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Special Report: Artificial intelligence apps come of age

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Meet your friendly sales assistant -- the AI chatbot

Artificial Intelligence allows companies to automate some tasks and will lead to changes in the job market. But people plus smart machines creates better outcomes than either alone.

Read part one of this article, "AI chatbot apps to infiltrate businesses sooner than you think."

Artificial intelligence chatbots are positioned to replace sales assistants responsible for highly repeatable tasks, the same way word processors replaced typing pools. Companies need to upskill those types of employees or plan for an upheaval.

Though cognitive computing tools such as the AI chatbot automate some job responsibilities, the technology won't be a wholesale replacement for most employees because it isn't able to handle novel, complex tasks, according to technology industry analysts and even the companies that deliver AI platforms.

Forrester Research Inc. recently predicted cognitive technologies, such as robots, artificial intelligence, machine learning and automation, will lead to 16% of U.S. jobs being replaced by 2025, while the equivalent of 9% of jobs will be created -- a net loss of just 7% of U.S. jobs. Office and administrative support staff will be disrupted the earliest, while new roles, such as robot monitoring professionals, data scientists, automation specialists and content curators, will make up some of the 8.9 million new jobs in the U.S.

If you consider how AI chatbots work, you understand why they won't displace more jobs: machine learning platforms only work on repeatable tasks that a person trains them to handle. An AI chatbot can't handle novel scenarios that require out-of-the-box thinking.

That said, people and smart machines are better together. Deep neural networks can identify patterns a person probably wouldn't notice, because they occur infrequently. However, the technology is far from perfect and may come up with probabilistic conclusions that require quality control checks, Gartner VP Tom Austin said during a recent webinar.

"There's a human-machine symbiosis where humans and machines complementing one another can outperform either alone," Austin said during the webinar. "Burn that into your head and never forget it; the biggest value that can come out of this is [the understanding that] machines are making humans smarter and humans are making machines smarter."

Indeed, even IBM is careful not to position its crown jewel, Watson, as a replacement for actual employees. Watson augments human intelligence, working side-by-side with humans to enhance their ability to act with confidence and authority, according to IBM Watson Platform Director Steve Abrams.

We had interesting people giving us an email address, but they weren't getting followed up on because it was tough to tell if they were real or not. This eliminates that problem.
Susan ZaneyKnowledgeVision's VP of marketing

"What if you could just talk to the data? So in the same way you would ask your assistant for the status of something, your assistant could ask the virtual assistant for the info -- and no one is put out of work," Abrams said.

IBM's Watson Conversation is being put to use in AI chatbot applications which supplement certain customer service and query tasks, and the latest iteration can decipher customer tones and intentions. This gets contact center agents off the hook for very basic questions that are asked again and again, freeing them up to focus on more complex problems.

"We aren't just looking at the literal intention of speech, but also the tone, sentiment and emotion analysis," Abrams said. "I can create a customer service solution that can tell when a customer is becoming irate and tailor the answers, using an apologetic tone, and hand it off to a human agent."

Virtual assistants do the grunt work

Conversica's virtual assistant, a combination of artificial intelligence technologies, is delivered as software as a service. The virtual assistant creates an email dialog to gather information from inbound leads which is ultimately passed on to live sales or marketing reps, explained Gary Gerber, Conversica's head of marketing.

One of Conversica's customers is KnowledgeVision Systems, an online business presentation platform provider based in Lincoln, Mass. KnowledgeVision's virtual assistant, which they named Caitlin Kelly, is tasked with following up on low-priority leads the company's business development representatives (BDRs) don't have time to focus on, Susan Zaney, the company's VP of marketing, said.

"Our BDRs were cherry-picking leads based on which ones they thought would be the easiest to convert to a sale," Zaney said. "We had interesting people giving us an email address, but they weren't getting followed up on because it was tough to tell if they were real or not. This eliminates that problem because 'Caitlin' follows up on every lead."

KnowledgeVision's leads sit in Salesforce, but salespeople don't see those names. First, leads are scored based on whether the company and title are real and how much research the person did on the website. High-priority leads are followed up on by a BDR, but it is a big jump from being a priority lead to actually wanting to talk to someone, Zaney explained.

Screenshot of an email following up on a request for a demo through Conversica's website. The sales assistant, Rachel Brooks, is a chatbot.

"Caitlin has bridged that gap," Zaney said. "With Caitlin, we are converting 8% of our untouched leads and we are re-engaging accounts that hadn't closed, but had potential."

Caitlin doesn't get to the bottom of why someone is interested in a product, though; her goal is only to get potential customers to request a meeting. When someone agrees, she will confirm their phone number and ensure a sales rep has the basic details they'll need to start a live conversation, Zaney said.

And if Caitlin learns someone isn't interested in a meeting or doesn't want more information, that's just as important because it means BDRs don't have to spend time making those calls, Zaney said. But it isn't perfect.

"Sometimes she doesn't understand out-of-office responses," Zaney said. "For example, if your out-of-office response says you will return on Tuesday of next week, she may interpret that as, you want a meeting on Tuesday."

That means KnowledgeVision's team has to review Caitlin's interactions before following up with customers. But the upsides far outweigh the limitations, according to Zaney.

One major advantage is that virtual assistants are 24/7 employees. If a potential customer responds to an email at 1 a.m., they can respond back immediately, and customers may never be the wiser that this persistent, tireless sales person is actually an AI chatbot.

Chatbots serve up fast answers

While these types of conversational interfaces certainly help companies increase customer engagement, they aren't mature enough to take over as the de facto user interaction platform, IBM's Abrams said. That's to be expected at this point. New user interaction platforms have come about throughout history, and during those transitions, the older ways to do things have remained useful, Abrams said.

"Today, I wouldn't feel comfortable booking travel through a conversation platform, and I don't with an actual travel agent, either, because there are so many options that are better to understand visually [on travel websites]," Abrams said. "The limited bandwidth of a dialog channel is better for addressing something like a travel disruption."

If Watson Conversation determines a customer needs to find information from a large pool of data, it can hand the request off to a system that is better suited for that task. For instance, if a doctor requests a research paper, Watson Conversation can hand the query off to an adjacent Retrieve and Rank service on IBM's Bluemix developer cloud.

"In the medical example, [Watson] is not replacing anyone; it is allowing doctors to get answers faster," Abrams said.

Welltok, Inc., an IBM partner, uses Watson machine learning and cognitive computing technologies to drive its CaféWell Concierge platform, which provides healthcare consumers with the information they need.

The Concierge understands customer intent and provides answers or directs customers to resources they may need, said the company's co-founder and vice president of functional architecture Jeff Cohen.

Cohen points out that you need subject matter experts to train machine learning systems. At Welltok, employees who have spent time answering customer calls help to train Watson, repurposing their expertise to scale through machine learning systems.

"Now the information isn't sitting in one person's head, and the system is a single access point for all customers to access," Cohen said.

Next Steps

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Data-driven marketing grows up

This was last published in August 2016

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Special Report: Artificial intelligence apps come of age

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