Three lessons to learn from contact centre AI

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While Artificial Intelligence is still a relatively recent topic of conversation in many businesses, it’s been high on the agenda in contact centres for many years. Operating at the intersection between companies and customers, the customer service sector was an early adopter of AI in the form of 'chatbots' - virtual agents that handle customer queries more quickly.

 

Setting goals to save time while providing a better customer experience prompted the industry, and service providers like us, to explore the best way to use the technology. The upshot is that contact centres provide a fascinating insight into how AI and machine learning are likely to evolve.

There are three principal takeaways from our contact centre experiences that will be useful to any industry contemplating AI investments:

1. Simple tasks can be automated and executed more efficiently

AI is enabling better customer experiences with faster authentication (confirming people are who they say they are) and quicker troubleshooting - cutting to the chase on the most common problems. A team of chatbot super-agents are an excellent investment for relatively straightforward tasks.

They use natural language processing and machine learning to understand freeform text or voice data and act on requests. Algorithms use data from past interactions to come up with an appropriate response in the present. The more a question is asked, the faster it’ll be to respond with the right answer.

2.  Self-service gives people more control

AI is often portrayed as dehumanising. But successful implementations in contact centres suggest the reverse is true. Chatbots empower people and let them take back control. Customers can have their queries answered more quickly on their own terms, anytime, anywhere, from any device.

This type of digital self-service is a fast and effective way of dealing with simple queries. Because machine learning helps identify the most common problems (and their resolution), it means organisations can answer queries quicker and achieve higher customer satisfaction scores. Everybody wins. The trick is knowing when to redirect more complex queries to human beings.     

3. AI stands for Augmented Intelligence

Chatbots carry out tasks with limited scope and are some years away from understanding and accurately responding to more general requests and conversations. One consequence of this is that customer service is one of the first sectors to realise that AI is about augmenting people, not replacing them.

The sector continues to provide an interesting model for how AI and machine learning is likely to evolve. The best-executed chatbots are about handling first response calls and triaging to human agents to resolve more complex queries.   

Even better, the chatbot can be trained to route the customer to the specialist agent best equipped to answer a query. At the same time, they’ll share the record of the initial exchange so customers avoid having to repeat themselves and the agent can get straight down business.  Such pathways will become major differentiators as organisations look to give their customers a better experience.

At BT, we're seeing organisations get smarter about how they use their people and where they deploy AI. Banks like Santander and RBS use intelligent assistants to handle common customer issues, like lost credit cards and forgotten PINs, freeing up human agents to spend time resolving more complex problems.

We think of artificial intelligence as ‘cobots’ rather than robots; AI-powered co-workers, on hand to help people work faster, safer and smarter, steering customers to human engagement where it’s most needed. Start to think about the future in terms of augmented intelligence rather than artificial intelligence and you'll see this exciting technology as an opportunity, not a threat.

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