AI in the Contact Center: Why and How?

Gary Barton – Analyst, Business Network and IT Services

Summary Bullets:

• Most enterprises agree that AI delivers benefits – but not necessarily the benefits they expected

• AI projects require clear goals and a dedicated project management team, as well as external advice

GlobalData’s research into AI includes talking to enterprises about how and why they are using AI-powered technologies in the contact center. This research has given light to a number of key trends, and also highlighted examples of best practice.

What Technologies Are Being Used?

GlobalData’s research shows that, perhaps unsurprisingly, AI-powered chatbots are the most prevalent use case for AI in the contact center. The use of text-based chatbots on websites is now common, but GlobalData’s research suggest that voice-based chatbots are more of a focus for enterprises. Cost reduction is a key reason for this, particularly for contact centers in North America and Europe. But chatbots also deliver the potential for increased customer service with the potential for quicker response times to more simple inquiries.

Away from chatbots, the technologies forming the majority of AI use cases are workforce management, agent support (e.g., AI assistants and AI-generated sales suggestions), enhanced call routing, and, particularly in North America, agent-facing electronic signage.

The (Unexpected) Benefits of AI

The enterprises GlobalData has spoken to have almost all been positive about AI in the contact center and most report a positive return on their investment. So far, returns have been modest – often around 20% – but many of the projects are at an early stage and have not yet necessarily been deployed across all teams in a given contact center. The use cases most clearly identified for AI were centered on advancing efficiency, cost reduction, and improve first-call resolution rates. Enterprises have seen improvements in all three of these categories, but the benefit that was reported by most enterprises was of improved agent job satisfaction – an important factor in an industry that has high staff turnover rates.

AI Learning Curve

One of the most noteworthy trends in GlobalData’s research was that even enterprises that felt that their initial AI trials had been unsuccessful were positive about AI technology – instead they put the blame for failure on poor project management/implementation practices. Even those enterprises reporting successful trials often felt that they would improve the process significantly on subsequent deployments.

This is indicative of the newness of AI technology and points to the need to identify clear business needs to be addressed by AI technologies. The surveyed enterprises strongly recommended appointing clear leadership for AI projects and putting sufficient resources (both personnel and finance) behind the projects. Enterprises also agreed that AI is the future for contact center environments.

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