AI Skills Gap Remains a Barrier to Implementation a Year After
O’Reilly’s Inaugural AI and Deep Learning Research Findings are Released
BOSTON–(BUSINESS WIRE)–lt;a href=”https://twitter.com/hashtag/AIAdoption?src=hash” target=”_blank”gt;#AIAdoptionlt;/agt;–O’Reilly,
the premier source for insight-driven learning on technology and
business, today announced the results of its 2019 Artificial
Intelligence (AI) survey, “AI
Adoption in the Enterprise” The report explores how enterprise
organizations are planning and prioritizing AI implementations and how
adoption patterns may change over the course of the year.
Similar to the results of O’Reilly’s
2018 AI survey issued last April, the findings suggest that there
continues to be strong interest in democratizing AI in production
regarding accountability, compliance and ethics.
Despite this, a majority of businesses are not equipped with the data or
AI/machine learning expertise they need for successful implementations.
In fact, the need for AI talent has become even more critical, with 23
percent of respondents indicating lack of skilled people as a factor
that slows adoption, compared to 20 percent of respondents last year who
indicated a lack of skilled people as a bottleneck.
Other notable findings include:
Eighty-one percent of respondents work for organizations that already
More than 60 percent work for organizations planning to spend at least
5 percent of their IT budget over the next 12 months on AI.
One-fifth (19 percent) work for organizations planning to spend a
significant portion—at least 20 percent—of their IT budget on AI.
The level of spending depends on the maturity of an organization.
Those with a mature practice plan to spend on AI at a much higher rate
than less-mature companies.
“Lack of data” and “lack of skilled people” remain key factors that
slow down AI, along with “company culture” (23 percent) and
“difficulties identifying use cases” (17 percent).
More than half of all respondents signaled that their organizations
were in need of machine learning experts and data scientists.
Half of all respondents belonged to organizations that used AI for
research and development (R&D) projects, while one-third used it for
customer service or IT.
More than half (53 percent) of all respondents already using deep
learning use it for computer vision applications, but many more use it
for “enterprise data,” including unstructured data (86 percent) and
text (69 percent).
In O’Reilly’s 2018 survey focused on deep learning, the top three
tools used were TensorFlow (61 percent), Keras (25 percent) and
PyTorch (20 percent). This year, usage rates for Keras (34 percent)
and PyTorch (29 percent) grew.
“AI maturity and usage in the enterprise has grown exponentially over
the past year and there are no signs of that slowing down,” said Ben
Lorica, O’Reilly chief data scientist and AI Conference chair. “Mature
organizations with plans to spend on AI tools that hire talent to
identify use cases that fit those AI solutions will succeed, but for
those less-mature companies with a lack of investment in AI, we expect
the gap between leaders and laggards will only widen.”
You can download the full survey results here.
Further exploring some of the most important trends and developments in
enterprise AI, O’Reilly and Intel AI will host the upcoming AI
Conference, taking place from April 15-18 in New York City.
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