Industrial digital transformation is critical to achieving new levels of safety, sustainability, and profitability--and "Industrial AI" is a key enabler of that change. 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. This has fueled the need for "Industrial AI," a new paradigm that combines data science and AI algorithms with software and domain expertise to deliver measurable business outcomes for the specific needs of capital-intensive industries. Industrial AI disrupts these industries by lowering barriers to adoption, offering new opportunities for industrial organizations to significantly reduce costs, improve efficiency, and transform their operations for the better.

Today's industrial organizations, and especially those in capital-intensive industries, stand at a crossroads for opportunity. They recognize the need to reinforce their industrial operations and complex value chains with greater resiliency, flexibility, and agility to respond to shifting market conditions. At the same time, they're investing in autonomous and semi-autonomous artificial intelligence (AI) capabilities to realize their vision of the digital plant of the future--the "Self-Optimizing Plant." 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.

Artificial Intelligence (AI) is changing the world around us and will bring new capabilities to everything from smart factories to drones to sports to health care and to driverless cars. Data is the common thread across all these applications, and our strategy is to make Intel the driving force of the data revolution across every industry. As a data company, it is imperative that we deliver solutions that create, use and analyze the massive amounts of data that are generated each and every minute. Data inference, or finding useful structure in data, may indeed be the largest computational problem of our time. That is why AI is so important to Intel.