Artificial intelligence and digital communication are disrupting the contact center space

The customer service (contact center) space is accelerating faster than the market has ever seen up to this point. Artificial intelligence and digital communication is changing everything.

Let’s start with some context. Right now we’re in the middle of a major market disruption by cloud-based contact center software platforms. They’re turning the conservative call center space into cutting-edge contact centers by helping them give up the expense and complexity of their hosted gear for easy-to-use, budget-friendly software as a service products in the cloud. They’re doing a great job of convincing and it’s coming at the expense of the traditional on-premise sellers at nearly 24% year over year growth (projected average over the next five years). That’s a ton of market share to lose in a very short amount of time.

Thing is, as fast as industry hardware giants like Avaya and Cisco are giving way to the new cloud platforms, the new cloud players are, if they’re not careful, going to be disrupted by the movement of digital channels with artificial intelligence before their own disruptive behavior is halfway capitalized. In case I lost you there, I’ll rephrase: The cloud players are going to be disrupted in half the time it’s taken them to begin disrupting the on-prem giants.

We’re in the middle of an Innovator’s Dilemma where cognitive technologies like artificial intelligence and machine learning are the new driving forces of change. Digital communication channels have been growing in demand for some time, fueled in part by the rapid rise of social networks, text messaging and now, messaging apps. But even as those channels have steadily reduced the inbound call volume over the last five years, it hasn’t been until the recent resurgence of artificial intelligence that contact center operators have seriously questioned their entire operations model.

Digital communication has given a taste of how relatively inexpensive it can be to support a customer, compared to answering a phone call. Operators have taken note of this and over the last few years we’ve seen many, for the first time, earnestly trying to figure out how to utilize networks like Twitter and Facebook more effectively to compound the savings. Now that many have read the whitepapers and case studies and have tasted what it’s like to see real cost of service savings with digital, they’re chomping at the bit for artificial intelligence and the idea of replacing percentages of front line work with bots.

Up to this point, the giant market of chat bots has been mostly about excitement and potential. They’ve been fun to play with in very specific, heavily scripted scenarios. But up until recently, they haven’t had the ability to understand the full context of what an inbound question or comment really means. At HelpSocial, we’re now seeing, for the first time, the ability of a bot to remember who someone is and take prior history into consideration when formulating a response. That’s the difference between getting an answer like, “Sorry for the issue. First, let’s make sure the modem is plugged in…” and “I’m sorry this has happened again. I just sent a message to the technician who helped you last time and we’re going to make sure it’s fixed.”

We’re not years out from this. Billions of dollars have been (and are continuing to be) put into R&D in the space. Thousands of new startups are being funded and starting to be acquired for their cognitive tech. It’s projected that over the next five years, these technologies will bring over $8 billion in savings to the customer service industry. To put that in perspective, that’s somewhere between a third and a half of the total projected cloud contact center software market value in the same time frame. If that’s not opportunity, I don’t know what is.

I confess, up until as recently as six months ago, I would have said we’re well over five years out from seeing humans being replaced in material percentages on the front line of the contact center. But since then, I’ve seen within my own company and with some of our partners the power of this technology. Now, I don’t believe it will take us near that long to see wholesales changes in how we think about workforce planning for customer engagement. And if you really want to go off on a tangent, start thinking about how that will impact everyone’s per-person pricing models and what that will do to the large industry incumbents who can’t afford to switch to cost-effective usage-based models…. We’re in for some big changes across the tech industry in general.

The next 18 months are critical. This is the same type of moment where Blockbuster had a chance to buy Netflix but didn’t do it. Cliche, I know, but true. The companies that lead over the next decade will be the ones that are able to act quickly right now on a strategy of advancing these technologies. They need to be able to tell a story of how to deflect big percentages of incoming call volume to digital and use AI to maximize efficiencies. That’s a big step for an industry living on revenues generated from using the phone. And that is a perfect case study for the Innovator’s Dilemma.