Headlines about AI may focus on consumer applications like home assistants
and self-driving cars, but the technology is greatly affecting the industrial
world. Stale business models in utilities, oil and gas, and aerospace no
longer stand up to rapidly evolving markets driven by changing consumer
expectations, increasing digitization, and next-generation analytics. And, as
recent history has shown us, companies late to embrace these digital trends
face imminent disruption.
To mitigate these market risks, industrial companies must leverage AI to
capitalize on emerging opportunities and pursue new revenue streams and
profitability. In fact, a 2018 report from McKinsey & Company found that 80%
of extensive AI adopters had better financial performance than their peers,
while research from Accenture indicates that AI will fuel profitability gains
of up to 39% by 2035. This improved financial position is key to maintaining
technological leadership, competitive advantages, and stability in dynamic
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DeepNLP integrates into existing workflows to enable organizations to better respond to changes in their business and quickly get answers to specific queries or analytics that support decision making.