ar from simple classification as “conversational commerce” – and a way to save on customer service resources – chatbots will grow ever more sophisticated and relevant in the workplace.

According to Gartner, by 2020, 85% of customer interactions will be managed without a human and at the close of 2018, customer digital assistants will recognize customers by face and voice across channels.

Rather than sound the death knell of job loss and the dehumanization of our interactions with companies and with each other, some three interesting trends have emerged regarding chatbots and AI. 

“Humanizing” chatbots and making them more lifelike

Some companies have found the ultimate way to get customers and employees more comfortable using chatbots: make the chatbot look like a real human.

Calling itself the “Digital Labor Company,” IPSoft has developed Amelia, a chatbot and avatar that is lifelike and based on a real person, model Lauren Hayes. Primarily a customer service tool for financial institutions, Amelia utilizes advanced machine learning models to make business decisions drawn from conversational data – and converse with participants — in real-time.

————————————————————————————————————————JOIN OUR FREE WEBINAR:

10/12/17  12:00 PM Pacific  AI Chatbot Development: How to Build an Awesome AI Chatbot Learn More Here


The aim of Amelia, now in version 3.0, is simply to automate routine tasks in customer service, IT, and business processes. She supports employees on the IT service desk at a global telecom provider, responds to 3,000 customer queries per week at a US insurance company, and has helped answer inquiries from external mortgage brokers at a global bank.

According to Quartz, Amelia “inspires both fears and hopes for the ways in which technology can replace humans.”

There are now companies specializing not only in the deep learning aspects of AI, but rather in the creation of avatars that simulate the anatomy and mechanics of muscles and other tissues of the human face.

What is the point of making Amelia’s avatar so realistic? Or creating a human persona for her at all?

“When you talk to somebody, there is all sorts of non-verbal communication. The avatar itself helps with empathy. If the end user feels like they’re being heard and understood, they’re more likely to engage further and in more length. And that allows Amelia to grasp the intent of what the user is trying to say.”

Christopher Reardon, IPsoft’s director of experience design, who previously worked on the branding for IBM’s Watson.

The avatar itself is programmed to react to human conversations with appropriate expressions and actions (so Amelia doesn’t smile, for instance, when an insurance client explains that they’ve just been diagnosed with a terrible disease).

And as can be expected, as Amelia acquires more information, she continues to “learn” and get smarter.

Training the bots to do their jobs better

Increases in automation, AI and chatbots continue to stoke fears of job loss. However, aside from the data scientists and machine learning engineers needed to keep AI humming, another job title has appeared out of nowhere:  intelligence trainer.

Katharine Rubin, a 22-year-old accounting major at New York City’s Baruch College, is part of a growing workforce that spends anywhere from 5 minutes to 40 hours a week increasing the I in AI. Specifically, Rubin and others provide training data for machine learning algorithms.

For an autonomous car to recognize pedestrians and stop signs, it’s typically fed thousands or millions of photos, all hand-labeled. To improve a conversation, a digital assistant or chatbot needs to be told over and over when it has failed.

Real humans must be there to provide these corrections.

As automation and AI eliminate a range of relatively rote jobs, the need to train software is also creating other employment opportunities. People must label massive collections of unsorted data so computers can perform more complex tasks, such as driving cars and carrying on conversations.

According to Bloomberg BusinessWeek, there are over 1 million people helping to train AI software for a fee.

Rachel Neasham, a human travel agent with travel app Lola, works alongside Harrison, the company’s AI platform, and sees it as a race: Can human agents find new ways to be valuable as quickly as the AI improves at handling parts of their job?

Lola was set up so that agents like Neasham didn’t interact with the AI much, but Harrison has been watching and learning from every customer interaction all along. Over time, Lola discovered that Harrison wasn’t quite ready to take over communication with customers, but it had a knack for making lightning-fast hotel recommendations.

It made me feel competitive, that I need to keep up and stay ahead of the AI,” Neasham said. On the other hand, she said, using Harrison to do some things “frees me up to do something creative.”


Corporate chatbots get the attention

While the number of consumer chatbots available for use in Facebook Messenger, Kik, and other chat platforms are growing exponentially, their use is largely arbitrary: people are not forced to have to use the chatbot to reserve airline tickets or ask for restaurant recommendations.

Though a brilliant tactic to get consumers to engage more with their smartphones – 68 percent of apps on a smartphone are messaging apps – chatbots are a way for software companies to distribute their software without asking the consumer to download yet another app. Indeed, the so-called “app recession” is powering the rise of chatbots.

However, people will more likely be forced to engage with chatbots and AI technologies at work. The bigger the company, the more likely there will be the use of automation and chatbots to handle routine, internal tasks. After all, AI technologies rely on troves of data – something which large organizations have a lot of.

Business intelligence (BI) is not a new concept in enterprise IT. BI enables businesses to know more about their customers, employees, markets, and overall processes and performance over time.  

AI now makes it possible to get this critical information faster and cheaper.

Companies using AI for customer-facing or employee-facing tasks can often free up resources that would have gone to paying a human for analysis tasks — and reinvest those resources in humans executing on the insights produced by AI.

Chatbots that connect to an organization’s data and BI systems can provide answers to questions that are asked of them in natural, human language. They can stand in for an entire data analytics team, and employees can use the chatbots to engage with this information 24/7.

Recognizing that chatbots will be central to organizations as a way to incorporate intelligence and convenience into the messaging experience, enterprise collaboration company Slack earlier this year invested in 11 bot companies for the sole purpose of increasing the relevance of its core platform.

Indeed, Amelia, the AI-powered avatar developed by IPsoft, has proven to be a success at answering questions for the IT help desk or fielding inquiries from a financial services firm’s brokers. Far from being a “throwaway” use, Amelia provides a direct business value to companies.

The Author, Rick Diamond, is CEO of AI & Chatbot News & President of YBS.  Visit to read additional articles about Artificial Intelligence and Chatbots.