Generational shifts in the workforce are creating a loss of operational expertise. Veteran workers with years of institutional knowledge are retiring, replaced by younger employees fresh out of school, taught on technologies and concepts that don’t match the reality of many organizations’ workflows and systems. This dilemma is fueling the need for automated knowledge sharing and intelligence-rich applications that can close the skills gap.

Industrial organizations are accumulating massive volumes of data but deriving business value from only a small slice of it. Transient repositories like data lakes often become opaque and unstructured data swamps. Organizations are switching their focus from mass data accumulation to strategic industrial data management, homing in on data integration, mobility, and accessibility—with the goal of using AI-enabled technologies to unlock value hidden in these unoptimized and underutilized sets of industrial data. The rise of the digital executive (chief technology officer, chief data officer, and chief information officer) as a driver of industrial digital transformation has been a key influence on this trend.