Call Center QA Featured Article
AI + CX = New Value
Businesses are increasingly moving their applications to the cloud. We all know that. It’s also common knowledge that artificial intelligence has arrived. And AI will play an even larger role in how we live and working in the future.
But, did you know that customer service is one of the key use cases for AI, and that cloud-based contact centers are ideally positioned to make the best use of artificial intelligence? That’s what this recent article suggests.
Considering that 40 percent of companies plan to adopt AI within two years and three-quarters of enterprise and independent software vendor developers expect to include AI or machine learning in at least one application, now may be a good time to consider a move to a cloud-based contact center.
"Software developers and end user organizations have already begun the process of embedding and deploying cognitive/artificial intelligence into almost every kind of enterprise application or process," says IDC’s (News - Alert) David Schubmel.
Artificial intelligence uses algorithms and rules-based logic to automate a wide variety of tasks.
“The answer to maintaining good customer service with multiplying channels is integrating AI with traditional, conversational communications is to augment the experience, not completely change it,” says Rajeev Shrivastava, chief strategy officer at inContact. “No matter how AI technology evolves, human interaction will always be a key element for a positive customer experience with the contact center.”
AI can also help with personalization, an important factor in optimizing the customer experience.
“AI offers endless possibilities for personalization,” adds Stephanie Trunzo, COO and chief digital officer at PointSource. “With the proper digital architecture, this technology can gather data points from a variety of interactions to create a thorough user profile. Amazon Alexa is a great example of where AI is headed. Alexa currently uses speech recognition, keywords, geographic information and previous user behavior to provide personalized suggestions.”
Edited by Mandi Nowitz
