Solving Quality and Maintenance Problems with AI

Chapter 1. Introduction and Primer on Predictive Quality and Maintenance

Overview

Following years of being dismissed as largely “hype,” we’re seeing a growing number of positive headlines about artificial intelligence (AI): “The artificial intelligence race heats up” (The Japan Times); “Healthcare’s Artificial Intelligence Market May Hit $6 Billion” (Forbes); and “Most Americans Already Using Artificial Intelligence Products” (Gallup). Even the Wall Street Journal is reporting on recent market advances. “After decades of promise and hype, artificial intelligence has finally reached a tipping point of market acceptance,” wrote Irving Wladawsky-Berger in early 2018.

Indeed, the artificial intelligence market is expected to grow to $190.61 billion by 2025 from $21.46 billion in 2018, at a compound annual growth rate (CAGR) of 36.62%, according to IDC. To put that in perspective, in 2018 the average technology budget for US businesses is expected to grow just under 6%, according to Forrester.

AI is transforming virtually all industries—from retail, to healthcare providers, to manufacturing, aerospace, and banking. Why? Because AI can deliver results in the form of insights. A report by Forrester forecasts that companies that use insight to drive their businesses will grow at a 27% annual rate at a time when the global gross domestic product (GDP) will rise only 3.5% annually (see Figure 1-1).

Figure 1-1. Revenue forecasts for insight-driven businesses (source: Predictions 2017: ...