Research is clear: customer service is one of the biggest drivers of customer loyalty. In fact, 78 percent of U.S. consumers say customer service is important to loyalty, according to Netomi’s State of Customer Service 2020 report. Increasingly, customers expect support that is fast, personal, and effective. To deliver the experience that customers expect, companies are adopting AI to provide immediate resolutions that bring customer delight and business value.
In the past 3 years, the AI space has become so noisy that even seasoned executives struggle to cut through the jargon, making it challenging to deliver against an AI strategy. Support leaders face a series of roadblocks. The AI space overall isn’t accessible to the business stakeholders who want to leverage it for improved customer experience.
Digital Experience Monitoring (DEM) is a growing practice within IT organizations that provides insight into the factors that make up the overall application User Experience (UX). As systems become more complex, as cloud adoption continues to grow, and IT loses direct control of infrastructure, it becomes both more difficult and more important to capture the overall end-user experience.
Understanding the latest advancements in artificial intelligence (AI) can seem overwhelming, but if it’s learning the basics that you’re interested in, you can boil many AI innovations down to two concepts: machine learning and deep learning. These terms often seem like they’re interchangeable buzzwords, hence why it’s important to know the differences.
Artificial Intelligence refers to the simulation of human intelligence processes by machines, computer systems to be precise. These processes primarily include learning, reasoning, and self-correction. Machine learning is a term that is synonymous with AI. As the name suggests, machine learning refers to empowering machines to learn by themselves using the data provided and predict the best possible outcome of a complex problem.
Unless you build or program computers for a living, you could be forgiven for never having wondered what actually happens under the hood. How do computers make decisions? What do their instructions look like? Can they, y’know… think?
