Chatbots

-Over the next few years, chatbots will become a ubiquitous component of the customer service experience.

-Phone centers may become a thing of the past as customer service switches to digital interactions. Chatbots will enhance chat conversations by helping humans with micro-tasks and automatic replies, though it's unlikely that bots will replace humans entirely.

-New features like natural language processing are improving chatbots everyday, but engineers are still trying to find ways to make artificial intelligence learn quicker with less data.

As more companies come to embrace chat functions to complement or reduce human phone centers, rudimentary human-to-human chat conversations will soon be a thing of the past, according to experts in the field. In the next three to five years alone, chatbots will become nearly ubiquitous, and work seamlessly with human customer support agents to provide customers with efficient, personalized responses.

Though chatbots have been around since the release of ELIZA in 1966, vast amounts of data and enhanced artificial intelligence capabilities have pushed the technology into the mainstream commercial space in the last few years, creating a hybrid experience between human customer service agents and bots.

Salesforce first launched an SMS chatbot product in 2014, and has since expanded it to include Facebook Messenger. The company also offers a product called Live Agent Chat, which facilitates human-to-human interactions.

"Salesforce believes fundamentally that bots are going to be complementing your live staff," said Meredith Flynn-Ripley, vice president of mobile messaging at Salesforce. "We really see bots as changing the job description and turning agents into intelligent problem solvers."

Flynn-Ripley described a future in which bots take over in "micro-moment exchanges" to relieve agents from doing tasks that "they don't even like doing." This could be as simple as information gathering, like asking a customer for their name and account number. But it could also look more like a conversational assistant, who gets smarter over time and can provide suggestions based off of data.

While the majority of customer service interactions are still over the phone, Flynn-Ripley said that call centers could soon undergo big changes as more companies embrace chat as the most natural way to interact.

"We often see the voice calls go down in a matter of weeks, and customer satisfaction go up," Flynn-Ripley said of new customers. "There's now an expectation that there should be automated bots."

A 'seamless' experience

sephora_facebook Leveraging its vast amount of user data, Facebook opened up its messenger platform to developers and businesses in April 2016.

It's since added functions like in-chat payment, built-in natural language processing (NLP), and what it calls Handover Protocol. NLP is the code that helps automated bots understand human messages more easily; Handover Protocol is Facebook's system the lets customer service agents and bots work within the same customer conversation.

Though still in beta mode, some companies like the beauty retailer Sephora implemented the protocol this summer.

It's not yet seamless, but that's the goal.

For messages that come in through Facebook, Sephora uses Assist, a business messaging platform, to evaluate which customer messages can be dealt with by a bot. If a bot can’t respond, the message will be passed along to a human agent using the customer service platform Sprinklr.

On the customer side, the bot generates a button which prompts the user to request a human customer service agent.

Soon, however, AI might be used to augment human conversations by suggesting responses to commonly asked questions, which the agent can send to customers without having to type anything out.

"We have a lot of potential to make that seamless, either by making the process smooth, or by providing humans powers like quick replies," Kemal El Moujahid, the lead product manager for Messenger Platform and M at Facebook, told Business Insider.

Like Salesforce, Facebook already has a lot of data about its users. Since artificial intelligence and chatbots are only as smart as the data they have access to, chatbots built on top of Facebook's system will likely have more advanced conversation abilities than chatbots built from scratch.

"The promise of chatbots is personalization at scale," El Moujahid said, describing a world in which every company has a chat function which can use artificial intelligence to quickly address customer concerns tailored to the data available about that customer.

"The most important thing for humans is for their expectations to be managed. As long as it's really clear what the agent is able to do — whether bot or human — then the users are fine with that," El Moujahid said. "You don't need to have a bot that can talk about its holiday with you for you to have resolution for your cable problem."

Outside of the text box

flo Many consumers would rather handle customer service issues by chat than over the phone phone — 56% according to a Nielsen study commissioned by Facebook. But this doesn't mean the future of chatbots is limited to words.

While Flynn-Ripley wouldn't reveal much about Salesforce's developing projects, she did suggest that in the next few years chatbots might find a use for something like Salesforce's Einstein Vision — a set of application programming interfaces (APIs) which allow programmers to integrate pre-trained image classifiers, or to train their own image recognition software.

It's not hard to imagine a function in which chatbots can read barcodes, or analyze photos to better help customers with their needs. Image recognition is already a common feature with content management systems like Box, which partnered with Google Cloud Vision to allow users to search untagged images, or automatically sort images by their content.

The data and capabilities appear to be there. It just hasn't been widely adopted.

Elsewhere in the space, companies like PullString are working on creating more interesting forms of audio chatbots. PullString started creating interactive voice features for children's toys, but it's since expanded to work on software and creative services that power the development of audio-based chat functions for skills on Amazon's Alexa platform.

Now, PullString focuses on developing personality-driven characters on Alexa, whose voice and word choice personify the brand as a whole.

Michael Fitzpatrick, president of PullString, said that brand identity is key when it comes to digital customer service, and chatbots can provide a level of continuity and brand messaging that live agents can't.

"One opportunity, I think, is to spend time designing interactions and model them to reflect truly what the brand's persona is," Fitzpatrick said, mentioning as examples that both Progressive and Geico insurance companies have done well with development of Flo and the Gecko, their respective mascots. After years of TV commercials focused on these characters, it would only seem natural to speak to one of them over Alexa to file an insurance claim or sign up for a new offering, Fitzpatrick said.

Technological barriers

Microsoft Tay AI Though the adoption of customer service chatbots has increased in recent years, there are still some technological barriers that need to be overcome before the technology is as seamless and helpful as its engineers dream it could be.

"The biggest hurdle at the moment is data," Fitzpatrick said. "I think that's true of artificial intelligence more broadly."

Fitzpatrick said that while there is a lot of data out there, it's not always applied in the best manner. Twitter-trained artificial intelligence like Tay, Microsoft's notorious xenophobic chatbot, highlight the need for smarter systems which can tell the different between good and bad inputs.

El Moujahid agreed that data is at front of mind, saying that the biggest limitation right now is the speed at which artificial intelligence can process data, and how much data it requires to accurately train a bot.

"Right now there's a lot of potential with the existing technology," El Moujahid said. "NLP is still in its early days, so we're seeing really interesting stories from around making it faster with less data. There's a notion that those algorithms are powerful but require a large amount of data to train."

Once these hurdles are overcome, however, chatbots could have a much bigger role in our day-to-day lives than they do now. El Moujahid said that it's not hard to imagine a world in which individuals have their own personal assistant-style bots to help with mundane tasks, like calling the cable company.

"There's no reason to imagine at some point you won't have your assistant interacting with the brand's bot," El Moujahid said.

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robot

What is a Chatbot?

You've likely talked to a robot already without even knowing it. And you might have even heard the term "chatbot" in the news. But what is a chatbot? How do chatbots work?

Essentially, a chatbot is just a robot chat that imitates human conversations through voice commands, text chats, or both. It's a virtual conversation in which one party is an online talking robot.

The artificial intelligence feature within talking robots has been used in various industries to deliver information or perform tasks, such as telling the weather, making flight reservations, or purchasing products.

Chatbot Technology

Inside the artificial intelligence of a chatbot is machine learning and what's known as natural-language processing (NLP). Machine learning can be applied in different fields to create various chatbot algorithms, while NLP has the ability to pick up conversational cadences and mimic human conversation.

The chatbot is trained to translate the input data into a desired output value. When given this data, it analyzes and forms context to point to the relevant data to react to spoken or written prompts. Looking into deep learning within AI, the machine discovers new patterns in the data without any prior information or training, then extracts and stores the pattern.

This machine learning algorithm, known as neural networks, consists of different layers for analyzing and learning data. Inspired by the human brain, each layer is consists of its own artificial neurons that are interconnected and responsive to one another. Each connection is weighted by previous learning patterns or events and with each input of data, more “learning” takes place.

Brain

How Chatbots Got Smarter

With the advancements in artificial intelligence and the rapid growth of messaging apps, chatbots are becoming increasingly necessary in many industries. Although bot technology has been around for decades, machine-learning has been improving dramatically due to the heightened interest from key Silicon Valley powers.

Natural language processing mimics human speech patterns to simulate a human tone in computer-human interaction, which creates more intimate interactions. The predictive analytics within bots uses statistics, modeling, data mining and more to generate information proactively, rather than in response to a prompt.

The sentiment analysis in machine learning uses language analytics to determine the attitude or emotional state of whom they are speaking to in any given situation. This has proven to be difficult for even the most advanced chatbot due to an inability to detect certain questions and comments from context. Developers are creating these bots to automate a wider range of processes in an increasingly human-like way and to continue to develop and learn over time.

An indicator of just how human-like these machines can be was actually developed in the 1950s by British scientist Alan Turing. His Turing Test checks the presence of mind, thought, or intelligence in a machine and if it can fool a human to believe that it is a human as well, then it passes the test.

There was a time when even some of the most prominent minds believed that a machine could not be as intelligent as humans but in 1991, the start of the Loebner Prize competitions began to prove otherwise. The competition awards the best performing chatbot that convinces the judges that it is some form of intelligence. But despite the tremendous development of chatbots and their ability to execute intelligent behavior not displayed by humans, chatbots still do not have the accuracy to understand the context of questions in every situation each time.

Chatbots Uses of Today and Tomorrow

Chatbots currently operate through a number of channels, including web, within apps, and on messaging platforms. They also work across the spectrum from digital commerce to banking using bots for research, lead generation, and brand awareness. An increasing amount of businesses are experimenting with chatbots for e-commerce, customer service, and content delivery.

Furthermore, major banks today are facing increasing pressure to remain competitive as challenger banks and fintech startups crowd the industry. As a result, these banks should consider implementing chatbots wherever human employees are performing basic and time-consuming tasks. This would cut down on salary and benefit costs, improve back-office efficiency, and deliver better customer care.

More to Learn

Chatbot technology will continue to improve in the coming years. Chatbot architecture and design will evolve to the point that interactive AI will become standard for customer service. But there are numerous applications for chatbots across a variety of sectors.

That's why BI Intelligence, Business Insider's premium research service, has put together a bundle of detailed reports on chatbots:

To get all four reports, subscribe to an All-Access pass to BI Intelligence and gain immediate access to this report and more than 250 other expertly researched reports. As an added bonus, you'll also gain access to all future reports and daily newsletters to ensure you stay ahead of the curve and benefit personally and professionally. >>Learn More Now

You can also purchase and download the full reports using the links above.

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alone sad depressed sea

Depression is the leading cause of disability worldwide, and it can kill. But scientists know surprisingly little about it. Even with awareness programs like World Mental Health Day, which happens every year on October 10, our knowledge of the condition is extremely limited.

We do know, however, that talking seems to help — especially under the guidance of a licensed mental health professional. But therapy is expensive, inconvenient, and often hard to approach. A recent estimate suggests that of the roughly one in five Americans who have a mental illness, close to two-thirds have gone at least a year without treatment.

Several Silicon Valley-style approaches to the problem have emerged: There are apps that replace the traditional psychiatry office with texting, and chat rooms where you can discuss your problems anonymously online.

The newest of these tech-based treatments is Woebot, an artificially intelligent chatbot designed using cognitive-behavioral therapy, or CBT, one of the most heavily researched clinical approaches to treating depression.

Before you dismiss Woebot as a half-baked startup idea, know that it was designed by Alison Darcy, a clinical psychologist at Stanford, who tested a version of the technology on a small sample of real people with depression and anxiety long before launching it.

"The data blew us away," Darcy told Business Insider. "We were like, this is it."

The results of the trial were published Tuesday in the Journal of Medical Internet Research Mental Health.

For the test, Darcy recruited 70 students who said they experienced symptoms of depression and anxiety and split them into two groups. One group spent two weeks chatting with Woebot; the other was directed to a National Institute of Mental Health e-book about depression. Over two weeks, people in the Woebot group reported not only chatting with the bot almost every day, but seeing a significant reduction in their depressive symptoms.

That's a promising result for a type of treatment whose results have so far been tough to quantify — we don't have a lot of research comparing bot-to-human therapy with traditional human-to-human therapy.

Woebot uses CBT to talk to patients, and several studies suggest the approach lends itself to being administered online. A review of studies published recently in the journal World Psychiatry compared people who received CBT online with people who received it in person and found that the online setting was just as effective.

Dr. Ali Darcy Headshot 2 One reason for this, according to Darcy, is that CBT focuses on discussing things that are happening in your life now as opposed to things that happened to you as a child. As a result, instead of talking to Woebot about your relationship with your mom, you might chat about a recent conflict at work or an argument you had with a friend.

"A premise of CBT is it's not the things that happen to us — it's how we react to them," Darcy said.

Woebot uses that methodology to point out areas where a person might be engaging in what's called negative self-talk, which can mean they see the environment around them in a distorted way and feel bad about it.

For example, if a friend forgot about your birthday, you might tell Woebot something like, "No one ever remembers me," or "I don't have any real friends." Woebot might respond by saying you're engaging in a type of negative self-talk called all-or-nothing thinking, which is a distortion of reality. In reality, you do have friends, and people do remember you. One of those friends simply forgot your birthday.

"Self-talk is a part of being human," Darcy said. "But the kinds of thoughts that we have actually map onto the kinds of emotions we're feeling."

Darcy is quick to point out that Woebot is not a replacement for traditional therapy, but an addition to the toolkit of approaches to mental health.

"I tend to not think of this as a better way to do therapy. I think of this as an alternative option," Darcy said. "What we haven't done a good job of in the field is give people an array of options. What about the people who aren't ready to talk to another person?"

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NOW WATCH: How to know if you're actually depressed

“fbmessenger”

All the recent chatter about chatbot ideas is not exclusive to just one industry, as they have been customized for many uses and tailored to various businesses. Chatbot uses typically fall into research, lead generation, customer service, content distribution, or affiliate marketing, all of which can look very different in various industries.

Below, we've compiled a list of chatbot examples and chatbot uses currently in place.

Companies Using Chatbots

Insurance Chatbot

In 2016, Allstate upgraded its commercial insurance line for small businesses. After the launch, agents jammed the internal call center inquiring about the policies and how to set sales quotes, but expanding the call center was out of the question for Allstate.

Soon after, the company developed an AI virtual assistant called Allstate Business Insurance expert (or ABIe), which now handles questions from 12,000 agents and eventually answers inquires directly from customers. By the end of the first year, ABIe had paid itself off, according to Allstate.

Financial Chatbot

Capital One Financial developed Eno, a chatbot leveraged by artificial intelligence to communicate with their customers via text messages. Currently only available for a small pilot of customers, Eno provides users updates and information immediately, and can even pay bills upon request. It has access to give you information on your balances, recent transactions, credit card due dates, and credit card limit. Unlike other chatbots, Eno only uses text messages but does not require the user to install another application.

Hotel Chatbot

Marriott International's chatbot is available through Facebook Messenger, Slack, and, soon, WeChat and Google Assistant. It allows Marriott Rewards members to research and book travel in more than 4,700 hotels. You can also plan for upcoming trips with suggestions linked from Marriot’s digital magazine Marriott Traveler, all while chatting directly with the Customer Engagement Center. Of Rewards Members using Facebook Messenger, 44 percent successfully received assistance related to their stay or reservation, and 53 percent received help with their Rewards account Marriott believes that the integration on chatbots will improve hospitality and increase their customer satisfaction.

Therapy Chatbot

“fbmessenger”

Woebot is used primarily through Facebook Messenger as an artificially intelligent chatbot that is trained in cognitive-behavioral therapy (CBT), one of the most widely known methods of treating depression. Woebot tracks your mood and will show users how their moods change while maintaining privacy and finding patterns that might be more difficult for the average user to analyze. It talks about your mental health and wellness from brief daily conversations about what’s going on in the user’s life and how they are feeling that day. Woebot also sends useful videos and other tools depending on your mood and needs at the moment.

Real Estate Chatbot

Apartment Ocean is an AI-powered real estate chatbot that builds relationships with potential clients using personalized greetings through Facebook Messenger. It also allows users to work on qualified leads to increase revenue and provide detailed customer support rather than spending time answering common customer questions. Chats with potential clients are automatically analyzed by the chatbot to extract essential information and allow faster conversions from potential clients.

Restaurant Chatbot

One of chatbots’ many appeals to businesses is their ability to integrate with existing messaging applications such as Facebook Messenger or WhatsApp. Chatobook is a chatbot that uses Facebook Messenger to connect with a restaurants’ customers and answer any questions that has to do with the restaurant at anytime of the day. The restaurants’ bot can take reservations, show off menus and promotions to customers, and collect feedback without additional manpower or platforms.

Chatbot Ideas & Applications for Other Industries

“fbmessenger”

The healthcare industry has seen a recent growth in innovative developments to reduce the cost of healthcare. HealthJoy set out to inform employees of their benefits and claims so that employers can reduce healthcare costs. This can only be done if employees are able to successfully navigate their way through the healthcare system.

HealthJoy is described as an operating system for healthcare engagement that reviews medical bills and optimizes prescription drugs to find the lowest prices for a procedure. It also helps people with their health savings accounts and pushes wellness information.

Other applications such as HealthTap or Your.MD help diagnose patients with common symptoms using AI. They can also direct them to booking an appointment with a doctor. The ability to provide advice and information for health and wellness can prevent long-term illnesses or symptoms that can be prevented with proper knowledge and access to information. For example, sexually transmitted diseases could be reduced with access to sex education.

Visabot, the first immigration robot powered by AI, can help immigrants to the U.S. get green cards by pulling all the relevant open data about the user, inform them of required documents needed, and ensure forms are accurately filled. Since its beginning at the end of 2016, this San Francisco-based startup has helped more than 70,000 users apply for immigration services.

Cost savings and improved user satisfaction will continue to drive chatbots growth

Twenty-four hour service and reduced costs for companies are only a portion of how beneficial chatbots can be for any industry. Companies can increase customer satisfaction with the elimination of repetitive and time-consuming tasks for more face-to-face service, and users can save hundreds of dollars because they won't need to book appointments. Chatbots have proven to improve human interactions and are able to connect with hundreds of humans at any moment, which only helps them develop a better sense of how to fulfill the emotional needs of customers.

More to Learn

Chatbots for business will continue to improve in the coming years. Chatbot architecture and design will evolve to the point that interactive AI will become standard for customer service. But there are numerous applications for chatbots across a variety of sectors.

That's why BI Intelligence, Business Insider's premium research service, has put together a bundle of detailed reports on chatbots:

You can also purchase and download the full reports using the links above.

Join the conversation about this story »

Shopping

Traditional retailers with large in-store presences are struggling to keep up with customer satisfaction now that customers have the option to shop via online and mobile phones.

Customers can, and do, ask for support, take advantage of deals, and browse various stores within chat apps. As a result, retailers are turning to chatbots to give customer more accessibility to merchants. These retail chatbots offer consumers a variety of options, generally in a question-and-answer format with the ability to complete tasks without ever leaving their messaging application.

However, without a buying functionality within the chat app, there is a partition in the customer experience that opens up opportunity for payment firms and card networks or processors to break through.

What is “Conversational Commerce”?

The integration of messaging apps and online shopping allows businesses to utilize applications such as Facebook Messenger, WeChat, WhatsApp, or even voice technology like the Amazon Echo. Customers can chat with an AI robot and ask questions, receive customer commands and personalized recommendations, or purchase products all within one channel. With conversational commerce, customers are able to interact with human representatives, chatbots, or both.

Conversational commerce is not exclusive to only messenger chatbots, but also company representatives. For businesses, these e-commerce chatbots can be used to automate customer service messages and send information regarding their orders (such as shipping and delivery notifications) resolve any issues and interact with customers in real-time. Already, companies are partnering up with chat applications to create a simpler environment for customers to utilize their business.

Examples of E-Commerce Chatbots

eBay ShopBot, which launched in October 2016, was an attempt to battle the ongoing decline in eBay's gross merchandise volume and to increase marketplace awareness. RJ Pittman, the Chief Product Officer of eBay, said in an interview with Forbes that Shopbot had created an opportunity for eBay to reach a new group of shoppers through Facebook Messenger, one of the top messaging applications.

ShopBot uses personalized shopping techniques that can save shoppers time and money by searching for deals through simple conversation or a photo, and can even create a size profile so that their curated collections and searchable inventory can give users the right size. When customers are prepared to purchase items, Facebook Messenger allows users to enter their credit card number and place an order within Messenger.

Masterpass Chatbots Subway and MasterCard, the second-largest US card network, partnered together to allow customers to purchase Subway food ahead of time. Using Facebook Messenger, the bot allows customers to choose nearby Subway locations and customize a sandwich. Subway found this as an alternative to customers calling in and keeping employees away from customers in store.

The bot also gives caloric information regarding the menu and quick, easy-to-use response buttons when choosing ingredients in your order. When customers place their order, they can choose to use Facebook’s payment system or Masterpass, a digital payment service from MasterCard, without leaving the application.

Alongside Subway, Mastercard also partnered with FreshDirect, an online grocer that allows users to order groceries in a Messenger chat window individually or as a group with the ability to split payments.

In 2016, Staples brought to life their signature “Easy Button” that takes the form of a two-way speaker that allows users to order and purchase supplies using voice commands as well as via Facebook Messenger, Slack, text, email and the Staples app. Powered by IBM’s Watson, an AI platform targeted to businesses, Staples aims to help businesses save time and have a better overall management of their organization by being available on not only messaging applications, but multiple communication tools for whatever offices prefer.

Chatbots in Online Shopping More Widely Used

facebook messenger bots A number of retailers are partnering with payments players in order to reap the benefits of making chat apps a single retail channel. Because chatbots are still in the preliminary stages of adoption, players already invested might not receive the immediate pay off; however, the growth of chatbots is undeniable.

According to a recent BI Intelligence report, more than 200 million users in China have added payments information into WeChat, a popular messaging application, and WeChat’s parent company now holds 37% market share of the Chinese mobile payment market.

Facebook Messenger has released a number of updates that let brands improve on their customer service and make their platform more attractive to businesses as well as users. Their built-in natural language processing detects message contexts. Messenger’s built-in natural learning processes (NLP), a core algorithm concept in artificial intelligence, enables businesses to scale and make user’s experiences seamless on Messenger. It prompts users and businesses to adopt chatbot retail and chatbot payments.

More to Learn

Shopping chatbots will continue to improve in the coming years. Chatbot architecture and design will evolve to the point that shopping bots will become standard for retail. But there are numerous applications for chatbots across a variety of sectors.

That's why BI Intelligence, Business Insider's premium research service, has put together a bundle of detailed reports on chatbots:

You can also purchase and download the full reports using the links above.

Join the conversation about this story »

alone sad depressed sea

Several tech startups have entered the mental health space in recent years, but few have made a real impact.
Woebot is an artificially intelligent chatbot designed by Stanford researchers. It uses one of the most heavily researched clinical approaches to treating depression.
This week, the company announced that a co-founder of the Google Brain project will serve as Woebot's new chair.

Depression is the leading cause of disability worldwide, and it can kill. Yet scientists know surprisingly little about it.

They do know, however, that talking seems to help — especially under the guidance of a licensed mental health professional. But therapy is expensive, inconvenient, and often hard to approach. A recent estimate suggests that of the roughly one in five Americans who have a mental illness, close to two-thirds have gone at least a year without treatment.

The newest of these tech-based treatments is Woebot, an artificially intelligent chatbot designed using cognitive-behavioral therapy, or CBT — one of the most heavily researched clinical approaches to treating depression.

On Wednesday, the company announced that Andrew Ng, a co-founder of the Google Brain project, will serve as Woebot's new chairman. The Google Brain research team focuses on artificial intelligence with an emphasis on a machine learning process known as deep learning. According to VentureBeat, Ng believes machine learning could greatly benefit the mental health space, which what led him to Woebot.

Woebot's designer, Alison Darcy, is a clinical psychologist at Stanford. She tested a version of the technology on a small sample of real people with depression and anxiety long before launching it.

"The data blew us away," Darcy told Business Insider. "We were like, this is it."

The results of the trial were published recently in the journal JMIR Mental Health. For the test, Darcy recruited 70 students who said they experienced symptoms of depression and anxiety and split them into two groups. One group spent two weeks chatting with Woebot; the other was directed to a National Institute of Mental Health e-book about depression.

Over two weeks, people in the Woebot group reported that they chatted with the bot almost every day and saw a significant reduction in their depressive symptoms. That's a promising result for a type of treatment whose results have so far been tough to quantify — there isn't much research comparing bot therapy with traditional human therapy.

Several studies have suggested that the CBT approach lends itself to being administered online. A review of studies published recently in the journal World Psychiatry compared people who received CBT online with people who received it in person and found that the online setting was just as effective.

"A premise of CBT is it's not the things that happen to us — it's how we react to them," Darcy said.

"Self-talk is a part of being human," Darcy said. "But the kinds of thoughts that we have actually map onto the kinds of emotions we're feeling."

Darcy is quick to point out that Woebot is not a replacement for traditional therapy, but an addition to the toolkit of approaches to mental health.

DON'T MISS: I've been on antidepressants for a decade — here's the biggest misconception about them

Join the conversation about this story »

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businessman texting

With messaging apps on the rise, chatbots are all the hype now. Chatbots are artificial intelligence systems that interact with users via messaging, text, or speech.

Many are deployed on chatbot platforms such as Facebook Messenger, WhatsApp, WeChat, Slack, or text messages. Facebook’s expansion with Facebook Messenger has been giving businesses the opportunity to better reach their target audience through different APIs, and chatbots are becoming a necessity in certain industries.

Despite the complexity of artificial intelligence used to pick content and context from conversations with users, there are a number of platforms and frameworks available to build a sophisticated chatbot. The ease and accessibility to build a customizable bot alongside the increased usage of messaging apps only proves the growth and strength that will push the chatbot industry forward. As the industry matures, the underlying AI technology continues to develop and grow more sophisticated.

Chatbot Market Stats & Size Data

According to a recent report by Grand View Research, the global chatbot market is expected to reach $1.23 billion by 2025, a compounded annual growth rate (CAGR) of 24.3%. Projections show growth over the forecasted period as chatbots reduce operating costs for enterprises. Chatbots can work in segments such as marketing, payments and processing, and service, but when it comes to revenue, chatbot service has a majority of the market share. Within the global chatbot market, approximately 45% of end users prefer chatbots as the primary mode of communication for customer service inquires.

In a survey by Oracle of chief marketing officers, chief strategy officers, senior marketers, and senior sales executives from France, the Netherlands, South Africa, and the UK, 80% of the respondents said they already used chatbots or planned to use them by 2020. Forty-two percent of participants are embracing automation technologies, 48% are already using automation technologies, and 40% are planning to implement automation by 2020. If companies were already weary of the use of chatbots before, they are now feeling the pressure to integrate more innovative technology to better their businesses.

Chatbot Trends & Growth

The four top messaging apps surpassed the top four social networks in terms of global monthly active users in 2015, and they continue to grow. The more activity messaging apps receive from users, the greater the opportunity for chatbots to facilitate usage of messaging apps.

In a survey by LivePerson, which included 5,000 consumers from six countries, 33% of consumers rated a positive perception of chatbots, compared to the 19% of participants that rated a negative perception. The remaining 48% were indifferent as long as their issue was resolved.

Some of AI and machine learning’s biggest advancements in recent years have been in perception and cognition. Voice recognition still has a way to go but Apple, Amazon, and Google have made leaps and bounds on advancements in voice recognition with Siri, Alexa and Google Assistant, respectively.

According to a study by Stanford computer scientist James Landay, speech recognition is on average three times as fastas typing on a cell phone, and the error rate has dropped 3.6%. Other improvements such as image recognition have also had reduced error rates.

Machine learning systems are now being used to decide trades done on Wall Street and to predict if users will click on particular ads, increasing efficiencies on both the business and consumer ends. In addition to being revenue generators, chatbots can also serve as research bots, or for lead generation and brand awareness to save businesses money. As more businesses and consumers use chatbots, the more demand will exist for better development of chatbots, thus making it easier for companies to implement them within their business.

Chatbot Ecosystem & Company Landscape

The chatbot ecosystem is quickly expanding despite the relatively robust ecosystem that currently exists. The ecosystem of the underlying technology and platforms for chatbots include deployment channels, third-party chatbots, companies that provide the technology for building chatbots, and native bots.

Deployment channels such as messaging apps, cloud networks, SMS, and email clients are where chatbots live and interact with users. Third-party chatbots are brands and businesses that a customer may use to, for example, order an Uber through Facebook Messenger. Bot building companies are typically third-party companies that employ AI technology to help businesses deploy their own chatbot across a platform. Finally, native bots are built by the platform or app in which they are operating (for example, Apple’s Siri or Google Assistant).

More and more major companies continue to announce their support for chatbots within their own business, such as LinkedIn, Starbucks, British Airways, and eBay. The key players within the chatbot industry, such as Facebook, Google, Microsoft, and Telegram, have been investing in the development of chatbot technologies for years and continue to work on major bot projects.

The rise of chatbot usage has launched an abundant amount of startup tech following in their footsteps in a variety of industries. Some chatbot startups such as Kasisto, Pypestream, and Automat.ai, are strong in funding and have the potential to revolutionize the industry.

More to Learn

That's why BI Intelligence, Business Insider's premium research service, has put together a bundle of detailed reports on chatbots:

You can also purchase and download the full reports using the links above.

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2 chat app users

This is a preview of a research report from BI Intelligence, Business Insider's premium research service. To learn more about BI Intelligence, click here.

To keep pace with the ongoing shift toward e- and m-commerce, retailers are turning to chat apps, where smartphone users spend considerable time each day.

One way they’ve been accessing consumers on these platforms is through chatbots, or software programs that use business-to-consumer (B2C) text-based messaging as an interface through which customers can communicate with merchants in a question-and-answer format.

For merchants, these offerings are valuable because sales increase as customers communicate with and shop from their brand on more channels. But there’s considerable friction — in chat apps, payments offerings are limited, which means users who might be browsing in a messaging app will still be redirected to another app or the mobile web to complete a purchase.

This is creating an opportunity for payments processors and card networks, which are beginning to partner with merchants to capture potential volume from chat apps. And as the hype increases, other payments firms, like remittance providers and banks are also entering the game, in the hopes of increasing user engagement or attracting new types of clients.

There’s a long road ahead: We’re just at the beginning of what’s likely to be a long adoption cycle, with payments firms only starting to dip their toes into the space. But improvements in the ecosystem, combined with rising consumer appetite for these services and increasing trust, will eventually lead to moderate gains in usage that open up a massive volume opportunity for Western firms.

BI Intelligence, Business Insider's premium research service, has put together a detailed report on chatbots' role in the payments ecosystem.

Here are some key takeaways from the report:

Chat apps are the next frontier for digital commerce, but without payments functionality, the opportunity is extremely limited. Customers can — and do — ask for support, take advantage of deals, and browse many stores within chat apps. But when it comes time to pay, users have to switch to another app or the mobile web — a turnoff that could hinder adoption and lower conversion rates.
Most payments firms are teaming up with retailers, often those they already count as clients, to enable customers to make payments using their mobile wallets or processing features within chat apps. That’s allowing retailers to get to the space faster while opening a revenue opportunity for payments players. Others are taking less direct approaches, working to increase consumer engagement in a way that promotes more spending offline.
We’re at the beginning of an adoption curve, so digital payments providers shouldn’t expect massive success quickly, but in the long run, it’s likely to be a large market. As firms work to grow consumer awareness and improve the experience, the technology will eventually become mainstream, which makes getting in early and becoming established worthwhile.

In full, the report:

Explains why the chat app is the next frontier for commerce, and why payments functionality is a linchpin of that success.
Details different types of chat app payments and their potential use cases.
Evaluates the hurdles that could prevent consumers from using chatbot payments.
Suggests ways firms can overcome these hurdles and begin seeing adoption.
Sizes the potential long-run market for chatbot payments in the West.

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Advancements in artificial intelligence are dramatically changing businesses, and chatbots are slowly becoming vital to customer service channels.

AI and machine learning advancements are able to detect the content of customers’ requests and questions and service inquires accordingly. With messaging apps continuing to surpass social media networks in usage, chatbots also continue to grow in popularity.

A business needs to adapt to consumers' needs and demands, and then utilize more efficient solutions to assist customers. Chatbots are revolutionizing the way companies stay with customers by giving customers the ability to contact the company through messaging apps, email, or text to help foster brand loyalty.

Customer Service Chatbots

A single negative customer service experience can deter potential customers from a company. In a report by BI Intelligence, 60% of US consumers have not completed an intended purchase based on poor customer service experience, which can translate to billions of dollars lost in sales for U.S. retailers alone.

With the abundant amount of options consumers have to consider, online customer service has increased user’s willingness to interact with businesses electronically.

Convenience is a key component of the customer experience, therefore a 24/7 chatbot that handles customer service is a cost-effective and powerful way to provide basic support to consumers.

Ideally, customers receive the same level of service they would with a representative, but if an issue too complex arises, the customer could be redirected to a human representative. Typically, customer service chatbots answer inquires based on keywords. However, the advancements in AI have given chatbots the power to ask questions, create context and intent, and better assist customers.

customer service phone call

Customer service chatbots focus on multi-step processes or input parameters to better aid customers more quickly, rather than asking multiple questions. The built-in natural learning processing (NLP) allows chatbots to understand and handle customer requests faster.

High volumes of requests or FAQs take time away from agents that could be assisting customers with more complex issues, and customer service bots reduces time. For example, airlines utilize Facebook Messenger’s chatbot platform to better reach their customers. Flyers won’t have to answer a series of step-by-step questions, but simply ask the bot to search for flights to the destination of their choice and to book their flights within the Messenger app.

Virtual Assistant Chatbots

The difference between a customer service chatbot and a virtual assistant chatbot (VAC) are their functions. Otherwise, their underlying technologies are similar. Supported by artificial intelligence, both are able to understand information fed either through text or speech recognition. Like customer service chatbots, VACs provide information, services, and assistance about web pages, and support a wide range of applications in business, educations, government, healthcare, and entertainment.

Some virtual assistants are more commonly used in helping employees of an organization instead of external audiences. VACs can carry out a range of tasks to better organize an office such as creating lists, scheduling any appointment or reminders, opening software, or activating smart devices. All of these can be controlled by voice commands or through text.

Staples partnered with IBM to bring their signature “Easy Button” to life with the cognitive capability of Watson. They focused on simplifying office management and their customer experience. The Easy Button now has voice recognition and can detect requests specific to an office’s business needs, such as ordering products and tracking shipments.

Chatbots for Websites

Chatbots on websites can generate leads and increase conversion rates if implemented correctly. Integration of chatbots within companies’ websites can make it easier for users to navigate the site and customize the user experiences.

Not only strictly for websites or for messaging apps, chatbots can be configured to many platforms for multiple uses. Nuance Communications, Inc. developed a chatbot named Nina, a human-like virtual assistant that delivers a customer experience that enables self-service capabilities via quick and easy access to information for customers and service agents. Nuance Communications develops customer engagement solutions powered by AI for businesses in various industries.

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That's why BI Intelligence, Business Insider's premium research service, has put together a bundle of detailed reports on chatbots:

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Some of the best artificial intelligent chatbots are created from a demand for better service, more efficient management, or just curiosity. These chatting bots are applicable to various industries and are accessible to an abundant amount of users, which opens doors to an endless amount of opportunities.

In the recent years, the growth in popularity of chatbots has been the result of the amount of research poured into its underlying technology. These AI-powered bots are now being integrated in various industries such as payments, banking, customer service, and even pure personal amusement. The birth of chatbots developed from the curiosity of whether a robot can really fool any human into believing that it is human as well.

Here are some of the smartest bots that you can talk to:

Cleverbot

Cleverbot is a chatbot web application that uses artificial intelligence to communicate with humans. Rollo Carpenter launched it in 1997, and it has since gone through a number of redevelopments that allows it to collect a large amount of data based on conversational exchanges with people online (or through crowdsourcing).

This form of obtaining information from the collective intelligence of a large number of people allows Cleverbot to respond in new conversations by taking into account the context of the conversation typed by a user and searching its database for an appropriate response. It scans its history for every user-submitted response to the given question and replies accordingly, which creates a more human-like conversation with users.

Existor is the algorithm used to developed Cleverbot, as well as EvieBot, BoiBot, PewDieBot, and ChimBot. It offers a wide-range of bot and AI-related products alongside bot development, such as apps and mobiles games, the Clever data set, and Cleverscript for scripted conversations. The underlying technology in Cleverbots not only processes verbal and textual interactions, but also the timing and degree of the avatars’ facial expressions and movements to create a more authentic conversation experience.

Eviebot

One of the more popular artificial personalities on YouTube that has been around for over a decade, Evie can speak French, German, Polish, Turkish, and English.

Boibot

Developed as counterpart of Eviebot, Boibot was released in June 2015 and shares the same capabilities as Evie.

PewDieBot

Developed based off a Swedish web-based comedian and video producer who is best known through his YouTube channel. He was also named the highest-paid YouTuber at $15 million in 2016.

pewdiepie looking at camera angry

Chimbot

Released in November 2015, Chimbot is an artificial personality that takes the form of a chimp avatar. Able to speak a number of languages, Chimbot understands more than the average chimpanzee.

ELIZA Chatbot

Created in 1966 as an early natural language processing (NLP) computer program that emulates a Rogerian psychotherapist, a clinical practice that allows clients to take more action and progression in discussions. This is also known as person-centered therapy. Developed by Joseph Weizenbaum, ELIZA, named after a character in the play Pygmalion by George Bernard Shaw, is generally known as the first chatbot.

Levi Chatbot

Created by a developer by the username of Amena-chaan on DeviantArt, Levi is an anime avatar known for his cool, indifferent nature. His popularity even inspired an interactive game created by another developer. Utilizing the same underlying technology as most chatbots, Levi’s conversations are archived and accessible for him to use when speaking with new users.

Answer Bot

Developed by Zendesk, a customer service platform that started in Copenhagen, Answer Bot is designed to help companies create customer relationships that are more personal and productive. Businesses can customize Answer Bot to answer and assist customers that visit their website without having to develop a customer service bot from scratch. When Answer Bot is unable to answer a customer’s request, customers are redirected to one of the businesses’ support agents.

Kiyana Chatbot

Described as a “friendly mythical flirt,” Kiyana is popular among users that look for more intimate and romantic relations with online robot chats. Created in June 2005, Kiyana’s persona is portrayed as a girl who likes to sing and talk about cats, and is favored among her guests who choose to speak with her.

Rose Chatbot

Having placed in the Loebner Prize competition, Rose is a bot with the persona of a 31-year old security analyst and hacker from San Francisco and a self-described “computer nerd” from an “unorthodox family.” Developed by Bruce Wilcox, Rosette, the earlier version of Rose, placed at the Loebner Prize in 2011 and again in 2014 as Rose.

Mitsuku

Running on Pandorabots, one of the most powerful conversational artificial intelligence chatbot platforms, Mitsuku won the award for the most human-like AI in 2013 and again in 2017. She was created from AIML, a bot language technology by Steve Worswick, who found the inspiration for Mitsuku after being asked to write her character for an internet games site.

More to Learn

The possibilities for advancements in chatbots are endless and waiting to be developed. As AI continues to grow in technological achievements and intelligence, chatbots can affect more than just the individual.

Chatbots for business will continue to improve in the coming years. Chatbot architecture and design will evolve to the point that interactive AI will become common in everyday life with the numerous applications for chatbots across a variety of sectors.

That's why BI Intelligence, Business Insider's premium research service, has put together a bundle of detailed reports on chatbots:

You can also purchase and download the full reports using the links above.

Join the conversation about this story »

bii chatbots_users

This is a preview of a research report from BI Intelligence, Business Insider's premium research service. To learn more about BI Intelligence, click here.

Improving artificial intelligence (AI) technology and the proliferation of messaging apps — which enable users and businesses to interact through a variety of mediums, including text, voice, image, video, and file sharing — are fueling the popularity of chatbots.

These software programs use messaging as an interface through which to carry out various tasks, like checking the weather or scheduling a meeting. Bots are still nascent and monetization models have yet to be established for the tech, but there are a number of existing strategies — like "as-a-service" or affiliate marketing — that will likely prove successful for bots used as a tool within messaging apps.

Chatbots can also provide brands with value adds — services that don't directly generate revenue, but help increase the ability of brands and businesses to better target and serve customers, and increase productivity. These include bots used for research, lead generation, and customer service.

A new report from BI Intelligence investigates how brands can monetize their chatbots by tailoring existing models. It also explores various ways chatbots can be used to cut businesses' operational costs. And finally, it highlights the slew of barriers that brands need to overcome in order to tap into the potentially lucrative market.

Here are some of the key takeaways:

Chatbot adoption has already taken off in the US with more than half of US users between the ages of 18 and 55 having used them, according to exclusive BI Intelligence survey data.
Chatbots boast a number of distinct features that make them a perfect vehicle for brands to reach consumers. These include a global presence, high retention rates, and an ability to appeal to a younger demographic.
Businesses and brands are looking to capitalize on the potential to monetize the software. BI Intelligence identifies four existing models that can be successfully tailored for chatbots. These models include Bots-as-a-Service, native content, affiliate marketing, and retail sales.
Chatbots can also provide brands with value adds, or services that don't directly generate revenue. Bots used for research, lead generation, and customer service can cut down on companies' operational costs.
There are several benchmarks chatbots must reach, and barriers they must overcome, before becoming successful revenue generators.

In full, the report:

Explains the different ways businesses can access, utilize, and distribute content via chatbots.
Breaks down the pros and cons of each chatbot monetization model.
Identifies the additional value chatbots can provide businesses outside of direct monetization.
Looks at the potential barriers that could limit the growth, adoption, and use of chatbots and therefore their earning potential.

Interested in getting the full report? Here are several ways to access it:

Subscribe to an All-Access pass to BI Intelligence and gain immediate access to this report and over 100 other expertly researched reports. As an added bonus, you'll also gain access to all future reports and daily newsletters to ensure you stay ahead of the curve and benefit personally and professionally. >>Learn More Now
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NOW WATCH: Unboxing the iPhone X: Here's everything inside and what you'll need to get

rock em sock em robots boxing toy machines

Everyone is jumping on AI and its advancements and growth in popularity in the recent years have proved a valuable opportunity for businesses and households.

Big industry players have already made strides in research, and some of the largest tech companies in the world have been investing in building their own AI framework, making it accessible not only to enterprises but also independent developers.

Large tech companies are harnessing the power of AI as more research developments are making strides in improvement in artificial intelligent technology.

Here is how some of the tech giants are approaching chatbots:

Amazon Chatbot – Alexa

The success of its Echo products spurred Amazon to put Alexa into a wider range of devices such as lamps, speakers, clocks, and cars. Earlier in 2017, Amazon launched a smart Wi-Fi speaker that uses voice recognition to not only respond to commands, but also display what it sees. It is a 7-inch touchscreen-equipped digital assistant called Echo Show powered by Alexa that allows you to connect home appliances and accessories.

Amazon wants its technology to be the dominant voice computing platform. To that end, the company is making its voice control technology available to all and is giving developers the ability to access the power tools used by Alexa. Amazon Lex combines speech recognition, text recognition, and conversational interactions to make it easier for tech companies to integrate voice or text-based chat interfaces for their apps.

Google Chatbot – Cleverbot

Google Assistant has been making large technological strides recently. In response to the Amazon Echo, Google Assistant is similar to Google Now, but the service goes beyond your phone and is integrated into Google Home.

It operates in multiple languages and offers more games and activities, including a partnership with Target that allows users to order Target products using voice commands. Google Assistant also responds to voice commands and text commands, which give users the ability to use its services anywhere their phone goes, even on an iPhone. Finally, in an effort to be more versatile and expand its reach, Google also launched Google Assistant on Android TV earlier this year.

Microsoft Chatbot – Tay

Despite its short-lived AI bot Tay, (who was released online through various social media platforms and then taken down within 24 hours after Twitter users corrupted the chatbot by teaching it racist and sexist terminology), Microsoft believes its AI technology and its ability to create chatbots with conversational capabilities sets it up to become the bot platform for companies already using Microsoft tools.

Microsoft released two AI-powered chatbots in the last few years: Xiaoice in China in 2014 and Rinna in Japan in 2015. It also debuted Unibot, which allows students to manage their courses and pay their university. Microsoft targeted Unibot towards non-English speaking students trying to navigate American university websites.

In addition to launching their chatbots and integrating the AI-assistant Cortana into their products, Microsoft launched Bot Framework in early 2016, which give developers the tools they need to create chatbots using Microsoft’s AI technology. Similarly, Microsoft’s Cognitive Services will let businesses build customizable chatbots.

IBM - Watson

ibm watson Watson is a cloud-based AI platform that provides optimal performance and services that can be used to build custom chatbots. The underlying AI technology is available to developers and clients to build, test, and deploy bots or virtual agents across mobile devices and messaging platforms to imitate natural conversations between users and their apps.

In 2016, IBM released the Watson Conversation, a cloud-based cognitive system that makes its possible for developers to custom build a chatbot, or to incorporate one within a business. For example, Staples integrated Watson Conversation into their “Easy System” to create a seamless office supply ordering interface.

Other Companies Getting Into The Mix

Earlier this year, Twitter deployed a way for advertisers to promote ads designed to pull consumers into personalized experiences within Direct Messaging, which includes interactions with chatbots. By adding a “Direct Message Card,” consumers can use it to connect with businesses. Businesses can also customize the card with an image or video. The cards should help businesses to reach out to more potential customers, as well as prompt customers to re-share the experience through a tweet following their interactions with the bot.

Microsoft also unveiled a bot framework and chatbot for Skype where Cortana was integrated directly into the app where she could identify the people, places, and things in your messages and display more information in a more user friendly interface. More recently, they also added support for chatbots to LinkedIn to help users look for and start conversations with appropriate connections.

More to Learn

That's why BI Intelligence, Business Insider's premium research service, has put together a bundle of detailed reports on chatbots:

You can also purchase and download the full reports using the links above.

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Ignition

AI tech is rapidly growing, and so are the number of chatbot, data science, and AI conferences to discuss the future of this technology.

We've compiled a list of conferences, events, and summits for 2018 (and the remainder of 2017):

2017

The AI Summit

When: December 5^th to 6^th

Where: New York City, NY

Summary: Only open to qualified business leaders, the summit includes 2017 Industry Partners Amazon Web Services, Google Cloud Platform, DRYiCE, IBM Watson, Microsoft, Sapient Razorfish, Facebook, and PwC. The AI Summit New York gathers more than 1,000 of the most senior business CxOs, AI visionaries, AI start-up innovators, press/media, and acclaimed researchers.

AI World Conference & Expo: State of the Practice of Enterprise AI

When: December 11^th to 13^th

Where: Boston, MA

Summary: The industry’s largest independent event that focuses on the state of the practice of enterprise AI and machine learning that will help businesses and technology executives learn how advanced intelligent technologies are being deployed.

2018

Re.Work Fifth Global AI Assistant Summit

When: January 25^th to 26^th

Where: San Francisco, CA

Summary: Co-located with the Deep Learning Summit and the Women in AI Dinner, the summit will showcase the opportunities of advancing trends in AI assistants and the latest technological advancements and industry trends with business leaders, influential technologists, data scientists, and entrepreneurs.

The Third International Chatbot Summit

When: January 30^th to 31^st

Where: Tel Aviv, Israel

Summary: Their mission is to connect the worldwide players who make up this newly-forming digital economy filled with chatbot enthusiasts who believe that chatbots mark the next wave of digital revolution.

AIEvolution: The Cognitive Enterprise

When: February 8^th

Where: New York City, NY

Summary: Attendees will be exposed to the capabilities and possibilities that alter roles in the workforce, relationships with employees, risks and opportunities, and challenge the status quo.

Conversational Interaction Conference

When: February 5^th to 6^th

Where: San Jose, CA

Summary: This conference focuses on an intimate atmosphere to share on how to deliver customer service using natural language, and how diversifying branded digital assistants are implemented into companies to benefit customers.

Modern Data Management Summit

When: February 26^th to 27^th

Where: San Francisco, CA

Summary: Covering the hottest topics within master data management, big data analytics, data science and business facing data-driven applications, attendees can obtain real action points and useful connections to better support their business goals.

Big Data & Analytics Innovation Summit

When: March 6^th to 7^th

Where: Melbourne, Australia

Summary: This is a two-day summit helping businesses understand and utilize data-driven strategies and discover what disciplines will change.

Big Data Innovation Summit

When: March 7^th to 8^th

Where: Las Vegas, NV

Summary: Attendees will learn how to build scalable architecture for highly available data and be exposed to the world’s latest and most advanced data tools and technologies to optimize their test phases.

Analytics and Data Summit 2018

When: March 20^th to 22^nd

Where: San Francisco, CA

Summary: Organized and managed by Oracle BI, Data Warehouse, and Analytics users, this three-day event includes educational sessions by practitioners and developers, hands-on labs, and keynotes by industry experts.

Big Data Innovation Summit

When: March 21^st to 22^nd

Where: London, UK

Summary: Those who attend will explore untouched areas, emerging themes, and new trends to stay ahead with industry leaders. The event will take place across four summits and a variety of industries that will teach techniques to future proof current models, tools, and predictive capabilities.

EmTech Digital

When: March 26^th to 27^th

Where: San Francisco, CA

Summary: This two-day event hosted by MIT Technology Review provides attendees a working understanding of complex tech that drives business innovation and how to harness technological advances to build a competitive advantage.

SpeechTEK 2018

When: April 9^th to 11^th

Where: Washington, D.C.

Summary: An event targeted towards attendees who want to learn more about deploying speech technology for business applications from speakers, in-depth workshops, customer case studies, and discussions.

Applied Artificial Intelligence Conference 2018

When: April 21^th

Where: San Francisco, CA

Summary: Aimed to those involved or interested in the most current progress of AI technologies and products, the one-day conference focuses on the latest and future of AI applications and commercialization across sectors such as Transportation, Healthcare Finance, Future of Work and Cybersecurity.

AI Expo Global 2018

When: April 18^th to 19^th

Where: Olympia, London

Summary: Topics covered include Business Intelligence, Deep Learning, Machine Learning, AI Algorithms, Data & Analytics, and Virtual Assistants & Chatbots. This expo will also be co-hosted alongside the IoT Tech Expo, the largest global gathering for the Internet of Things sector, and Blockchain Expo.

F8 - Facebook Developer Conference

When: May 1^st to 2^nd

Where: San Jose, CA

ODSC East

When: May 1^st to 2^nd

Where: Boston, MA

Summary: This four-day conference offers full days of training, talks, workshops, and networking on the latest data science advances with eight focus areas: Open Data Science, Machine Learning & Deep Learning, Research Bridge, Data Science Kickstart, Big Data Science, Data Visualization, Accelerate AI, and Data Science Management.

Machine Learning Innovation Summit

When: May 10^th to 11^th

Where: San Francisco, CA

Summary: Bringing together industry leaders to share how machine learning technology is transforming business practices and creating innovative new products.

Rise of AI

When: May 17^th

Where: Berlin, Germany

Summary: A one-day, 500-person limit allows attendees to easily network with startups, investors, journalists, clients, and enterprises to discuss the ethical and legal consequences of the increasing use of AP and understanding the difference between Narrow Artificial Intelligence, Strong AI, and AGI.

Data Disrupt

When: May 22^nd to 24^th

Where: New York, NY

Summary: Focused on the impact of large scale data sets, new data courses, innovative analytic techniques, the latest technologies and the more creative entrepreneurs on the financial services sector, the conference will explore the impact of alternative data on lending and investing markets.

Re.Work Machine Intelligence in Healthcare Summit

When: May 24^th to 25^th

Where: Boston, MA

Summary: The summit will showcase the opportunities of advancing methods in deep learning and their impact across healthcare and medicine.

dotAI The Artificial Intelligence Conference for Developers

When: May 31^st to June 1^st

Where: Paris, France

Summary: The conference explores the current state-of-the-art machine learning frameworks and how to build intelligent applications for 2018.

Machine Intelligence Summit

When: June 6^th to 7^th

Where: Hong Kong

Summary: For its 5^th Global summit, it will showcase the opportunities of advancing trends in machine learning and their impact on business and society. Topics include advances in machine learning and smart artificial intelligence as well as speakers from the industry experts in speech and image recognition, neural networks and big data.

The AI Summit London

When: June 13^th to 14^th

Where: London

Summary: Now in its third year, speakers at the summit share a platform that highlights both AI business strategy and technical know-how that help business leaders, data scientists, and engineers implement their AI projects.

The 4^th Research & Applied AI Summit

When: June 29^th

Where: London, UK

Summary: A community designed for entrepreneurs and researchers who accelerate the science and applications of AI technology are focused on companies creating transformational solutions.

Machina Summit.AI: Data Analytics, AI & IOT for the Enterprise

When: October 3^rd to 4^th

Where: London, UK

Summary: Co-located with Cyber Security Europe, this summit explores how Data Analytics, IoT, and Artificial Intelligence are causing major disruption across all industries.

Minds Mastering Machines [M^3]

When: October 9^th to 11^th

Where: London, UK

Summary: Conference sessions and in-depth workshops will familiarize attendees with basic concepts to determine which aspects of products and systems would benefit from machine learning techniques, and how to incorporate and implement them accordingly.

More to Learn

As developments in AI and chatbots continue to improve in the coming years, chatbot architecture and design will evolve to the point that interactive AI will become standard for customer service. But there are numerous applications for chatbots across a variety of sectors. Catch up on current developments in AI and chatbots for businesses.

That's why BI Intelligence, Business Insider's premium research service, has put together a bundle of detailed reports on chatbots:

You can also purchase and download the full reports using the links above.

Join the conversation about this story »

Popular chatbots commonly used today, such as Siri and Amazon Alexa, are examples of how far automated assistants have come.

But they also show how far they still have to go.

Some companies were developing a standalone application because it seemed popular to do so; however, for any application to have a chance at success, it must provide substantial value. Given that the use of messaging apps is growing in popularity, chatbot uses for enterprise have also grown, which has fueled major industry players to integrate more chatbots into their systems for both individual and enterprise use.

Facebook Bots

In 2016, Mark Zuckerberg announced the launch of Facebook’s Messenger Platform, a service that allows businesses of any size to build custom bots into Messenger. It also includes Messenger codes, unique images that are used as a visual thumbprint for businesses and bots on Messenger. This allows businesses to redirect customers to the corresponding company page or bot.

Facebook’s experimental Messenger bot, M, proves the value of a bot and its ability to not only just retrieve simple pieces of information from its database, but understand complex requests as your digital butler.

Similar to Siri, you can type out or speak your request. But when your request cannot be fulfilled, instead of searching the web or replying that it cannot understand, a Facebook human representative invisibly takes over responding to your request as if the algorithms were still decoding your request.

On trial with a few thousand users in 2015, the semi-public R&D project reveals how people would react to an omniscient virtual assistant and provides data that would let the algorithms learn to take over the work of their human counterparts.

Slack Bots

slack

IBM partnered with fast-growing workplace messaging app Slack in 2016 to power the next iteration of Slackbot, Slack’s virtual assistant. The incorporation of IBM's artificial intelligence into the Slack app allows the chat platform to understand the inner workings of a company, as well as an individual user’s role within it.

Its purpose will be to provide useful answers to questions answered by employees. Already, companies that use Slack have employees that spend about 20 percent of their time looking for information or looking for someone who has the information they need.

Among the countless existing frameworks that users have access to online, Slack allows you to build your own chatbot and makes it simple for users to publish their bots on their app store. They also provide detailed launch documentation that you can use as a checklist. Bots must be approved for various permissions and access to data that is dependent on the bot built.

Skype Bots

Microsoft is making its flagship messaging platform Skype open for chatbots with a Skype bot SDK. As a Microsoft product, Skype opened its APIs in 2016, and developers from all around the world could now build chatbots on their platform.

The Skype bot SDK allows developers to write in text, voice, and video bots, which likely feature animated characters. The bot directory makes it easy for Skype users to easily install and search for bots with the feature to discover bots on its own webpage so that users are able to interact directly on the webpage without installing it into the messaging app.

Skype chatbots are able to integrate deep within Microsoft’s own digital assistant Cortana. Cortana can pass the conversation to third-party chatbots as needed to address specific user issues. The conversation control and context are then passed along from bot to bot.

Chatbot Platforms Market Growing

A successful integration of a chatbot creates a perfect vehicle for businesses to reach customers and achieve higher retention rates, while also appealing to a younger demographic.

AI has reached a stage where chatbots have increasingly engaging human conversations and allow companies to leverage this inexpensive and wide-reaching technology. Platforms such as Kik and Facebook Messenger offer a series of responses that users receive quickly. This helps developers build a stronger conversational design philosophy within their chatbot.

More to Learn

That's why BI Intelligence, Business Insider's premium research service, has put together a bundle of detailed reports on chatbots:

You can also purchase and download the full reports using the links above.

Join the conversation about this story »

bii chatbot ecosystem

This is a preview of a research report from BI Intelligence, Business Insider's premium research service. To learn more about BI Intelligence, click here.

Advancements in artificial intelligence, coupled with the proliferation of messaging apps, are fueling the development of chatbots — software programs that use messaging as the interface through which to carry out any number of tasks, from scheduling a meeting, to reporting weather, to helping users buy a pair of shoes.

Foreseeing immense potential, businesses are starting to invest heavily in the burgeoning bot economy. A number of brands and publishers have already deployed bots on messaging and collaboration channels, including HP, 1-800-Flowers, and CNN. While the bot revolution is still in the early phase, many believe 2016 will be the year these conversational interactions take off.

In a new report from BI Intelligence, we explore the growing and disruptive bot landscape by investigating what bots are, how businesses are leveraging them, and where they will have the biggest impact. We outline the burgeoning bot ecosystem by segment, look at companies that offer bot-enabling technology, distribution channels, and some of the key third-party bots already on offer.

The report also forecasts the potential annual savings that businesses could realize if chatbots replace some of their customer service and sales reps. Finally, we compare the potential of chatbot monetization on a platform like Facebook Messenger against the iOS App Store and Google Play store.

Here are some of the key takeaways:

AI has reached a stage in which chatbots can have increasingly engaging and human conversations, allowing businesses to leverage the inexpensive and wide-reaching technology to engage with more consumers.
Chatbots are particularly well suited for mobile — perhaps more so than apps. Messaging is at the heart of the mobile experience, as the rapid adoption of chat apps demonstrates.
The chatbot ecosystem is already robust, encompassing many different third-party chat bots, native bots, distribution channels, and enabling technology companies.
Chatbots could be lucrative for messaging apps and the developers who build bots for these platforms, similar to how app stores have developed into moneymaking ecosystems.

In full, the report:

Breaks down the pros and cons of chatbots.
Explains the different ways businesses can access, utilize, and distribute content via chatbots.
Forecasts the potential impact chatbots could have for businesses.
Looks at the potential barriers that could limit the growth, adoption, and use of chatbots.
And much more.

Interested in getting the full report? Here are several ways to access it:

Subscribe to an All-Access pass to BI Intelligence and gain immediate access to this report and over 100 other expertly researched reports. As an added bonus, you'll also gain access to all future reports and daily newsletters to ensure you stay ahead of the curve and benefit personally and professionally. >>Learn More Now
Purchase & download the full report from our research store. >> Purchase & Download Now

Learn more:

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mark zuckerberg

Facebook is putting an end to M, its hybrid human/artificial digital assistant that helped users make dinner reservations or get gift suggestions.
M first launched in 2015 and never left beta mode. Only a few thousand people ever had access to it.
Facebook isn't scrapping all of its M technology. Companies can still launch chatbots for customer service, and M's key-word driven suggestion feature will stay in place.

Facebook M

Facebook is putting an end to M, an ambitious digital assistant product unveiled two years ago that was supposed to be the company's answer to Apple's Siri and Google's Assistant.

M, which was first announced in August 2015, used a mixture of artificial intelligence and human "trainers," to answer Facebook user's questions in the Messenger app. A user could ask M for a gift recommendation, or to book a dinner reservation, for example.

"We launched this project to learn what people needed and expected of an assistant, and we learned a lot," a Facebook representative said in a statement on Mondayt. "We're taking these useful insights to power other AI projects at Facebook."

The project, which is still in beta, will officially shut down on January 19, Facebook said.

A source close to the situation told Business Insider that M was never rolled out more broadly than a couple thousand Facebook users — a small drop in the bucket for a company with 1.37 billion daily active users.

Though M has seen its last days, Facebook will keep its M "suggestion" feature, which jumps into conversations on its own, in order to suggest relevant stickers or to offer to schedule a meeting.

Other machine learning projects on Facebook, such as a tool that lets companies like Sephora build Facebook chatbots for customer service, will also remain in place.

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Phil Libin headshot

Disco, a startup partnered with Evernote cofounder Phil Libin's young artificial intelligence studio All Turtles, released its product to paying customers Tuesday.
The product tracks positive language within office chat apps like Slack and Microsoft Teams, and then aggregates the comments into positive feedback reports for employees, managers, and executives looking to get a sense of what is going right on their teams.
The idea is that positive reinforcement can keep employees happy and improve office culture.

An artificial intelligence startup backed by Evernote cofounder Phil Libin and Salesforce CEO Marc Benioff wants to automate positive reinforcement.

Disco — one of the first companies to come out the artificial intelligence lab All Turtles, which Libin launched in May— is an employee feedback tool that scans office chat software like Slack and Microsoft Teams for compliments and positive comments.

Those comments are then aggregated into reports that employees can regularly check for positive feedback.

The idea behind it, said CEO Jeremy Vandehey, is that employees work better and harder when they feel that their efforts are recognized by the company.

Disco CEO Jeremy Vandehey Vandehey started developing the product in 2015 after working at companies where positive feedback was hard to come by. He believes that Disco can help companies build a culture of positivity, which ultimately will be reflected in the quality of work.

After members of a particular workgroup invite the Disco bot into their group, the bot quietly monitors and collects examples of each individual's good work. If a company's values involve prioritizing customers for example, Disco will log each time a staffer says or does something that reflects that they prioritize customers.

"At its core, we've simplified the ways you give positive feedback to your coworkers, managers and even you're executives," Vandehey said. "It's basically democratized that whole experience and made it a lot easier to do that every single day, versus once a quarter or even once a year, by being inside of the work stream."

On Tuesday, Disco opened up its product to paying customers. So far the product has enjoyed a hefty beta mode with 20,000 different companies using it internally, including Spotify, Intuit, Adobe, Slack, and Walmart. Disco will charge companies $4 per employee per month, or $3 per person for month for annual subscriptions.

The platform uses natural language processing and machine learning to create profiles for employees based off of what people have said about them in digital environments.

Employers can issue regular feedback reports to show their workers what they're doing well, or to keep track of an employee's strengths for review purposes.

There is one problem though: while Disco has all of the makings of an automated review platform, Vandehey said that there is no mechanism for tracking negative feedback.

"We want to feel good about developing a culture of appreciation before we talk about that," Vandehey said about a negative comment tracker. "It's something a lot of our customers ask for because they want to fully replace performance reviews with real time feedback system. But we don't want to release something like that without really thinking through the consequences of opening up constructive feedback to the masses."

Investors, so far, don't seem to mind the positive approach. Disco has raised $2.15 million in seed funding from General Catalyst, Slack Fund, XSeed Capital, Inventus Capital Partners, 500 Startups, and Salesforce CEO Marc Benioff.

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Growth in Share of Retail Site Visits

This is a preview of a research report from BI Intelligence, Business Insider's premium research service. To learn more about BI Intelligence, click here.

Social media is becoming increasingly influential in shoppers' purchasing decisions. In fact, the top 500 retailers earned an estimated $6.5 billion from social shopping in 2017, up 24% from 2016, according to BI Intelligence estimates.

In addition to influencing purchase decisions, social media is a large part of the product discovery and research phase of the shopping journey. And with more and more retailers offering quick access to their sites via social media pages, and shoppable content becoming more popular, it's likely that social media will play an even larger role in e-commerce.

In this report, BI Intelligence examines the advantages and disadvantages of each platform, and reviews case studies of successful campaigns that helped boost conversion and increase brand awareness. Additionally, we explore how retailers can bring social aspects into their own sites and apps to capitalize on consumers' desire for social shopping experiences.

Here are some key takeaways from the report:

Social media is becoming more influential in all aspects of the purchasing journey.
Facebook is the clear winner in social commerce, with its huge user base and wide-ranging demographics.
However, retailers should have a presence on every platform their target market is on. Each platform will require a different strategy for retailers to resonate with its users.
Retailers can also benefit from bringing social aspects in-house. They can do this by building their own in-house social networks, or by embedding social media posts into their sites.

In full, the report:

Provides an overview of the top social media platforms — Facebook, YouTube, Instagram — that retailers should be using, the demographics of each platform, as well as their individual advantages and disadvantages.
Reviews tools recently developed by these platforms that help retailers create engaging content.
Outlines case studies and specific strategies to use on each platform.
Examines how retailers like Sephora, Amazon, and Poshmark are capitalizing on consumers' affinity for social shopping by creating their own in-house social networks.

Interested in getting the full report? Here are two ways to access it:

Subscribe to an All-Access pass to BI Intelligence and gain immediate access to this report and over 100 other expertly researched reports. As an added bonus, you'll also gain access to all future reports and daily newsletters to ensure you stay ahead of the curve and benefit personally and professionally. >>Learn More Now
Purchase & download the full report from our research store. >> Purchase & Download Now

Join the conversation about this story »

Welcome to Digital Health Briefing, a new email providing the latest news, data, and insight on how digital technology is disrupting the healthcare ecosystem, produced by BI Intelligence.

Sign up and receive Digital Health Briefing free to your inbox.

Have feedback? We'd like to hear from you. Write me at: lbeaver@businessinsider.com

RESEARCHERS TAP DEEP LEARNING TO PREDICT IN-HOSPITAL PATIENT MORTALITY AND READMISSION RATES: Newly published collaborative research from Google, Stanford, the University of Chicago, and the University of California, suggests that artificial intelligence (AI) can be used in combination with electronic health record data to predict mortality, readmission, and other events that have an adverse impact on healthcare in the US.

The study adds considerable weight to the growing body of research in the field of big data and health analytics. Researchers fed almost 47 billion data points, including clinical notes, into deep learning models. These models analyzed the data, which had been de-identified for anonymity, and predicted with significant accuracy things like in-hospital mortality rates, 30-day unplanned hospital re-admissions, prolonged length of stay, and patients' final diagnosis. Moreover, these deep learning models outperformed traditional state-of-the-art predictive models in all instances.

Big data presents a significant cost-saving opportunity for healthcare systems, and researchers are working hard to unlock its potential. Predictive analytics, precision medicine, and population health could help alleviate mortality rates, improve medication adherence, and monitor chronic illnesses such as heart arrhythmias, which are a heavy burden on the healthcare system. Each year in the US, healthcare-related infections lead to more than 99,000 deaths, problems with medication result in more than 770,000 injuries and deaths, and unexpected hospital readmissions cost up to $17 billion, according to Google head of product and research Katherine Chou.

There are a growing number of healthcare systems hoping to leverage the early potential of big data to improve patient quality of care. Several challenges stand in the way of predictive analytics being used en masse. However, small-scale operations are already being explored. Last week, for example, Yale New Haven Hospital announced a partnership with Epic Systems with the aim of using real-time big data to enhance the quality of healthcare. And researchers in Cleveland are looking into using its population and health data to better understand and address people outside of hospitals.

bii healthcare data growth

AI CHATBOT FOR DEPRESSION LAUNCHES IN APP STORE: An AI chatbot designed to help people with feelings of depression and anxiety launched a stand-alone app in the iOS App Store last Thursday, according to Business Insider. The chatbot, dubbed “Woebot,” is programmed to provide scripted responses in line with Cognitive Behavioral Therapy model. Once signed up, Woebot engages with users daily, recording things like mood and energy levels — two symptoms associated with depression and anxiety. Digital tools like Woebot are growing in number as mental health professionals seek new ways to bypass the barriers in the way of providing sufficient patient care. These include things like a lack of resources, not enough trained professionals, and the social stigma around mental illness. Apps and chatbots offer around-the-clock self-monitoring, which may help improve patient outcomes and illness management. They can also help people who are either embarrassed about going to see a professional, or don’t think they have time for regular check-ins get a small-degree of help. In the US, around two-thirds of people with a mental illness are estimated to have gone at least a year without treatment, according to NAMI.

ISRAEL’S PM ANNOUNCES UPCOMING NATIONAL DIGITAL HEALTH PROJECT: During the World Economic Forum in Davos, Switzerland last week, Israeli Prime Minister Benjamin Netanyahu outlined plans to launch a NIS 1 billion ($295 million) digital health project in collaboration with software giant SAP, The Jerusalem Post reports. The initiative, which will be carried out over five years, aims to stimulate and support research into personalized and preventative medicine, with a focus on the implementation of artificial intelligence (AI) systems to facilitate analysis of Israel's population. It will be submitted to the Israeli government in the coming weeks for approval. Israel is a fast-growing digital health innovation hub in large part because of the government’s efforts to drive and incentivize investments in the emerging field, according to a study published in The Lancet. The vast troves of patient data that result from nationwide digital health systems will be the key to developing population health. The data is necessary for AI platforms to be able to reveal useful insights for things like predicting illness outbreaks.

MEDICAL DEVICE MAKER HOPES TO INCREASE PATIENT ADHERENCE VIA RPM: Biotricity, a medical-grade wearable provider, is developing a range of remote patient monitoring solutions aimed at increasing patient adherence and improving patient outcomes, according to mHealthWatch. The company's flagship product, Bioflux, is a mobile cardiac telemetry device that provides physicians with real-time monitoring and ECG information. Biotricity believes that RPM devices can improve patient adherence rates by demonstrating how certain choices directly impact on their health. This can include sticking to treatment plans and engaging in healthy lifestyle choices. Non-adherence is a massive strain on healthcare systems, leading to increased hospital readmissions and additional clinical visits to physicians.

In other news…

Allscripts was hit with a class-action lawsuit accusing the company of not sufficiently protecting its clients’ health data, according to FierceHealthcare. The lawsuit comes just one week after two Allscripts data centers were attacked by ransomware.
New York governor Andrew Cuomo will devote $664 million to building a new unified health system in Brooklyn, according to an announcement last week. $70 million of the planned funding will go towards creating an enterprise-wide health IT platform, providing a single medical records system across three partnering hospitals.

Join the conversation about this story »

robots

Slack and Workday announced a partnership on Wednesday that will make it easier for the customers of both software companies to get their work done.

Starting in the fall, Workday customers will be able to manage human resource tasks like requesting time off or submitting an employee review without ever having to exit the Slack window. The idea behind the partnership is that employees who use Slack as an office collaboration platform often find it easier to manage all of their work tasks from inside of the Slack window.

Another new feature resulting from the partnership is a new Workday Assistant, which will act as a bot inside of Slack. This puts the HR software in the background, and lets users do all of their business from inside a single window.

With more software companies deciding that Slack integrations are valuable when it comes to making customers happy, it is clear that the way people use their computers at work is evolving.

Cal Henderson, CTO at Slack, and Joe Korngiebel, CTO at Workday, sat down with Business Insider to share their vision for the future of work.

This interview has been edited and condensed for clarity.

Becky Peterson: I know that Slack allows for integrations regardless outside of the partnership relationship. What does having a partnership allow for that Workday couldn't do without a partnership?

Cal Henderson: What we’re saying with the partnership is that we are together developing a really great experience around using the two together. So that’s things like figuring out the time-off requests and approvals — you know, the actions that people regularly do in Workday — and bringing those right into the experience of doing them in Slack. Or putting employee feedback in the same place where you communicate with your employers.

So what we’re doing with the partnership is making the richest possible experience when you’re using the two tools together. I think we can work together to build a really, really great experience for our customers.

Joe Korngiebel: It makes things more friction-free, and get work done easily, whether it’s quickly asking for information from your system of records or your people, and being able to run with that. You can get employee information when you’re in the middle of a conversation or collaborating with employees — so being able to move at that speed in the business today. Employees grew up with digital devices everywhere they go, they’re demanding it from consumer software, they’re demanding it from their business software as well.

Peterson: I’m really intrigued by the end of "context switching," where people prefer to not use multiple different websites or platforms. Have you noticed context switching being a barrier for customers in the past?

Henderson: It’s part of the nature of the changing workplace and the set of tools that people are using today and that the modern company is using today.

Your attention is becoming more fragmented across all of these individual tools, and people are choosing more software from more vendors that satisfy more specific use cases, and achieve very specific tasks in a better way than they have before. So it helps to have some common hub to tie those together, and a place that is your default interface, and for our customers, that’s inside Slack.

It helps to have some common hub to tie those together, and a place that is your default interface, and for our customers, that’s inside Slack.

But what we want to do is bring those interactions from inside other systems and into the place where you’re already working. If we can bring a time-off request, or an approval, or a piece of employee feedback into the same conversation — whether it’s in that same channel in Slack or that thread message within Slack — then it means people don’t need to switch out to another software for doing this task. It keeps you in a single place.

It also means you have a single record of that communication. Increasingly, what I’ve seen over the last decade is the switch from the kind of file-centric model of computing, where the data you had within your company was stored in files like Word documents that you passed around, and it’s been moved into the cloud. Having that tied into the place where you’re working, collaborating with others, where you’re talking with your teammates and your partners, is super important.

Interfaces can create workflow friction, and that's bad for users

Korngiebel: Just to echo that, teams are more distributed than ever now. Being able to connect and collaborate without having 20 tabs open across your browser — one being, you know, a tab for your Microsoft stuff, one tab for your Workday stuff, one being for your personal stuff, one being for your Slack stuff — let’s go into the tool you're using. If you’re using Slack to collaborate between your distributed teams, get that information quickly and easily out of Slack. That empowers the workforce to move at the speed of innovation today.

And for us, it’s not just about switching that context from tab to tab. It’s also about the friction of the interface itself. We’re moving to more of a conversational interface, and moving out of forms, and being able to just ask in human language in Slack, “What’s my time off balance?”

“Do I have any approvals that I need to approve?”, and having that approval push and find me in my natural workspace, collaborating with my coworkers.

So I think it’s about that context and not having to switch contexts, but also about that conversation and simplifying that interface even more, which you can see in our integration here with Slack.

Workday opened its platform to meet its customer demand

Peterson: Does Workday have any partnership with other companies that would facilitate the same sort of single interface?

Korngiebel: We provide a very open platform. Openness is the future of business. When cloud data comes together like you’re seeing with this partnership here, it makes our workforce more dynamic and puts people at the center of what we want work to be as we move forward.

So in a sense, yes, we’re open, but what this strategic partnership does is really highlight what our workers and customers have pushed us to say, “Hey, we’re using Slack." Slack is a very powerful mechanism for our employees to connect in the distributed world we’re in now. In Slack, we can do a much better job of meeting our employees where they want to be.

Peterson: I can definitely understand that from the user perspective. From the company perspective, I’m just wondering...there must have been a time when Workday got a little suspicious of Slack, right? Is there a sense in which, you had tried to make the Workday landing page more accessible to users, or did you think a Slack integration was something that was bound to happen anyway?

Korngiebel: We meet employees where they are with our mobile experience. We meet people where they are with a completely accessible web experience. We move all over the place as far as the needs of our employees goes and where they need to be met. We'd be naive to say we’re the only tool to do that.

An open stance, for us, is essential. It's making sure that when your employees are using a tool, that they can run with that. And Slack is a great conversational experience. Why not meet those employees where they are there? So it’s not about us versus them. It’s about the experience.

To see the future of enterprise tech, look in the consumer space

Peterson: What do you think of voice? Are Alexa-type interactions the future of computer-human interactions?

Korngiebel: We’ll have to be more bullish with where we’re going with the ability to text. I have a teenage son and he can actually look me in the eye and text to all his friends while he’s having a conversation. That’s where the world is going, and we want to be there.

Henderson: With the last few products at Slack over the years, we’ve benefited enormously from the rise of messaging outside of the business. The rise of the messaging in the consumer space, and then the continuing consumerization of IT is, I think, what led Slack to be so successful.

So we can look outside of the workplace for trends like voice, with things like Alexa and Google Home. And it’s interesting to see how that will evolve into usage inside the workplace. That’s something we’re looking at closely. Those trends of how people communicate outside of work are going to be key to the evolution of how people communicate with their teams in the workplace.

Those trends of how people communicate outside of work are going to be key to the evolution of how people communicate with their teams in the workplace.

Peterson: Are there any other behavioral trends that either of you see coming up?

Henderson: I think the that what we see is there’ a shift in the attitude of the way that people work together that pushes for more transparency and more teamwork.

All kinds of business across all kinds of industries are information work, and all information work is teamwork. The more teams that can feel connected to each other, and connected to their sense of purpose, the better they can work together, the better they can collaborate, and the more effective they can be.

I think the transparency in communication is at the heart of that. Pulling the sort of “transparent model” of channels, and working with all of your tools in the same space, whatever those tools are, is kind of key to teams working more effectively together.

Korngiebel: I’d say for us, it's making software more personal and taking that aspect that we see now in our consumer life, where information like sports scores finds me.

We’re doing a lot with machine learning, and guiding the algorithms so that in Slack, you get pushed the next great job candidate that you need to hire. Or pushing the important approvals that need to happen. So when we have this type of partnership, where we collaborate with natural workspaces, we can push out relevant information with the knowledge we have on our employees. We see that as an important trend. Making software that you truly love using every day.

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