The limits of AI
AI, however, has its limits. Today, the technology is extremely proficient in recognition (of faces, objects, sounds, and patterns), classification (of quality, customers, etc.), prediction (of demand or churn), and similar functions. What it doesn’t do well, however, is display creativity or empathy, or gain real insights into problems. There are no signs that this will change anytime soon, so the human factor will still have its place.
The real challenge for AI is the quality and availability of data. This data is needed to train and test machine-learned models. Insufficient, irrelevant or inaccurate historical data can lead to project failure.