In their recent Cloud Next conference held in San Francisco, Google announced that they’ve partnered with various companies in the AI, telecommunications, and cloud computing sectors to create an AI software for call centers.

According to a blog post by Fei-Fei Li, Google AI’s Chief Scientist, the true goal of the project is to empower a contact center’s human agents and the customers that rely on them. The software, aptly called Contact Center AI, is being developed with a “commitment to using a responsible, human-centered approach to AI.”

Empowering the call center

Contact Center AI will serve as a virtual agent that will be the customers’ first point of contact. When a customer calls a company’s customer care hotline, it will immediately respond and answer questions to resolve customer concerns.

It shares some underlying technology with the previously announced Google Duplex, which means that callers would be able to casually interact with the virtual assistant like they would with a human customer support representative.

If it encounters a question it can’t answer, the customer will automatically be transferred to a human representative. Contact Center AI will then become an onscreen support tool, providing the representative with relevant information directly from the company’s knowledge base. It may give the product or service information or outline a series of best solutions to help solve the caller’s issues.

“The result is a flexible solution that adapts to the needs of each and every call and provides a seamless experience between live and virtual agents, playing as big or as small a role as the situation demands,” Li explains.

More AI implementations down the line

Currently on Alpha stage, Contact Center AI is merely one step that Google is taking towards a future of the AI-empowered workplace. While a roadmap hasn’t been unveiled, the company has disclosed that there are indeed more projects being developed in their AI sandbox for businesses.

One tool is the Conversational Topic Modeler that analyzes archives of customer interaction logs to uncover insights about customer support trends. The data collected would be instrumental in shaping the customer experience, refinement of internal call center processes, and for improving both virtual agents and call center training programs for human representatives.