3 Use Cases of AI Adding Value to the Customer Experience

Phil Gray of Interactions shares three examples of how Artificial Intelligence (AI) can help to improve customer journeys.

There is no shortage of use cases where AI adds value to the customer experience. Whether it’s increasing automation to improve efficiency or providing personalised customer experiences, AI has the potential to improve how customers interact with brands on a daily basis. But for companies looking to justify AI investments, it can be difficult to know where to start.

Here are three specific use cases where AI adds value to the customer experience — for both the customer and the brand.

AI Assistants Can Handle Complex Customer Interactions

The most exciting examples of AI today are when a human and AI work “alongside” one another to see an entire customer interaction through. This means instead of handing the conversation off to a human when it gets too complicated— adding an additional touchpoint to the customer’s experience— the AI utilises real-time human guidance to complete the entire interaction. This way, the AI receives enhanced, structured human guidance, and the customer gets a smooth, efficient experience.

AI virtual assistants employing this type of collaborative model are rapidly advancing their natural language processing thanks to deep learning processes that incorporate the structured human direction. This means the systems can handle increasingly complex interactions— everything from adjusting travel itineraries, to transferring sensitive bank information, to establishing utility service accounts.

Delivering on the True Omnichannel Promise 

Another use case for AI in customer service is its ability to infuse personalisation and cross-system data collection to deliver the true “omnichannel” experience. While omnichannel has long been promised in the customer service realm (the ability of customers to carry on interactions across multiples devices), AI has brought that experience to life by providing true context persistence and personalisation.

For example— say you’re chatting with your bank’s automated text bot to adjust account information. Running late to your kid’s soccer game, you jump in the car. You still need to finish the task, but don’t want to text and drive. Instead of ending the conversation, getting in the car and calling the bank back at a different time— starting the process from the beginning— you instead tell the messenger bot that you want to continue through voice. The automated assistant confirms, and calls you on your cell. The conversation continues uninterrupted.

The AI assistant identifies the number you are calling from and retrieves not only your account information but also the context from the interaction you just ended— allowing the conversation to continue seamlessly. Without the AI assistant, you likely would have had two separate and repetitive conversations. With AI you were able to carry on the same conversation, and the technology bears the burden of providing convenience.

Customer Service Is a Pioneering Space for AI

The most exciting applications of AI in customer service are the ones where AI and humans work collaboratively to complete tasks together, not just hand them off to one another. It’s undeniable that AI has made significant progress in the customer care space. Not too long ago, customer service was a behind-the-times industry, but today it is a pioneering use case for AI.

For more on the future of AI in customer care, download Interactions’ ebook: Analyzing the Future of Customer Care