Artificial intelligence learns to talk back

A long-term fallout of the Covid crisis has been the rise of the contactless enterprise, in which customers, and likely employees, interact with systems to get what they need or request. This means a pronounced role for artificial intelligence and machine learning, or conversational AI, which add the intelligence needed to deliver superior customer or employee experience.


Photo: Joe McKendrick

Deloitte analysts recently analyzed patents in the area of conversational AI to assess the direction of the technology and the market — and the technology has been fast developing. “Rapid adoption of conversational AI will likely be underpinned by innovations in the various steps of chatbot development that have the potential to hasten the creation and training of chatbots and enable them to efficiently handle complex requests — with a personal touch,” the analyst team, led by Deloitte’s Sherry Comes, observes.

Conversational AI is a ground-breaking application for AI, agrees Chris Hausler, director of data science for Zendesk. “Organizations saw a massive 81% increase in customer interactions with automated bots last year, and no doubt these will continue to be key to delivering great experiences.”

Deloitte’s data from conversational AI vendors “showed that the volume of interactions handled by conversational agents increased by as much as 250% in multiple industries. These solutions are already delivering significant value for many organizations. Around 90% of companies mentioned faster complaint resolution and over 80% reported increased call volume processing using conversational AI solutions.”

With AI-enabled messaging, “companies can be available to customers 24/7, which is especially helpful as companies experience surges in volumes,” says Hausler. “AI has helped scale with businesses as they manage increases in digital interactions with customers.”

Still, there’s still much work to be done. “Enterprises have learned, sometimes the hard way, that in certain applications, including customer service in industries that rely on credibility, like banking or healthcare, replacing a human with AI technology can be challenging,” says Eric Jang, CEO and co-founder of Deepbrain AI. “One successful and growing area for AI is in customer service applications where AI is being used to help customer service reps be more productive and efficient. However, it’s essential to have these AI avatars be as real as possible, through the creation of ‘AI humans.’ While conversing with AI humans has been a long-time feature of science fiction, it’s now a reality, especially in customer service.”

The use of AI in contactless customer service “will be highly effective in delivering on the true promise of AI,” Jang says. “Due to the Covid-19 crisis, the contactless industry is growing rapidly. For traditional high touch industries, like customer service, contactless solutions must exhibit a human-like experience unlike any other technologies.”

Conversational AI also is playing a role in improving the employee experience, “Additionally, AI-powered bots are the best way to ease workers’ stress when they have to answer the same question over and over again,” Hausler points out. “In particular, healthcare organizations were even more overwhelmed when the Covid vaccines initially became available, but they would be able to delegate frequently asked questions like, “When can I get a vaccine?” to bots and as a result consumers get faster answers.

Conversational AI “can also do more complex things like schedule appointments,” Hausler says. “By using automation to handle a high volume of repetitive tasks, workers can focus on the more difficult and complex tasks which makes a huge difference to organizations.”

To date, conversational AI bots “are typically designed for a narrow purpose such as handling a particular set of queries related to a business function such as IT, HR, or finance,” according to the Deloitte team. “Attempts to build general-purpose bots have generally produced poor results. Another area of innovation aims to sidestep this challenge by describing efficient methods for composing multiple specialized chatbots into an ensemble.” This could take the form of “an enterprise assistant with a single master interface that can route users to virtual assistant specialists for CRM, ERP, and human capital management.”

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