Chatbots were part of a wave of new artificial intelligence tools that were changing the way people interacted with technology. Digital virtual assistants housed in a smartphone, desktop, or laptop computer, such as Apple’s Siri and Microsoft’s Cortana, had paved the way for person-bot communication. More recently, Amazon’s Alexa, which could be awakened at any time by a voice prompt that spoke her name, provided ambient virtual assistance to consumers in their home.
Unlike these virtual assistants, chatbots were less sophisticated and tended to specialize in executing simple tasks rather than providing omnipresent and wide-ranging functionality (see Exhibit 2). While the most advanced virtual assistants were powered by artificial intelligence, which enabled them to understand complex requests, personalize responses, and improve interactions over time, most of today’s bots followed a simple set of rules programmed by a human coder who simulated a typical conversation and then programmed the bot to prompt a conversation by delivering a series of queries to a customer and to respond to them with canned responses triggered by simple if-then statements. Explained Derek Fridman, global experience director at Huge, a digital agency that helped its clients build chatbots, “The illusion that HAL [the computer from the movie 2001: A Space Odyssey] is out there, and the machine is alive is just that: an illusion. There’s machine learning taking place and algorithms making decisions, but in most cases, we’re scripting sequences.”1
According to McKinsey & Company2, technology companies spent between $20-30 billion on artificial intelligence in 2016. The market for chatbots was estimated to be $1 billion and was expected to nearly double by 2020 and triple within a decade. A recent Forrester study3 claimed that worldwide, 57% of firms were already using chatbots or planned to begin doing so shortly and 80% of businesses