O'Reilly today announced its latest survey findings in the report, "The State of Machine Learning Adoption in the Enterprise."
As machine learning has become more widely adopted across industries,
O'Reilly set out to learn more about how companies approach this work.
By
surveying more than 11,000 data specialists across North America,
Europe, and Asia, the company has identified some of the key learnings
that derive from deploying machine learning in production, and where
other companies should focus as they begin their journey of machine
learning adoption.
Notable findings from the survey include:
- Job
titles specific to machine learning are already widely used at
organizations with extensive machine learning experience: data scientist
(81%), machine learning engineer (39%), deep learning engineer (20%).
- 54%
of respondents who belong to companies with extensive experience in
machine learning check for fairness and bias (compared to 40% across all
respondents).
- More
than half (53%) of respondents who work for companies with extensive
experience in machine learning check for privacy (43% across all
respondents). The EU's GDPR mandates "privacy-by-design," which means more companies will continue to add privacy to their machine learning checklist.
- 51%
of respondents use internal data science teams to build their machine
learning models, whereas use of AutoML services from cloud providers is
in low single digits, and this split grows even more pronounced among
sophisticated teams. Companies with less-extensive experience tend to
rely on external consultants.
- Sophisticated
teams tend to have data science leads set team priorities and determine
key metrics for project success - responsibilities that would typically
be performed by product managers in more traditional software
engineering.
"Navigating
large-scale machine learning deployments is no easy feat, especially in
light of recent privacy legislation such as GDPR. This research gives
organizations a better understanding of how other companies are
approaching machine learning at all stages of adoption and how the
technology is impacting these companies from a cultural and
organizational perspective," said Ben Lorica, O'Reilly chief data
scientist and Strata Data Conference chair.
Full survey results can be downloaded from the O'Reilly website.