What is AI, or Artificial Intelligence? And to what extent is a robot truly capable of feeling?
Many of our customers now know approximately what artificial intelligence is. As a result, a lot of them have created goals to indicate their intention to make use of it in some way. However, saying that you’re working on it doesn’t mean much. What’s important is that you make it practical and broadly applicable. It is somewhat reminiscent of the trend of corporate social responsibility (CSR) that appeared some years ago. Every company included CSR in their statement or on their website. But what actually happened wasn’t always very clear.
Artificial intelligence, or AI in short, has the potential to serve customers in a very personal way, despite the automated process. Because today’s chatbots are getting smarter, and no longer depend on a pre-written script, they are slowly but surely developing a form of empathy. And this is a huge advantage for customer contact centres. Maarten van de Koevering of Chatlayer.ai says: “On the one hand, employees now have more time for more interesting tasks because the simpler work is taken on by chatbots. On the other hand, it also means that there is huge potential for scalability. The customer service of the future, or rather of today, can also be reached at 2PM on a Sunday afternoon. Even when there’s no one in the office.”
Applying artificial intelligence
As an example, artificial intelligence is increasingly being applied in the insurance industry in the form of end-to-end solutions for process and insurance claims. For example, if someone drops an expensive vase and wants to claim this on their insurance, it is perfectly possible to handle this via a chatbot. This will help the customer a lot quicker, and the assessment process will be objective.
Our human brain understands both verbal and non-verbal communication, such as tone of voice and facial expressions. We are able to determine in no time whether or not someone has a sarcastic undertone. This can be tricky for computers, but thanks to machine learning, it is becoming increasingly easy for computers to filter sentiments from words. In this way, labels such as “positive”, “negative”, or “neutral” can be assigned. Especially when this is done for a long conversation, it is possible to extract a certain sentiment from the context and use this during the conversation. For example, in case of a negative sentiment you could decide to escalate the conversation to a call centre agent. The fear that jobs will disappear as a result of this is rather unfounded. In the example of the insurance industry, agents can now focus on the more complex claims that make the job a lot more interesting and challenging.
We would love to continue discussing this important topic with you. Please feel free to contact us or visit our website. We look forward to your message.