Bridging the Artificial Intelligence Skills Gap in the Machine Manufacturing Industry
I NTRODUCTION
Artificial Intelligence (AI) talent is
nowadays hard to find, and no company
today has enough in-house AI talent. AI will
transform many different jobs, and
companies should give every employee the
knowledge they will need to adapt to their
new roles in the AI era. It is important to
keep in mind that AI is much more than just
a technology. It is a resource to implement
new business models and better services.
User acceptance is the prerequisite for
solution implementation.
During the last decade, there has been an
explosion in the design, development and
implementation of AI in many sectors.
However, little attention has been given to
AI as a societal phenomenon and to the
broader implications of the different
approaches taken as we move rapidly
toward an AI age.
Organizations do not see AI technologies
or its availability as a challenge. Instead,
organizations are currently struggling with
AI business potential understanding and
with finding AI talent.
A growing number of countries have
recognized the opportunities provided by
artificial intelligence and have prepared a
national artificial intelligence strategy. In
2017, Finland was among the first
countries to launch an artificial
intelligence program. The objective of the
program was to make Finland a leader in
the application of artificial intelligence.
1
The
Finnish
Artificial
Intelligence
Programme 1 identified a small portion of
companies as forerunners in AI
implementation, with the majority of
companies still being at the early stages of
utilizing data and AI in their operations.
One of the ways, and an important starting
point, to address the AI skills gap is to
increase resources for digital, math and
technical education in general. In addition,
the current education system in Finland
does not yet pay enough attention to
applying AI in different fields. Academic
and training programs are just not able to
keep up with the rapid pace of innovation
with AI. AI education should start early and
take place for every education stage.
Academia, companies and public sector
officials must work together and ensure
that comprehensive AI curriculums will be
available. MOOCs (Massive Open Online
Courses) show the way and are a good
example of a modern way to educate
masses with basic AI knowledge. However,
deeper understanding of how to apply AI in
company and industry contexts typically
requires tailored education modules.
The manufacturing sector is currently
lagging behind in AI and Machine Learning
(ML) utilization compared to many other
industries (Figure 1). Adopting new
technologies especially in process
industries requires pedantic planning
which is time consuming. Companies have
long histories in optimizing their
production, and as the life span of
investments can last for decades, changes
unfortunately cannot be made rapidly. In
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IIC Journal of Innovation
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