97f4cd71e2938514c56aa