How conversational AI will boost CX this decade

3 key conversational AI market trends to follow in 2020

Last year was a banner year for conversational AI, capping off a decade that saw the market grow to $4.2 billion with no signs of slowing down. Markets and Markets estimates that, by 2024, adoption of conversational AI in the enterprise could eclipse $15.7 billion. This growth is expected to be primarily driven by demand for AI-powered customer support services, omnichannel deployment, and reduced development costs over time.

This bullish outlook sends a clear signal that, as the technology becomes more commonplace, consumers are growing accustomed to interacting with their bank, insurance company or mobile phone carrier via automated self-service systems in the form of conversational AI-powered virtual agents. Of course, not all conversational AI solutions are created equal and the market is currently awash with vendors claiming everything from the very best technology to the quickest returns on investment, but, ultimately, failing to deliver on the promise of either. 

It’s no wonder then that, in Gartner’s recent report Hype Cycle for Artificial Intelligence, chatbots and conversational user interfaces sit right at the top of the ‘peak of inflated expectations’. While companies looking at implementing a conversational AI solution in 2020 need to be wary of the enormous levels of hype surrounding the market, there are several trends emerging that will clearly define the space as we move into the years ahead. 

Overall, there are three specific trends that are responsible for growth and adoption. While they represent the main drivers, there are others that pertain to the conversational AI market as a whole and the technology that powers it, which are discussed at length here. 

Applying a ‘chat-first’ strategy

No longer will the chat channel be tucked under phone and email info on company ‘Contact Us’ pages. Organizations will begin to capitalize on customer familiarity with conversational AI by placing virtual agents front-and-center in their digital customer-service strategy, making them the first—and sometimes only—point of contact for customers visiting their websites.

In Europe, this trend is already evident and the results are compelling. Norway’s largest bank, DNB, handles more than 10,000 customer inquiries per day via its virtual agent called AINO. By making AINO the only way customers can interact with the bank digitally, DNB now automates 20 percent of all customer support traffic across all channels, including phone and email.

Another Norwegian bank, Sparebank 1 SR-Bank, was a pioneer in this ‘chat-first’ approach back two years ago. At the European Digital Banking Summit in 2019, the firm announced that conversational AI helps automates 34 percent of all B2C traffic, and 39 percent of total B2B support traffic, with three of every four customers choosing to receive assistance from a virtual agent even when given the option to speak with a human.

Enter the AI Trainers

Customer service workers—a group previously identified as at high risk of being made redundant due to automation—are actually uniquely positioned to be upskilled into one of the most important jobs of the Fourth Industrial Revolution. Namely, training and maintaining conversational AI.

Last year, Microsoft and IDC published a report which revealed that 67 percent of business leaders and 64 percent of workers believe that, in the future, AI will augment their jobs rather than displace them. 

This makes sense. In 2020, we will see these skilled workers shift their existing product knowledge and expertise away from call centers and support desks. Instead, thanks to conversational AI handling the menial, repetitive queries that typically bog down support lines, customer service reps will transition to backend AI systems, where they will principally have responsibility for ensuring that a company’s virtual agent is the best possible representation of its brand. 

After all, who knows your customers better than the employees who have spent years serving them on the customer service front lines?

Proprietary language understanding

While the previous two trends will be crucial to driving the conversational AI market forward, advances in natural language technologies will ultimately differentiate industry-leading vendors from the hundreds of also-ran solutions. Proprietary Natural Language Understanding (NLU), in particular, will play a big part in helping vendors stand out. 

Some of the key advances in the space that will be crucial to a virtual agent’s success going forward include the ability to accurately understand multiple intents or topics in the same sentence. This is coupled with the capability to easily parse complex and wordy customer requests to minimize their negative impact. No less important is the ability to reduce false-positive responses, and keep them at a minimum.

A virtual agent is only useful to customers if it can accurately understand what they need help with. The algorithms that power conversational AI will only improve exponentially. This is, in part, thanks to huge inputs of data that are honing the ability of these systems to accurately and efficiently understand human interactions.

In the year ahead, we can expect to see these trends rock the conversational AI market forward as never before. In the process, virtual agents will continue to emerge as a primary customer service channel for many of the world’s best-known brands and large enterprise organizations.