AI powered chatbots failing due to disappointing performance

Developers created 33,000 chatbots on Facebook Messenger during the first six months of the service. However, the success rate is low.

Although companies the world over are looking forward to embracing chatbots, most of such artificial intelligence (AI)-powered platforms are failing worldwide and some early adopters have dropped chatbots owing to disappointing performances.

Developers created 33,000 chatbots on Facebook Messenger during the first six months of the service. However, the success rate is low and Facebook reported that its chatbots failed 70 percent of the time.

"Most chatbots fail because companies don't clearly define their purpose. The scope that companies set for their chatbots tends to be broad and generic," Xiaofeng Wang, Senior Analyst with US-based market research firm Forrester, said in a report on Thursday.

For example, Singapore's POSB Bank rolled out a chatbot to handle general inquiries about its products and services. "Tactics like being the first bank in the region to launch a chatbot may generate some brand and PR value -- but all too often, firms fail to clearly define their chatbot's purpose and communicate it to users," Wang added.

Any gains will evaporate when customers end up confused or frustrated after asking questions that far exceed the chatbot's abilities. On the other hand, Singaporean OCBC Bank's chatbot, which focused on generating home loan leads, helped the bank close S$10 million new loans in three months. "It's crucial to find the key focus of a chatbot. You cannot try to do everything with one chatbot." Altona Widjaja, Vice President, Fintech and Innovation Group, OCBC Bank, noted.

According to Wang, chatbots are at a very early stage of development. Today's successful chatbots are driven more by keywords than by machine learning. They can deliver quick-hit information such as the latest promotions and provide shortcuts to content such as tutorials. "Most chatbots' cognitive capabilities are still far too limited to deliver context- or intent-based personalisation or advise customers about complex products such as life insurance," she said.

In the future, advances in AI will allow chatbots to use more contextual and predictive data and bring their capabilities closer to those of humans. "If marketers can clearly define the purpose and scope of a chatbot, thoroughly evaluate the benefits it can bring, and plan and execute it well, it can deliver business and customer value," Wang wrote.

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