CNBC’s official Android app, CNBC: Breaking Business News & Live Market Data, can now be downloaded on the Android TV platform, allowing users to stream their favorite content from the broadcaster directly to the biggest screen in their home rather than being stuck on a phone, tablet, or a computer. Beyond premium content accessible via a login through a paid TV provider, there is quite a bit of content for non-paying users as well. Beyond paid content, free short-form clips are available from a variety of shows via curated playlists without ever needing to sign in, and all of the app’s features appear to have made their way to Android TV.
It goes without saying that the inclusion of the app to the platform is probably not the biggest change to Android TV over the past few months. Having said that, new content is always welcome and the added ability to utilize Google’s A.I.-driven digital assistant is an interesting direction for the app to take and may signal that CNBC will be exploring voice-enabled user interfaces in a more in-depth manner going forward.
Virtual Agents, Chatbots, and Virtual Assistants for Enterprise Markets Utilizing Artificial Intelligence, Natural Language Processing, and Conversational User Interfaces
Virtual digital assistants (VDAs) are automated software applications or platforms that assist humans through understanding natural language in written or spoken form, and leverage some form of artificial intelligence (AI) in doing so. Enterprise VDAs are controlled by an enterprise and deployed for interaction with a specific set of systems, using channels the organization typically controls, such as phone/interactive voice response (IVR), website, mobile applications, or kiosks; and channels they do not control, such as messaging applications like Facebook Messenger, LINE, or Telegram, or smart assistants like Amazon’s Alexa.
Companies seeking efficiencies and automation for customer support and customer service began experimenting more than 10 years ago with automated applications that leveraged natural language processing (NLP). Most of these applications lived within an enterprise website, delivering smart search for frequently asked questions (FAQs), and then later as pop-up VDAs and avatars with more advanced capabilities. In the last 3 years, significant advances in combining NLP with other forms of AI, primarily machine learning and deep learning, have made enterprise VDAs more intelligent and more useful. This advancement and other market factors have begun to expand the use cases for enterprise VDAs beyond customer service & marketing. Other notable use cases for enterprise VDAs include e-commerce and sales, business applications, healthcare, foreign language tutoring, and tax filing and processing.
This Tractica report examines the market and technology issues surrounding enterprise VDAs and then presents 9-year forecasts for VDAs used in these end markets. The report covers how enterprise VDAs will be used across multiple channels in six key use cases: customer service & marketing, e-commerce & sales, business application, healthcare, foreign language tutoring, and tax filing & processing. The study includes profiles for key industry players throughout the ecosystem. It also presents global market forecasts for enterprise VDAs, segmented by region, covering the period from 2016 through 2025.
Key Questions Addressed:
What is the current state of the enterprise virtual digital assistant market and how will it develop over the next decade?
What are the key use cases that will drive greater enterprise virtual digital assistant adoption?
What are the key drivers of market growth, and the key challenges faced by the industry, in each world region?
Who are the key players in the enterprise virtual digital assistant market, what is their competitive positioning, and which ones are poised for greatest success in the years ahead?
What is the size of the enterprise virtual digital assistant market opportunity?
Who Needs This Report?
Customer experience-focused enterprises
Customer experience solution providers
AI hardware and software providers
Internet service providers
Brand marketers and advertisers
Table of Contents
Market Drivers and Barriers
Competitive Landscape and Key Industry Players
Enterprise VDA Software Revenue by Use Case
Enterprise VDA Software Revenue by Region
Enterprise VDA Total Revenue by Segment
Scope and Definitions
Consumer Demand for Self Service
Consumer Expectations for Control, Speedy Resolution, and Personal Context
Increased Customer Satisfaction
Shifting App Use/Fatigue
Emergence of One-to-One Marketing
Better Data Analysis = Better Decision Making
Improved Employee Satisfaction
Understanding Language Context
Automated or Live Agent?
Internal Agreement and Integration
Fear of Failure
Customer Service & Marketing
Narrower, Practical Sub-Use Cases
Vertical Market Momentum for Financial Services
VDAs Using Rules-Based and Machine Learning
Introduction of Deep Learning to Enterprise Virtual Digital Assistants
Momentum for Messenger Platforms as a Channel, Experimentation with Voice Assistants as a Channel
E-Commerce & Sales
Banking and Financial Services
Selling Financial Services
Productivity and Collaboration
Workflow and Project Management
Automated Job Recruiting
Tax Filing and Processing
Foreign Language Tutoring
Natural Language Processing
Legacy Natural Language Processing Gives Way to Hybrid Natural Language Processing
Natural Language Processing Market Drivers
User Interface Technology for New Computing Platforms
The Failure of Big Data
Natural Language Processing Market Barriers
Need for Accurate Data
The Importance of Machine and Deep Learning to Natural Language Processing
Understanding Natural Language: Word Maps and Language Models
Natural Language Generation
Legacy Approaches to Natural Language Processing
Deep Learning in Context
What Is Deep Learning?
Key Industry Players
Enterprise VDA Software Revenue
Enterprise VDA Software Revenue by Use Case
Enterprise VDA Software Revenue by Region
Enterprise VDA Total Revenue by Segment
Enterprise VDA User Forecasts
Unique Active Enterprise VDA Users by Region
Enterprise VDA Users by Use Case
Enterprise VDA Software Revenue by Industry
Enterprise VDA Software Revenue, Business Services Industry
Enterprise VDA Software Revenue, Education Industry
Enterprise VDA Software Revenue, Finance Industry
Enterprise VDA Software Revenue, Healthcare Industry
Amazon’s Alexa voice-recognition artificial intelligence will help a major Wall Street bank serve its customers.
J.P. Morgan clients are now able to ask Alexa for the bank’s research reports, Bloomberg News reported Monday. The firm is also working on financial assets price data requests through Amazon’s device, according to David Hudson, the bank’s global head of markets execution.
Voice assistants are “clearly becoming something people are habituated to in their lives,” Hudson told Bloomberg News. “It’s about taking information that’s somewhere in the bank, that someone has to generally go and look for, or which is time-consuming or requires authentication to get, and putting that to you in another channel.”
If J.P. Morgan’s Alexa use rises, it should allow the bank’s employees to focus on more complex service requests from its clients.
The Alexa deal is another in the line of joint ventures between the bank and the e-commerce internet giant. Amazon and J.P. Morgan Chase announced in January a partnership to cut health costs and improve services for employees.
J.P. Morgan is one of the first banks to offer Alexa to its institutional clients, according to Bloomberg News.
Amazon and J.P. Morgan Chase did not immediately respond to requests for comment.
Today it is great to see the full launch of Natural Language Generation (NLG) technology in our UK and Ireland Transaction Support business. We’ve been on a journey to get to this stage and have further to go but this is giving our staff time back from the more tedious elements of what we have previously asked them to do so they can focus more time on high value add work. So happier staff and (even) more value add for our clients when they work with us. Next stop for NLG is our Restructuring, Operational Transactions Services and Corporate Finance businesses. #TASx
Microsoft has so far released its artificial intelligence technologies largely through its well-known software platforms, such as the Cortana voice assistant on Windows 10, automated language translation in Microsoft Office, and AI-powered speech, vision, search and language technologies for developers on Microsoft Azure.
Next up for an AI infusion: Microsoft’s first-party hardware.
Artificial intelligence specialists at the company are now working closely with its devices group, said Harry Shum, the executive vice president of Microsoft’s AI and Research group, in a broader interview with GeekWire about the next phase of the company’s AI initiatives. Without giving details, Shum said he expects some “very, very exciting devices” to result from the work by the company’s AI engineers and devices group.
Shum mentioned this as an aside, not to get the gadget blogs buzzing but to underscore the scope of what Microsoft is trying to do. As part of the massive engineering reorganization announced by CEO Satya Nadella last week, the company is attempting to bring artificial intelligence into everything it does.
“It’s all infused by AI,” Shum said.
It’s a risky move, focusing the company on emerging technologies that could take years to have a major impact on its bottom line. At the same time, the changes in the engineering divisions reduce the role of Windows, the flagship operating system that has padded its profit margins for decades. Windows chief Terry Myerson is leaving Microsoft as part of the reorganization.
Microsoft has the financial resources to play the long game in artificial intelligence, and its focus on the ethics of AI gives it a selling point at a time of growing concern about the use of personal data by tech companies. The company’s strength in enterprise technology also helps, providing an inroad to large companies separate from the consumer market. And even as the company expands its horizons, Windows 10 still has more than 600 million users, providing massive reach.
However, Microsoft is competing for AI talent and attention against other tech giants and startups making their own major investments in artificial intelligence. Unlike Amazon, Apple and Google, Microsoft doesn’t have the advantage of its own smartphone platform or a large base of smart speaker users to help fuel its AI initiatives.
Ultimately, the AI initiative is the biggest test yet of Microsoft’s cultural changes under Nadella. For many years, the rap on Microsoft’s research unit was that its best work too often ended up in papers and presentations, not in actual products. One major goal of the new engineering structure, Shum said, is to get AI out of the labs and into the world at a faster pace.
“It’s not only about winning awards, or about winning ‘best of’ papers,” Shum said. “It’s also about the connection to many millions of customers.”
Microsoft’s Bot Framework, allowing developer to create chatbots and interactive assistants, is now used by more than 270,000 developers. “We see so many bots popping up every day, it’s pretty amazing,” Shum said. “With many of those bots, of course, the quality still needs a lot of improvement. But I think that’s where we can add more value.”
Microsoft’s AI technologies for business applications, in customer support, sales and marketing, are moving to the new Cloud + AI Platform engineering division, led by Scott Guthrie, with the goal of developing products for its Dynamics business applications. Microsoft is going head-to-head with rival Salesforce, which has been aggressively moving into AI through its own Einstein initiatives.
Shum also cited the growing accuracy of the Microsoft Translator language translation technology as an example of the company moving its research advances and breakthroughs into products.
Under the new structure announced by Nadella last week, Microsoft’s AI and Research Group is now one of three large engineering divisions inside the company, alongside the Cloud + AI Platform division and the Experiences & Devices division, led by longtime exec Rajesh Jha, which includes Microsoft Office and Windows.
Several groups are moving out of the Microsoft AI and Research Group and into Cloud + AI as part of the reorganization: Cognitive Services, Business AI, AI for Customer Support, and Ambient Intelligence.
Microsoft declined to say how many employees are shifting between the divisions as part of these changes. The teams that develop Cortana and the Bing search engine are still part of AI and Research, along with Microsoft Research and several other groups in areas including quantum technology, economics and MSR NExT.
In addition, Nadella wrote in his memo that Shum and his team will work closely with a new group inside the Cloud + AI division, called AI Perception & Mixed Reality, led by Alex Kipman, the creator of Microsoft Kinect and HoloLens. AI and Research will also still play a role in the cognitive services effort that moved to the cloud group.
Microsoft is taking a stand on AI ethics as part of its effort to differentiate itself from other tech companies in the field. Shum and Brad Smith, Microsoft’s president and chief legal officer, lead an internal Microsoft group called AI and Ethics in Engineering and Research (AETHER).
Asked if recent revelations about Facebook have made things more difficult for Microsoft and other companies that rely on large data sets to fuel their AI and machine learning algorithms, Shum declined to comment on that controversy but pointed to the internal ethics group as an indication of Microsoft’s approach. Over time, he said, he hopes to see the group develop “AI shipping criteria” that the company can use to assess products before they’re released, much as it does accessibility, privacy and security already.
Can Microsoft win in AI? Ultimately, it comes down to a “mindset change across the whole company,” Shum said. “Satya and I keep telling people th
Amazon launched a new feature for the smart assistant today that allows you to donate anywhere between $5 and $5,000 using your voice. To donate, you just have to say, “Alexa, donate [X amount of dollars] to the American Heart Association.” You don’t have to enable any special skills to make it happen.
The skill currently supports 50 different charities ranging from well-known groups like the American Cancer Society and St. Jude’s to lesser-known charities such as the West Seattle Baseball League and Moments with the Book, CNET reports.
Alphabet’s (GOOGL) Google is using its voice-enabled digital assistant to help simplify money transfers between individuals. People using Android and iOS devices can ask Google Assistant to request money from a friend or send money to a friend, by saying something such as “Hey Google, request $10 from Peter” or “Hey Google, send Jane $20 for lunch.”
Although Siri was the first voice assistant to enter the market, it now faces stiff competition from Amazon and Google. Therefore it comes as no surprise that Apple is allegedly on the hunt for 161 new employees to join the Siri team and make it smarter and more sophisticated than its rivals.
According to data site Thinkum, the latest hiring stats from Apple suggests that the number of new positions containing the word Siri has ramped up over the past few weeks. The site reports that there are now 161 Siri-focused roles, which are mostly based at Apple’s new headquarters in the Santa Clara Valley, California, U.S.
LexisNexis Legal & Professional® today announced it will showcase new capabilities and updates to its legal information solutions and technology at the 2017 annual meeting of the American Association of Law Libraries (AALL), held in Austin, Texas July 15-18. Located at AALL Booth #502, the exhibit provides law librarians a comprehensive overview of the extensive, innovative portfolio of next-generation offerings from LexisNexis, highlighting recent enhancements and acquisitions designed to meet the needs of and empower today’s data-driven law practice.
“We work closely with law librarians and other legal professionals to offer next-generation legal information solutions that help our customers work more efficiently and better decision insights,” said Jeff Pfeifer, vice president of product management at LexisNexis. “We’re excited to feature a number of these tools at AALL 2017, including the newest capabilities available to LexisNexis customers.”
Law Librarians can see demonstrations and experience significant new Legal Analytics, artificial intelligence and Digital Library capabilities, as well as learn about updates and get previews for solutions such as Lexis Advance, Lexis for Microsoft Office and others.
Featured at the Lexis Advance stations will be Lexis® Answers, a new artificial intelligence (A.I.) enhancement launched last month to the legal research offering. Using powerful machine learning and advanced natural language processing technologies, Lexis Answers takes a user’s natural language question and delivers the clearest, most concise and authoritative answer within a finely tuned, comprehensive set of research results.
Also in the spotlight is Ravel Law, acquired in June, which provides a research, analytics and visualization platform empowering users to contextualize and interpret vast amounts of information to uncover valuable insights for use in court. Additionally, information about a new agreement between LexisNexis® Digital Library and ALM® to make more than 250 treatise titles from ALM available on the Digital Library platform and the LexisNexis eCommerce store will be available.
“Keeping law librarians up to date on the latest and upcoming features for the solutions we offer is a top priority for LexisNexis,” said Paul Speca, vice president of large law and law schools at LexisNexis. “AALL presents a great opportunity for us to do not only this, but to also address another priority we hold dear to us: deepening our conversations and our relationships with customers.”
Located around the AALL show floor are additional LexisNexis businesses. This includes Lex Machina™, a leading Legal Analytics® company (booth #513); Intelligize™ (booth #321), provider of the industry standard for U.S. Securities and Exchange Commission (SEC) intelligence; respected daily legal news outlet Law360 (booth #316); and Reed Tech® (booth #515), provider of solutions and services to government agencies, the intellectual property market and the life sciences industry. Staff and leaders from these businesses will be on hand to engage with law librarians and answer questions.
Attendees are invited to learn more about featured products and services from LexisNexis by attending any of the seven live theater presentations—which showcase recently launched capabilities and providing a look ahead at what’s coming to key legal research solutions. Topics to be covered in these 30 minute sessions are:
Lexis Advance®: What’s New and What’s Coming
LexisNexis eBooks & Digital Library—Must See New Enhancements
Research, Draft, and Review with Lexis® for Microsoft Office®
Lexis Practice Advisor®: What’s New and What’s Coming
Researching by Practice Area and Jurisdiction Made Easy with Lexis Advance® Practice Centers
LexisNexis Newsdesk®: What’s New and What’s Coming
Improving Patent Prosecution with Big Data from Reed Tech, a LexisNexis Company
Theater presentations are delivered in two locations on the AALL exhibit floor. Attendees should consult the presentation schedule and exhibit floor maps available from AALL for details.
About LexisNexis® Legal & Professional
LexisNexis Legal & Professional is a leading global provider of content and technology solutions that enable professionals in legal, corporate, tax, government, academic and non-profit organizations to make informed decisions and achieve better business outcomes. As a digital pioneer, the company was the first to bring legal and business information online with its Lexis® and Nexis® services. Today, LexisNexis Legal & Professional harnesses leading-edge technology and world-class content to help professionals work in faster, easier and more effective ways. Through close collaboration with its customers, the company ensures organizations can leverage its solutions to reduce risk, improve productivity, increase profitability and grow their business. LexisNexis Legal & Professional, which serves customers in more than 175 countries with 10,000 employees worldwide, is part of RELX Group, a global provider of information and analytics for professional and business customers across industries.
Automation, machine learning and artificial intelligence are changing how firms use software analytics, says Oliver Schabenberger, CTO of SAS Institute
Automation, machine learning (ML) and artificial intelligence (AI) are changing the way companies think about, and use, software analytics, insists Oliver Schabenberger, executive vice-president and chief technology officer of SAS Institute Inc., a global analytics solutions provider.
“It’s fascinating to think what happens when you apply these technologies to compete not only in new spaces but also in existing ones—how do we augment what we have already been doing,” Schabenberger observed during a recent interview in Mumbai.
Pointing out that ML is not a new space for companies, he acknowledged that it is AI, depending on “how you define it”, that is “somewhat of an emerging area for us”.
Schabenberger cited the example of cognitive computing, where SAS has had solutions such as sentiment analysis, content categorization and entity extraction from text for decades. “But now,” he said, “new technologies are being brought to bear in the same spaces—around deep learning, for example. That changed the accuracy with which we could solve some of these tasks.”
Schabenberger likened data to fuel and analytics to the engine of the new economy. “We see a big change in the way analytics is being used now,” he said, pointing out to several nuances in how the term ‘analytics’ or ‘advanced analytics’ are being used.
Predictive to prescriptive analytics
Defining analytics as a “multi-disciplinary approach to deriving insights from data,” he said there are different degrees of analytics, starting with descriptive analytics in which you look at historical data to find out what is going on in an organization, what has happened, and what can be learned from that data. The next step, he noted, is predictive: what will happen? Can I forecast the future? “When we get into the predictive space, analytic techniques become more advanced,” he said.
In Schabenberger’s opinion, many of the predictive tools would fall under what we today call AI. “However, AI and machine learning have become such buzzwords that many different things get lumped under them. At SAS we try to delineate these areas clearly and have a good understanding of what we mean by deep learning or AI. My calculator is better at arithmetic than I will ever be, but it’s not AI,” he said. Prescriptive analytics goes a step ahead—it is often used as a more advanced form of predictive analytics, according to Schabenberger. “It tells us how we should run our business—not just predict what will happen but tell us what we should do,” he said.
The underlying motivation for the adoption of ML and AI right now, insists Schabenberger, is automation. “It’s like we have so many problems to solve based on data—and data is reaching such velocity and volume that we need to find ways to automatically, and more dynamically, derive insights,” he said.
In his view, there are different levels of automation. One is “ingest the data, learn from the data and find the right analytic technique” to solve the problem at hand. “That, to me, is classical machine learning. Then there is automation where computers actually write the algorithms that a computer scientist or software developer would have otherwise developed. That’s when we move into deep learning and what I call pragmatic AI,” he explained.
The key to solving the challenges in analytics usage, he said, is to first understand the “pain point in your business”—for example, what do customers think about a particular promotion? What is the cost behind customer churn? Where is revenue going to grow? “These are concrete questions that need to be answered—and then you map those questions to the right analytic technique,” he said.
Adoption in India
“The early adopter of analytics in India is the banking, financial services and insurance (BFSI) sector and they have the most structured data as they had implemented core banking solutions more than a decade ago,” said Noshin Kagalwalla, managing director of SAS Institute (India) Pvt. Ltd. He added that companies in this sector had the data “in the right format” to leverage analytics. Over time, however, analytics usage in other verticals has also grown. “Telecom is another vertical we are seeing tremendous uptake, as they have huge data volumes by virtue of hundreds of millions of subscribers. What is heartening to find in the recent past is that the government and the public sector units are also utilizing analytics in a big way,” he said.
For instance, the Central Board of Direct Taxes had a project called Project Insight, which looked at how the government could increase the tax payer base so as to drive more people to file taxes. Analytics is also helping the government to identify the profile of people who could be potential tax evaders. “So we are seeing huge uptake in usage of analytics both at central and state government levels,” said Kagalwalla.
Manufacturing is “another big area”, in addition to the potential for analysing all the data from multiple devices of the Internet of Things (IoT) that is set to get a big boost from the government’s smart cities initiatives in the next few years. “We are in advanced discussions on several initiatives as we speak and hope that by the fourth quarter of 2017, we should see some clearly defined projects,” said Kagalwalla.
Worldwide revenues for big data and business analytics are forecast to reach $150.8 billion in 2017, an increase of 12.4% over 2016, according to a 14 March note by research firm International Data Corporation (IDC).
The industries that will be making the largest investments (totalling $72.4 billion) in big data and business analytics solutions in 2017 are banking, discrete manufacturing, process manufacturing, federal and central governments, and professional services. They will also be the largest spenders in 2020 when their total investment will be $101.5 billion, the report said.
Besides, SAS, the top companies in the analytics segment include SAP SE, Oracle Corp., Microsoft Corp., International Business Machines Corp. (IBM), Qlik, Tableau Software Inc., Teradata Corp. and Informatica.
However, while the opportunity is huge, the challenges for companies are equally imposing. These include attracting the right talent (like data scientists, statisticians, etc.), storing the data appropriately in data lakes so that quick retrieval is easy, dealing with security, privacy and compliance issues, and using the right tools to make business sense of the humongous amounts of structured and unstructured data.
Schabenberger concludes that it is indeed a challenge for companies to have “the talent and the human brainpower and the number of eyes” to really look at all this data to make sense of it and build “static models as we have done in the past”.