Zero One: AI Transforms the Contact Center

Tech giants and line-of-business execs see real value for AI in the contact center.

February 24, 2017

3 Min Read
Zero One AI Transforms the Contact Center

Like wood stacking up behind an arrowhead, Salesforce, Microsoft, Google and other tech titans are gathering behind artificial intelligence, or AI. More importantly, line-of-business executives (LOBs), the new shot-callers in tech, now expect AI to deliver real-world results, particularly in the contact center.

All of this means tectonic change is coming, and just about everyone better brace for the impact.

The contact center and other operations touching the customer are emerging as the sweet spots for AI in the enterprise. In a Forrester survey, 57 percent of AI adopters said improving the customer experience is the biggest benefit. Marketing and sales, product management, and customer support lead the AI charge.

In February, Salesforce unveiled Einstein AI for its Service Cloud contact center offering. Customer service agents will lean on Einstein AI to give them information about a particular customer when they need it, as well as escalating cases using machine learning. Managers will tap Einstein AI for insights about their contact center operations, in order to make changes and boost customer satisfaction scores.

AI in the contact center isn’t new. At Dreamforce last year, Humana, a healthcare insurance company, showcased its use of AI for listening to customers in the contact center and flagging elevated tones. In turn, the AI bot Cogito informs the customer service agent to change tactics.

Related: Zero One: Are You Ready for AI?

Best use cases for deep learning and AI occur in contact centers with lots of historical customer service data, such as email transcripts and chat logs, said Mikhail Naumov, co-founder and president of DigitalGenius, an AI tech company. Contact centers dealing with lots of repetitive questions are also ripe for AI.

Microsoft, too, is driving AI into its core products, from Cortana Intelligence Suite to Dynamics 365. Speaking at Channel Visionaries in San Jose, Calif., in January, Larry Persaud, director of Azure strategy, gave an example of an AI chatbot helping an agent lock in a hotel reservation. Microsoft’s AI technology also improves the Uber customer experience by ensuring drivers match their profile photos and securing passenger information.

“We want our partners to understand what this really means for the future [and] to learn about the business and technical aspects,” Persaud said. “Data and intelligence are very tightly coupled. We’re adding machine learning aspects, readying AI into our data platform.”

Related: Zero One: Can the Channel Pivot to Digital Business in the Cloud?

There’s no question AI tremors will be felt across the channel landscape.

“My bet is we’ll see huge progress in the next 12 months,” said Tim Fitzgerald, vice president of digital transformation at Avnet Technology Solutions. “It will impact substantially the as-a-service commerce, transaction experience and the ability to support localization and personalization on a specific customer level.”

Echoing Microsoft, Google’s Sergey Brin, speaking at the World Economic Forum Annual Meeting in Davos-Klosters, Switzerland, in January, said Google’s AI technology called Google Brain “probably touches every single one of our main projects, ranging from search to photos to ads to everything we do.”

As major platform vendors embrace AI, particularly in the contact center, it’s important to maintain a little perspective, said Forrester analyst Ian Jacobs.

Today’s AI chatbots in the contact center are good at basic tasks, such as delivering content, replenishing a pre-paid phone account, and handling information requests that require accessing a single knowledge source, Jacobs said. Complex problems, such as troubleshooting a router and reconnecting a smart thermostat to it, still require human agents.

In other words, LOBs shouldn’t expect AI to replace legions of human agents and, in the process, bring about massive savings.

“Using AI for basic blocking and tackling, rather than for moonshot projects, means brands will see tangible results much sooner, even if those results are somewhat more modest,” Jacobs said.

 

Tom Kaneshige writes the Zero One blog, covering digital transformation, big data, AI, marketing tech and the Internet of Things for line-of-business executives. He is based in Silicon Valley. You can reach him at [email protected]

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