AI in contact centers

AI in Contact Centers – IT Gets the Driver Seat

Artificial intelligence is one of the hottest topics today and nearly every C-level executive is eager to understand how AI will transform their business. Contact centers are no exceptions.

Only about a third of the customers are willing to use bots and virtual assistants to interact with companies AI is not a customer pleaser, yet! But it shows high potential. Contact center execs are keen on leveraging AI for the right use cases and the one team they rely heavily is IT. IT plays a crucial part in translating the larger AI vision to reality. It is never easy and they lack a clear execution path, especially, given the technology is still nascent.

As IT leaders, here are some key aspects to think through as you roll out an AI project in your contact center.

Choose the right use case for your AI projects

While there might be various possible use cases for AI in contact centers the most popular ones are around agent-facing bots that help in automating mundane agent activities and the customer facing AI chatbots and conversational AI bots that help drive self-service. Partner with your Contact Center counterpart to identify the use cases that make the most sense for your centric – based on customer demography, various channels used and where the need for change is high.

Don’t miss some architectural considerations

When building a CX tech stack it is important to choose the right contact center platform. One that is flexible, cloud native and has open APIs that can easily integrate to various AI applications from different vendors. Also an orchestration layer is critical specially when deploying more than one AI application.

Pilot before you scale

Having the right data and models, identifying failure paths to human interactions and having agents and bots in the same customer experience flow are some aspects to test, learn and refine.

Evaluate AI technologies critically

In addition to a demo that shows features, look for details on how it impact business outcomes. Look for time and effort to add code, make configuration changes or maintain models. Don’t forget data and compute requirements.

Measure AI success meticulously

Measuring success is critical as you roll out AI in your contact centers. While there are various use cases on automation and cost reduction, it is important to balance it with improved customer experience as well. Learn more from our webcast featuring Gartner, and get some practical IT guidelines and frameworks as you roll out AI projects.