When it Comes to the Economy, Automation is Buzzing

The rise of robotics, artificial intelligence, and machine learning have put us on the brink of a new automation age, projected to last from 2015 to 2085, according to McKinsey. Unlike the type of automation we witnessed during the Industrial Revolution, during which the steam engine replaced routine physical work activities, the changes we can expect from this new transformative period will center around cognitive capabilities, like consequential decision-making, tacit judgments, and sensing emotion. These activities have traditionally required a college degree, which is why the world is now alarmed at the broad swaths of the job market at risk of becoming obsolete.

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Clearly, there are unparalleled productivity gains from this new type of “intelligent automation”. But what are the implications for customer-facing functions like customer care and support? And what limits should be placed on how much automation is allowed in these spaces?

Automation: a Friend or Foe?

According to Fast Company, automation is expected to eliminate 6% of US jobs in the next five years. Other observers and experts, like IBM CEO Ginni Rometty, have stated that while AI will reduce jobs in the industrial and manufacturing sectors, the corresponding increase in programming and development roles will lead to net job creation. As far as customer service agents are concerned, chatbots probably pose the biggest risk to job loss. But like Rometty, I feel that the effects of automation are not so black-and-white.

“We could reframe the threat of automation as an opportunity for augmentation”-Harvard Business Review

My prediction is that, as customers continue to demonstrate their preference for effortless, mobile-friendly channels like messaging apps over phone calls, the model for customer service will likely shift towards a smaller number of specialized, highly trained, insourced customer care agents—who, with support from technology like machine learning, auto-tagging and intelligent distribution of actionable conversions (also known as PLAY), will be able to handle a larger volume of customers inquiries.

Whereas traditional customer service staff often function on the level of rote memorization—reading from outdated, standardized scripts—the ability to interface with various intricate technologies will actually boost the value of today’s social customer service agents on the job market.

Partial Phase-Out: What Automation Will and Won’t Change

In part, some of the panic over automation is a natural reaction to the way it’s been framed. When we talk about the new automation age, it’s important to recognize that individual activities are a better unit of measurement than entire occupations. As McKinsey points out, rather than replacing jobs outright, automation will often mean that certain tasks become more efficient.

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Following the framework detailed in the above chart, we can say that customer service involves a mix of “data collection”, “data processing,” and “stakeholder interactions.” According to McKinsey’s analysis, the latter activity—in which the agent speaks to the customer directly—is less susceptible to automation than the others. Why is that?

The answer, in part, is that modern consumers are simply fed up with the type of non-personalized, synthetic resolution they receive from call centers, and need to feel like they are interacting with a human who can speak to them about their issues in a way that’s natural, relatable and down-to-earth—especially if they are upset or already frustrated with attempting to fix their issue.

So chatbots will not necessarily make social customer service agents obsolete, but will work with them as a kind of “personal assistant”, serving as the initial, high-level touch point of requests, and escalating issues when they become more complex. A perfect example of this workflow can be illustrated by Twitter’s DM Dispatcher by Conversocial, a functionality that prompts customers to proactively provide details on the service issue at the first point of contact, eliminating the initial back-and-forth between agents and customers to gather more context. And, as these technologies enable customers to get even complex issues solved in-the-moment, at the touch of a button, more customer care volume will shift away from phone calls and into messaging.

The Tradeoffs of Automation

According to McKinsey, technical feasibility is just one of the components that needs to be addressed when predicting the impact of automation, but not the only relevant factor. Another to consider is the side effects beyond the cost reduction derived from labor substitution. For instance, what would happen to customer satisfaction scores if service interactions are completely automated and robotized? Are companies jeopardizing the incremental value of increased retention and satisfaction by focusing too much on cost reduction? There must be a balance.

Another factor to consider is “regulatory and social-acceptance issues, such as the degree to which machines are acceptable in any particular setting”. A robot may, in theory, be able to replace some of the functions of a nurse, for instance. But for the time being, most patients would reject fully robotic treatment, in favor of an actual health care professional, capable of answering complex questions and handling emotional situations. Likewise, in customer service, people will still expect a degree of human contact when it comes to the more time-sensitive, emotional issues–such as when a customer needs to cancel a stolen credit card, or change a flight at the last minute.

The Future is Humanity at Scale

Unleashing automation’s full potential requires people and technology to work together. And although our initial instinct is to resist the upheaval of potential job loss, an integrated approach that makes life easier and effortless for customers will encourage them to turn to social, messaging and digital channels to resolve more and more of their conflicts, ultimately creating more and new future jobs in the social customer service sector.