How many data scientists does it take to screw in a lightbulb?” goes the familiar joke. “None, we’ve already automated it.” While this elicits a chuckle, its less optimistic cousin, “how many data scientists does it take to do data science?” (let that sink in) paints a bleaker picture. This idea of AI overtaking humans has been around at least since Samuel Butler’s 1862 article, “Darwin among the Machines.”

It took clearer form in E.M. Forstner’s chilling 1909 novel, “The Machine Stops.” And the concept has increasingly appeared in academic literature and popular culture over the intervening century. But in recent years the drumbeat has intensified. From Watson’s chess victories to deep fake videos indistinguishable from reality, solving cosmology’s unsolvable three-body problem, and the rise of chatbots in our everyday lives, AI has arrived en force and has captured the imagination. Witness the popularity of Ray Kurtzweil’s bell ringing in “The Coming Singularity” and the viral sweep of Elon Musk’s suggestion that we are, right now, living in a simulation.

As humans, perhaps to our disadvantage (against the bots?), we tend to fixate on the ominous notes. We haven’t forgotten Marc Andreesen’s prophecy that “software is eating the world.” We now know that he was right, and it’s easy to extrapolate this to AI. So, we assume, not unreasonably, if AI is destined to eat the world, perhaps customer service is the appetizer. Most of us, even with limited brand engagement, have already faced a chatbot. And while it’s obvious, sometimes painfully so, that most of today’s bots aren’t ready to pass a Turing test, we do recognize that they are getting smarter. In fact, in one recent survey, only 9% of respondents stated that “companies shouldn’t use chatbots.”[1]

The investment community, it would seem, agrees. In 2019 alone, per CrunchBase, there were more than 40 venture capital investments in conversational AI solutions for customer service.[2] Add to this intrapreneurship, university spin-outs, and bootstrapped startups, and it’s easy to suspect there are at least 100 companies vying for a share of this opportunity. There is no denying a revolution is underfoot.

That said, few believe that chatbots or, more broadly, AI in any form, will fully replace human labor. Brad Birnbaum, in his Forbes article “AI Is Growing, But the Robots are Not Coming For Customer Service,” leans in on this sentiment. “Nowadays,” he says, “there is an entire ecosystem that is forming around the customer with a suite of platforms and services designed to handle everything from marketing to payments to delivery to shipping. But, without customer service as the human touch point, this ecosystem would crumble like a precarious house of cards.”[3] Birnbaum’s perspective is mirrored in the MIT Sloan Management Review by P.V. Kannan and Josh Bernoff, who conclude that “successful AI-powered customer service systems will depend on bots working with humans, not replacing them.”[4]

But that raises some serious questions for today’s customer service leaders. If all the money is flowing towards (read as, all the innovation is focused on) conversational AI for customer service, who is innovating in the human-powered space? If chatbots are introduced upstream from human labor, doesn’t the downstream need to be modernized? If AI tackles the more routine questions and tasks, doesn’t that mean humans will receive an increasingly difficult set of tickets, raising the bar on skills and performance? A more nuanced question, how does one properly allocate share of traffic amongst the available resources, which now include both humans and bots? Putting these into focus: How do we design a human-powered customer service program that is meant to coexist with chatbots?

In the next couple of posts, I’ll delve into this. In the meantime, I’d love to hear your thoughts.