Transforming Data Sets into Prediction Engines.
There are many different ideas of what AI is. Some define AI as robots that can mimic human thought and feeling. Meanwhile, others think any process using machines to perform calculations is AI.
We use a wide definition: any process with automated decisioning can be considered to be AI. This is any decision making that does not rely on a human in the loop. This includes machine learning.
An AI system may also include automated actioning, where an action is taken without a human in the loop. A phone helpdesk that uses voice recognition to understand a customer and transfer them to the right department is AI. But so is a tool that advises a sales rep whether a customer is likely or unlikely to register for a loyalty card based on their demographics and behavior. A system does not need to take actions itself to be AI.
Which business problems could or should be solved using Artificial Intelligence?
Every day, we hear examples of AI providing innovative new ways to deliver services, disrupting entire industries.
AI has reinvented how we can understand our customers and deliver services to them. And AI isn't restricted to Silicon Valley.
If we don't end up using AI within our own businesses, we may miss out on the huge potential gains that our competitors are enjoying.
However, using AI to solve problems is rarely simple. Projects based on AI often run over time and over budget. They don't always deliver the promised results. And once the person who made them leaves, the solution needs to be redesigned.
Anyone who has introduced AI into business processes understands that these projects come with whole new levels of complexity and uncertainty.
This guide will help decide when AI is your best choice for solving a business problem you face.