Enterprise artificial intelligence has reached a tipping point. Whatever you call it – machine learning, predictive analytics, artificial intelligence, cognitive computing – this phenomenon is not only dominating our news feeds, but our business conversations also.
AI is using a machine to understand past behaviour in order to first predict, then potentially alter future behaviour to produce more optimal outcomes.
All the major enterprise software vendors and hundreds of up-and-comers are rolling out AI-powered solutions
AI is already so ingrained into our personal lives, it seems that the consumer space is about ten years ahead of the enterprise.
The reason it has taken so long for AI to permeate your workplace is that most organisations believe AI is all about the algorithms.
But, in fact, the real value lies in the data and the workflow. Meaningful AI requires three crucial elements:
· Algorithms – those that look for patterns in data in order to predict future outcomes.
· Data – information that continually feeds the algorithms, making them smarter and more accurate.
· Applications – software that turns predictions and prescriptions from the algorithms into improved outcomes by integrating into activities and workflows.
Anyone can build an algorithm, but the real magic of AI, and what sets winning solutions apart, lives in the data. Better data results in better predictions, which ultimately produce better outcomes.
This article originally appeared in information-age.com. To read the full article, click here.