(July 2016, 268 pages)
A digital assistant, as the term is used in
this report, uses “natural language” (a human language in speech or text) to interact
with a user of a digital system. As the term suggests, the digital assistant
aims to be like a human personal assistant. General personal assistants, such
as Apple’s Siri, Microsoft’s Cortana, and Amazon’s Alexa try to do almost
everything for you. But companies, as well as content and application
developers, can develop specialized digital assistants to connect with
customers. This report discusses over 170 vendors that can help with that task.
Alternative terms for digital assistants have
proliferated: “intelligent assistants,” “intelligent agents,” “bots,” “personal
assistants,” “avatars,” “virtual agents,” “virtual assistants,” “Intelligent
Virtual Assistants (IVAs),” “robots,” and more. The term “bots” is often used
for specialized applications in messaging services, where the bots are reached
by sending a text message in natural language to an application.
In some cases, interaction with a computer
system may be in natural language, but not identified as a digital assistant. A
customer service call center that answers your call with the equivalent of “How
can I help you?” or “Please tell me why you are calling?” is an important
example. In effect, this functionality is a digital assistant without a name,
and is considered as such in this report.
The maturing of natural language interpretation
and speech recognition technology, as well as the usual continuing drop in the
cost of computer power, has led to many companies providing this alternative to
their customers, from chatbots on web sites to voice assistants on mobile
phones. The trend has accelerated rapidly as the messaging services provided
tools to build bots (Facebook claims 11,000 bots have been developed) and the
general digital assistants such as Alexa and Cortana support connecting with
outside company’s specialized assistants. This trend, in effect, will make a
company having a digital assistant as much as a necessity as a web site, as
people increasingly seek information through these channels rather than through
More generally, the Conversational User
Interface (CUI), supported by natural language processing and speech
recognition when voice interaction is allowed, is a major trend. As the
Graphical User Interface (GUI) becomes over-burdened in general and
harder-to-use on mobile devices with smaller screens than PCs, the CUI becomes
an important overlay that can work alone or supported by the GUI. This
revolution in user interfaces is an inexorable trend forced by the increasing
complexity of the software and services we use.
The Digital Assistant report looks at the
growth of the market created by the use of natural language to interact with
digital systems, breaking it down over five years by global region and by
consumer-facing versus within-enterprise opportunities.
The report also provides a guide to developing
specialized digital assistants that represent your company, service, or
application with an easy-to-use interface. The 172 vendors that can help you do
this are listed by category in this report, with guidance on which may be
relevant to you, depending on the level of involvement you want in developing a
digital assistant. Obviously, while the discussion centers on how companies can
use these resources to develop a digital assistant, it also provides a guide to
the landscape for companies that want to participate in providing such
The sections immediately following this
introduction dig a bit deeper into some of the trends outlined and the
technology behind them:
Overview and definitions
Assistants: Categories, Strengths, and Limitations: Digital assistants at
their core are defined by what they do.
Segments: Markets are defined by the objective of the digital assistant.
General Personal Assistants: In addition to motivating the growth in the
use of the Conversational User Interface, these general assistants are conduits
to specialized digital assistants and bots.
Technology: Where we are and where we’re heading: An overview of core
technologies, what they can do today, and what to expect in the near future.
of natural language applications: Specific examples of deployments, with
some examples of resulting savings and service improvements.
vendors that match your goal: Alternative ways a company or app developer
can create a natural-language digital assistant, ranging from contracting out
the entire process (other than specification) to working with a consultant (who
in turn is managing outside resources) to hands-on assembly and set-up of the
core technology components.
Companies that can be part of your creating a specialized digital assistant are
listed by company and discussed individually. Introductory sections help you
navigate this reference section:
vendors: A quick introduction to vendors that can help you all the way to
table: A list of all companies covered with categorization and web sites.
- Vendor description: Detailed discussions
of 170 companies that can contribute to building a digital assistant.
size and evolution: Estimates of market size by global region from 2016
through 2020, with separate estimated of the consumer-facing category and the
The report is intended as a reference, designed
to help the reader find desired information quickly as needed. This is
particularly true of the vendor section, where there are individual discussions
of over 170 companies. The companies are categorized, so that the reader can
find options for a particular resource; the companies that provide a full
assistant solution are summarized as well in a special section.
A summary table of all the companies includes
their web sites and categories.
the first market study by Bill Meisel and TMA Associates in over a decade. The
subject is one that the writer is deeply familiar with, from having written a
technical book on machine learning early in his career, founding and running a
speech recognition company for a decade, to publishing a paid-subscription
monthly newsletter covering applications of speech recognition and natural
language processing as an industry analyst and consultant for the last two