Bridging the Artificial Intelligence Skills Gap in the Machine Manufacturing Industry
addition, the safety and environmental
regulations require strict governance.
Drawing from the sector estimates of the
PwC AI impact index, 2 PwC estimates that
by 2023, individual industry sectors may
increase their operating margins (i.e. how
much of each euro of revenues is left over
after both costs of goods sold and
operating expenses are considered) by 60-
100%. The difference in the industry
specific ‘AI boost curve’ shapes reflect the
impact of two different factors: 1) the
speed with which the industries are
capable of adopting different AI
applications and 2) the AI solution
development to address the industry-
specific business issues.
In manufacturing, short-term benefits are
expected to come mostly from process
automation
and
productivity-based
solutions. In the mid-term, more complex
processes can be automated as intelligent
automation offers considerable potential,
and
predictive
maintenance
and
optimization applications further boost
performance.
Figure 1: AI growth boost varies by industry (source: PwC Finland: Uncovering AI in Finland)
Productivity gains from AI and ML are not
only dependent on the introduction of the
technology itself. There is also a need to
change the organization of work and
increase employees’ knowledge.
2 PWC Finland: Uncovering AI in Finland, 2018.
3 e.g. O’Reilly 2018; Ernst & Young 2017
S KILLS G AP IN A RTIFICIAL
I NTELLIGENCE A DOPTION
Research 3 shows that the biggest barrier to
AI and machine learning adoption is a lack
of human skills. Most of the time, surveys
refer to the technical skills needed to
develop AI and ML solutions. However, the
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