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The artificial intelligence effect on industrial products

Organizations in the global industrial products industry face significant challenges: cost pressures, increased regulations, disruptive technologies and the increasingly costly delivery of raw resources. High volatility in commodity prices has put severe pressure on company margins and can quickly expose inefficient operations.

Processes, workflows and the understanding of performance are dramatically changing. Operations can no longer work in linear execution, or in isolation of other functional work streams such as engineering, maintenance and planning. Instead, the value chain needs to perform as an integrated whole to support the fluctuating demand cycles and higher cost supply activities.

New AI technologies have the capacity to make sense of the abundance of data through systems that can adapt and learn. By expanding digital intelligence adoption, AI technologies can help executives translate data into insights to drive greater innovation, and better operational and financial decisions.
To understand how organizations can better plan for AI adoption, the IBM Institute for Business Value (IBV), in collaboration with Oxford Economics, surveyed more than 6,000 C-suite members and heads of functions worldwide – including 300 industrial products respondents. The goal was to better understand their considerations, expectations and objectives in applying AI solutions to the most pressing business challenges and opportunities.