Galit rpa predictions 2019

Michael Baxter December 11,
2018
RPA predictions for 2019, from UiPath
information-age.com/rpa-predictions-uipath-123477199/
Robotic process automation is growing fast, indeed Gartner has forecast that the RPA
business will grow 57% over the next year. Here are six RPA predictions.
RPA predictions; Attended robots set to increase, but since they are software, they
probably won't be bringing you a cup of tea.
Recently we spoke to UiPath’s chief evangelist Guy Kirkwood, who outlined RPA
predictions and some broader trends; this is based on what he told us.
RPA prediction number one, the rise of attended robots.
Attended robots (that’s robots that work alongside humans, augmenting human
workers) will accelerate past unattended robots. Guy told Information Age that last year,
the ratio of unattended to attended robots was 70:30, “Last week (9 November 2018), I
worked out that it is now 54:46. By the end of this year I project that it’s going to go over
the 50:50 mark and I predict by the end of next year that we are going to end up with
about the 70:30 split, the other way around. So, I think there is going to be massively
more attended robots — which also has positive implications for jobs.” And if you are
unsure of the difference between attended and unattended robots, a fuller explanation
is below.
1/5

RPA market with UiPath in the cockpit is taking off like
a rocket
The RPA market is exploding, RPA or robotic process
automation, has moved up the Gartner hype cycle, and it is no
longer ‘one day’ technology it is technology that is
transforming business now, and UiPath sits in a comfortable
position, it claims to be the fastest enterprise software
company in history, and we spoke to Guy Kirkwood, its chief
evangeliser.
RPA prediction number two: RPA in the public sector will
explode.
Governments have woken up to the value of RPA in two ways
Doing more for less
Significant increase in citizen-centric services.
RPA prediction number three: business-cases for
automation will stop being built on headcount reductions
and start being built on improved employee engagement.
“This is how automation information should be measured,” he adds by way of an
explanation: “Happier employees make for happier customers who spend more.”
RPA Prediction number four: Outsourcing will die.
“Outsourcing (particularly business process outsourcing) been dying for some time, but I
think 2019 will see a catastrophic reduction in new deals and anyone anywhere near a
break clause will use it. The Evidence lies with the fact that organisations are changing
bottom up, not top down. 9% of our revenue has come from India, yet 60% of the people
who have been to our free training courses are based in India.” This means that firms
which have traditionally provided outsourcing services are now looking at how they can
become experts in automation, in the process shifting their approach to an advisory, or
consultancy-led role.
RPA Prediction number five is not so much about RPA at
all. Artificial Intelligence will slowly bleed into the
mainstream.
“AI is where RPA was in terms of adoption two years ago. I know this because I did a
webinar in March where I had about 800 people on the call;, all using RPA. I asked them
the question: “What do you do with AI?” And I gave them a choice between four answers:
2/5

nothing, at pilot stage, in production, or extensively. The answers were almost exactly
the same, to the percentage, that RPA was getting two years ago. So, does that mean it’s
going to take another two years to move into the mainstream? No, it’s going to happen
more quickly than that, in about 12 to 18 months; it will start to move into mainstream
from next year.”
Why is artificial intelligence overshadowing RPA?
Technology firm V1, has warned that companies are in danger
of missing out on major operational efficiencies because they
are blindsided by AI. Although AI is tipped to transform
business, many firms aren’t yet ready to adopt it and should
instead be looking towards RPA which is more accessible
Final RPA prediction: analysts will continue to underestimate
growth.
In 2016, Gartner forecast that the global RPA market size would grow by 41% year over
year to 2020. Forrester predicted 61% growth to 2021. But all of the RPA vendors have
been growing much more quickly: “In the last three years UiPath’s growth has been 480%
CAGR.”
On this theme, it is interesting to note that in November 2018, Gartner projected that
“Global spending on robotic process automation (RPA) software is estimated to reach
$680 million in 2018, an increase of 57 per cent year over year.”
But this all begs one question. What’s the difference between attended and unattended
robots? “Unattended robots typically sit on a server or virtual machines; they do the
tasks that do not require any human interaction, for instance, moving information
through and between systems.”
Guy gave one of the Big Four audit, tax and consultancy firms as an example. “This firm
has automated 45% of its core audit business in India using a combination of Microsoft
Cognitive Tool kit, IBM Watson, and Abbyy which is an intelligent OCR platform;
orchestrated by UiPath. Guy puts it poetically: “Attended robots can do all the crappy
stuff, such as the auditing that people did in their first and second years out of university.
I would describe it as the shitty stuff that no one wants to do but has to do it in order to
get on with their job.
3/5

RPA provider, Blue Prism announce partnership with
ABBYY
As part of the partnership, Blue Prism adds Visual Perception
skill to its Digital Workforce via ABBYY FlexiCapture, giving
enterprises more data extraction and insight capabilities.
“Attended robots is where an action is triggered by the
human; it’s agent augmentation, it helps you to do your job.
The best example of that is let’s say in insurance, by the time you’ve gone through
security, the robot will have rushed off to multiple different systems that an insurance
company has, on for example, pet insurance and household insurance and car insurance
and whatever else you’ve got, to give the agent a full picture of you as an individual,
everything you’ve bought, what your claims history is and all the rest of it. The robot
does that in lightening time which means that you don’t have to transfer between
different departments. This creates a happier experience for the customer and for client
and for the agent, who are able to on-sell and up-sell much more effectively.
Opinion: “Robotic Process Automation delivers greater
productivity in the workplace”
Dean McGlone, Sales Director at V1, explores the benefits of
Robotic Process Automation (RPA) and how it can boost
productivity levels in the workplace.
“The important thing is that the attended robot promulgates
information back into multiple different systems so that
human workers don’t have to because that is what most of their time is spent doing,
getting information from the systems and putting it back in once at the end of the call
and that is what the robots do.” Karl Nolan, chief executive of Generali Link, summed it
up best when he reported that since implementing RPA, “the mood music has changed,
we have happier employees and we now measure our service in terms of compliments
rather than complaints.”
As automation in the work place potentially moves to the point where there is a robot
for every person, this type of culture change could become more prevalent.
4/5

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5/5

Licensed for Distribution
Magic Quadrant for Robotic Process Automation
Software
Published 8 July 2019 - ID G00379618 - 74 min read
By Analysts Derek Miers, Marc Kerremans, Saikat Ray, Cathy Tornbohm
As organizations look for ways to improve operational efficiency and integrate
legacy systems with new enterprise applications and digital business, robotic
process automation continues to grow its footprint. Here, we examine these
market forces and the leading enterprise vendors for such software.
This document was revised on 8 July 2019. The document you are viewing is the
corrected version. For more information, see the Corrections
(http://www.gartner.com/technology/about/policies/current_corrections.jsp) page on
gartner.com.
Robotic process automation (RPA) is a digital enablement technology that
predominantly leverages a combination of user interface (UI) and surface-level features
to create scripts that automate routine, predictable data transcription work.
RPA tools link applications, eliminating keying errors, speeding up processes and
cutting costs. As a market, RPA is still relatively small, with a total revenue of slightly
less than $850 million in 2018. However, RPA is the fastest-growing software
subsegment officially tracked by Gartner, with year-over-year growth of more than 63%
in 2018.
RPA has effectively bypassed the traditional IT buyer, appealing directly to business
users, with its emphasis on resource reduction, easy efficiency and accessibility of the
scripting environments. During the years, businesses have paid for an expensive
patchwork quilt of applications and systems. Given the rapid evolution of the
prevailing business climate, business executives are finding it increasingly difficult to
understand why they need to wait for IT to integrate their existing technology
solutions. The net result is a tremendous pent-up demand to democratize process
Gartner Reprint Page 1 of 45
https://www.gartner.com/doc/reprints?id=1-1C6RAVTI&ct=190709&st=sb&utm_cam… 15-Sep-19

automation and data integration. Business executives are lining up to sponsor new
RPA initiatives directly within their functions.
The buying tornado that has ensued is driving up the valuations of the biggest vendors
and causing new players to rush into the market. This market growth is in stark
contrast to the more traditional, but related, workflow and broader process automation
tools, such as intelligent business process management suites (iBPMSs). The
challenge with these products was always the perceived level of skill required to
successfully integrate third-party applications. Although still a significantly larger
market, iBPMS has struggled to penetrate the broader business consciousness.
The technology trajectory has evolved from screen-scaping technologies many
decades ago; however, RPA emerged as a marketing term around 2010. Unlike
traditional screen scraping, RPA tools typically interact with the metadata that drive
modern applications at the UI level. RPA has continued to evolve and develop as it
helps organizations to:
With that sort of scope, there are a great many opportunities for RPA tools to deliver
significant value to enterprises struggling to leverage a patchwork quilt of existing
Often referred to as
“unattended” RPA, the emphasis here is on straight-through task automation.
Scripts are designed to replicate the actions of a person interacting with those
systems or documents, which, typically, do not have effective APIs. Each iteration
takes a second or two to deal with a discrete element of data, rather than many
data items together in batch mode. At relevant points, the RPA tool substitutes
credentials required by those external systems and data for the item of work. The
same sort of approach can also support large-scale data migration, using carefully
structured scripts to extract from a set of data sources and systems for a new
target system. With some tools, it’s possible to embed these integrations directly
into third-party applications using APIs.
■
Referred to as “attended” automation, RPA tools
can extract information from systems and related documents, shaping it and
preparing it for consumption by the worker at the point of need. For example, when
interacting with customers or external stakeholders, employees often require data
from many systems. The employee typically accesses multiple systems and may
also need to interact with other colleagues, each of whom also has systems to deal
with. This can take a long time and affect the customer experience significantly.
Ultimately, this sort of functionality can enable customers to interact directly with
systems via chatbots.
■

systems. At the core, they help organizations unlock the data and value associated
with their historical technology investments.
Key Misconceptions, Challenges and Developments Surrounding RPA
Of course, there are different sorts of challenges and common misconceptions to
overcome if organizations are to maximize the value they get from RPA. Organizations
must recognize that:
RPA
involves developing integration scripts that get information in and out of other
systems. These are easy to build; however, they are not equivalent to humans, who
can interpret and adapt as needed. Customers should not confuse in their minds
the cost of an employee and the cost of a set of integration scripts. The claimed
head count reduction rarely happens, because employees are normally refocused
toward more value-adding work.
■
The term “long running”
refers to a wider work item or customer case. The term “process” in the RPA
acronym is more accurately discrete “task” automation. Most automations
supported by RPA tools last, at most, a couple of seconds. Furthermore, at best, the
process support aspect of these products is limited to simplistic workﬂow. For
long-running processes, you need an iBPMS. In fact, many of the products combine
with iBPMS environments to support longer-running business processes.
■
Rather than competing with iBPMS products, RPA tools complement these
more broadly targeted process automation tools. Other elements of that tool box
include process mining to quickly identify existing processes, integration platform
as a service (iPaaS) platforms for more-robust, API-based integrations, low-code
application development platforms and content extraction capabilities found in
optical character recognition (OCR).
■
RPA
customers are buying technical debt without realizing it. The organization is
effectively chaining itself to the UIs of the past. Some of the tools have
mechanisms to alleviate this, allowing the automation to handle simple changes in
the target application. Organizations must manually track the systems, screens and
ﬁelds that each automation touches in each third-party application, if they want to
predict the impact of a third-party system change. Most products support this
critical need very poorly.
■

The next challenge revolves around separating the reality from the hype surrounding
artiﬁcial intelligence (AI), machine learning and so-called cognitive capabilities — in
terms of the genesis of the RPA market, and its ongoing development. The key area in
which machine learning has enabled a major step forward in RPA is a type of
computer vision, used to recognize a submit button for example. Secondly, machine
learning has enabled breakthroughs in several, related “add-on” areas that are
tangential to the core of RPA. These include:
Depending on their focus and history, RPA vendors have developed their own machine
learning approaches, often based on open-source libraries, or they have leveraged
capabilities sourced from the megavendors, such as Amazon, Google, IBM and
Microsoft. However, despite the claims of some of the RPA vendors, there are only
limited opportunities to use machine learning in the core of RPA itself. Certainly,
automation tools — such as those from RPA or iBPMS vendors — can provide a
framework within which you can apply machine learning algorithms to your business
process problem, but that is not AI in RPA per se.
Given the rapid growth in the market, we have seen a great deal of investment activity
in the leading vendors. The three vendors in the Leaders quadrant have a combined
market valuation of slightly more than $11 billion at the time of writing. We also
expect to see further acquisitions, with many of the megavendors buying up the small
RPA players. With this level of volatility in the vendor landscape, buyers should be wary
of committing to long-term sales contracts. The actual switching costs of RPA
software is relatively low, compared with major enterprise application systems.
This Magic Quadrant focuses on the providers of RPA products and not service
providers that leverage RPA capabilities licensed from another vendor. Although the
vendors may offer cloud-based services, the vendors included must be deployable on-
premises.
OCR to recognize text, and intelligent character recognition (ICR) to interpret
handwriting.
■
Augmented content analytics that uses machine learning to identify the position of
ﬁelds on documents such as customer invoices.
■
Natural language processing (NLP) and natural language generation (NLG), which
can help support chatbot integration and virtual personal assistants (VPAs).
■
Automated business process/task discovery, which can help organizations identify
processes and task patterns that could be automated by RPA or an iBPMS.
■

Vendor Strengths and Cautions
Another Monday appears in the Visionaries quadrant with a product that has evolved
from its automation consulting engagements. Another Monday’s product is based on
an ecosystem of software agents that deliver the important characteristics of long-
term stability and scalability. Another Monday reports a workforce of 125 employees
and is based in Cologne, Germany. This analysis pertains to AM Ensemble Version
1.2.21, containing AM Conductor, AM Composer, AM Recorder and AM Monitor.

Another Monday’s visionary offering considers RPA an enterprisewide
platform focused on sustainable value and governance of bots. This vision is
reﬂected in Another Monday’s roadmap, which includes the monitoring and control
of third-party bots.
■
Another Monday’s platform introduces a client-centric,
lightweight architecture with a decentralized execution model in which no central
application is required to run, manage and deploy a robot. Combined with
encryption features and a separate messaging layer, these architectural principles
are in stark contrast to the relatively tactical task automation focus of most
competitors in the RPA market.
■
At the heart of the Another Monday’s RPA ecosystem approach is a focus
on completed transactions, which carries over into a simple pricing model. Another
Monday applies a “pay per use” or “no cure, no pay” pricing model, with
micropayments per successful transaction.
■
Although Another Monday recently launched ofﬁces in the
U.S., it is still a small player that sells mainly into the German-speaking region of
Europe (Germany, Austria and Switzerland [DACH]) and neighboring countries. It has
little market recognition outside this region. Companies considering Another
Monday should investigate the availability of implementation partners.
■
Although its product is innovative, Another Monday’s go-to-market
model is constrained by its choice to grow organically. Another Monday recently
took some external investment that should allow it to expand its market presence
and accelerate its planned innovations. However, this should be put into context
against the recent funding rounds of other, larger competitors. Given the explosive
growth of the RPA market and the broader resource base of its larger competitors,
Another Monday may still struggle to effectively scale its business operations.
■
Given the relatively unusual, distributed architecture and
decentralized execution of Another Monday’s product, prospective customers
should be careful when making direct comparisons with other RPA offerings.
Furthermore, customers will need to think carefully about alignment with existing
architectural patterns in use. Another Monday is unlikely to be your RPA choice if
you are searching for a stand-alone, personal RPA tool that largely automates tasks
supported by common productivity tools (e.g., email and spreadsheets).
■

AntWorks appears in the Niche Players quadrant. The company stresses its
background in AI, machine learning and related techniques to create differentiation.
AntWorks is headquartered in Singapore and reports a workforce of 266 employees,
with more than half of that in product development. This analysis pertains to ANTstein
Version “Triangle” 3.1.
AntWorks asserts a proprietary approach to a machine learning
engine, natural language modeling and a data capture engine to support its vision of
RPA. At the core of this is what AntWorks call “fractal science,” which it uses to
support image recognition and pattern recognition, rather than neural networks. Its
assertion is that its recognition techniques need less data to detect patterns,
delivering faster and more accurate results for characteristics such as OCR.
■
The AntWorks platform is built around the concept of
reusable services. Customers can choose any or all of the modules in the ANTstein
integrated enterprise automation platform. AntWorks provides accelerator
templates for verticals such as banking and capital markets, insurance, CPG and
retail, healthcare and life sciences, high-tech and telecom, media and entertainment,
transport and logistics. It also provides similar functional accelerators for HR and
ﬁnance functions.
■
AntWorks is aggressively building a marketing organization
that focuses on its claimed cognitive capabilities in combination with broader
automation needs. The company stresses that enterprisewide orchestration of
process automation requires clean data and is more than the tactical, task-based
RPA offerings that proliferate in the market.
■
AntWorks is a new player and has a developing roadmap designed to plug
some of the gaps in its RPA offering, when compared with other vendors in our
assessment. For example, the product has limited introspection features and a
restricted set of underlying integration capabilities. Customers should validate that
the product meets their full needs.
■
Given the vendor’s narrative around cognitive, AI and machine
learning, one would expect AntWorks to have effectively demonstrated these
claimed capabilities. Its narrative extends quickly to enabling automations
themselves to become “intelligent” beyond “scripts on computers.” However,

Automation Anywhere appears in the Leaders quadrant and is focused exclusively on
the RPA market, with a relatively well-developed partner ecosystem and strong
investor backing. Automation Anywhere is also one of the most visible players in the
RPA domain, setting the tone through extensive marketing and customer engagement
efforts. Automation Anywhere is based in San Jose, California, with more than 1,200
employees as of December 2018, and approximately one-quarter in product
development. This evaluation is based on Automation Anywhere Enterprise (AAE)
version 11.3, IQ Bot 6 and the Bot Store.
demonstrations were limited to simple script building. Moreover, the vendor failed
to show effective support for at least two of our three RPA use cases.
■
: For a relatively small company, AntWorks has an ambitious go-to-
market strategy. Based on a relatively limited number of clients, Antworks has
attempted to cover eight different vertical industries. We would advise customers to
first validate the effectiveness and applicability of the provided accelerators and
templates, checking for the ability to match internal requirements.
■
Automation Anywhere has a strong innovation profile and has
demonstrated innovation through the growth of its partner ecosystem. Automation
Anywhere uses the ecosystem to fill out broader functionality for its customers,
with extended benefits for partners and customers delivered through its Bot Store.
This is complemented by internally funded innovations, such the IQ Bot.
■
At the product level, AAE includes a wide array of integration components
that users can string together to create automation scripts. There are also
preintegrated components that allow Automation Anywhere to provide extensions
to its product with effective functionality accessible from within the product. For
example, customers can link through to IBM’s business process management
(BPM) tooling, or they can leverage their relationship with Celonis for process
mining. A scalable architecture is also provided to enable customers to dynamically
spin up additional resources as required.
■
Client references cite ease of use, customer support and
flexibility. Automation Anywhere has many enterprise clients (approximately 1,600).
Its market achievements are driven by resources dedicated to ensuring that larger
customers have successful implementations.
■

AutomationEdge appears in the Niche Players quadrant. In addition to more-general
use cases, it has a specialized focus on IT process automation, such as components
for extraction, transformation and loading (ETL). It provides a cloud-based RPA-as-a-
service offering, along with an on-premises RPA model. The company is based in
Pune, India, and it has 75 employees as of the time of evaluation. This analysis is
based on AutomationEdge Version 5.
Automation Anywhere’s marketing message emphasizes that its product is
accessible to business people. In common with other platforms that cover such a
broad spectrum, script developers need to work with a vast array of components —
each of which can require specialized conﬁguration. Therefore, to produce
sophisticated automations, developers usually require a wide understanding of the
product. Although Automation Anywhere has recently announced a development
environment that adapts to the persona and competency of the user, it was released
after the cutoff date for this evaluation.
■
Some client references cite restrictive product-licensing
terms, poor product dashboards and inadequate support for troubleshooting, when
errors arise. Moreover, compared with some vendors in this assessment, customers
cite limitations in such areas as source code management and the sophistication of
the screen recorders. Other references also asked for stronger online training
materials.
■
Gartner customers exploring Automation Anywhere as an RPA
option often cite a lack of transparency on pricing information, and a lack of clarity
around product direction and the underlying product functionality. Although AI is a
cornerstone of the marketing message, its use is limited to an on-screen computer
vision and extracting data from unstructured sources, such as emails, documents
and chatbot conversations, via its IQ Bot functionality.
■
AutomationEdge focuses on ﬁnance, IT service management
(ITSM) and data operations. For a small vendor, AutomationEdge has built a strong
partner and customer ecosystem, with out-of-the-box connectors available for
leading mainframe, ERP and CRM platforms, as well as partnering with leading
ITSM providers, such as BMC, ServiceNow and Cherwell.
■
AutomationEdge offers RPA as a service through a
subscription-based model. Its different annual subscription plans, with multiple

Blue Prism appear in our Leaders quadrant and is based in Warrington, U.K., with
slightly fewer than 500 employees at the time of this analysis, approximately half of
which are focused on business development and sales. It was one of the first vendors
to describe RPA as a “market” having realized the broad potential of task automation
at the UI level. From the beginning, it has focused on supporting enterprisewide
deployment, balancing the democratization of automation development with the
governance tooling needed for long-term success. This analysis pertains to Blue
Prism Version 6.4.
price tiers, provide viable choices for price-conscious customers that prefer RPA
software as a service (SaaS), but want to avoid complex usage-based models.
■
AutomationEdge provides a marketplace with more than
400 prebuilt bots developed by customers and partners. These bots are targeted
toward common business functions across verticals such as banking, finance,
insurance, government and IT. In addition to these ready-made bot solutions,
AutomationEdge has leveraged machine learning models to provide intelligent
support desk operations, managing customer retention and case management
scenarios.
■
Although AutomationEdge has customers across a wider set of
industries, its primary focus is on banking, finance, insurance and IT. It is one of the
smaller vendors in our assessment and is challenged on multiple fronts to compete
effectively and scale operations.
■
As is common in relatively small vendors, some reference customers cited
usability issues with core capabilities in areas such as system setup, administration
and the control room.
■
Reference customers also cited AutomationEdge’s lack of partnership with
other AI providers to bring in more capabilities in addition to its own embedded
machine learning features. They pointed to opportunities to improve the range of
options available to address different AI use cases, such as fraud detection,
sentiment analysis and the handling of unstructured data.
■
Blue Prism has focused on supporting the needs of IT in
scaling RPA initiatives. This is reflected in the configuration of “objects” to manage

the interaction and the interfaces to external applications that help customers drive
reuse and more easily support changes in those systems. These objects become
components in individual process automations, with work items moved between
shared queues. All of this is developed using Blue Prism’s graphical, Visio-based
development environment, complemented by tools to better support the IT
organization in managing the overall environment.
■
Blue Prism has developed a strong implementation,
technology and consulting partner ecosystem. Blue Prism invites partners to create
applications that extend and augment the core platform with capabilities such as
decision management, advanced analytics, unstructured data support and process
mining.
■
Blue Prism has a strong verticalization strategy with
industry-focused experts, campaigns, website navigation and partners. This has
resulted in 42 industry solutions, representing at least 10 customers in each of
these industries.
■
Blue Prism focuses on centralized control of unattended
— i.e., uninterruptable — automation, rather than attended automation. To counter
this issue, Blue Prism has built-in integrations with complementary BPM products
from partners such as Appian, Bizagi and TrustPortal. This is a challenge for
organizations that need to include human interactions in their process automation
efforts, because they need to license third-party products. Blue Prism has described
“human-assisted automation” features as a part of its roadmap. Blue Prism also
rejects the notion of a “recorder” to build automations. However, other vendors have
successfully shown how screen recorders can capture initial process outlines.
■
Although Blue Prism has in-house resources for business
development, sales and advisory/assurance, the vendor relies heavily on partners
for sales support and implementation. Reference clients and other Gartner inquiries
cite concerns about the company’s responsiveness to requests for information.
This suggests that Blue Prism has historically struggled with service and support
processes, compared with competitors that have invested heavily in these areas.
■
Several clients in our reference survey mentioned that Blue
Prism needs to improve aspects such as the central monitoring function (the
Control Room), scheduling, reporting and operational efﬁciency in large-scale
deployments. These areas lacked the ease of use and enterprise level functionality
of other components in Blue Prism’s platform.
■

Datamatics appears in the Niche Players quadrant. It is based in Mumbai, India, with
slightly fewer than 250 people dedicated to RPA. The Datamatics TruBot product is an
RPA tool that develops and runs C# scripts. It was initially developed to support
Datamatics customer engagements and is now sold as a stand-alone RPA tool. This
analysis covers Datamatics TruBot Version 3.0.0.
Datamatics’ go-to-market model leverages existing
customer engagements — particularly in the banking, financial services and
insurance arenas — especially where it has also deployed its proprietary TruOCR
tooling and machine learning capabilities. The emphasis is on cross-selling to these
engagements, while Datamatics ramps up its partner engagement activities.
■
Datamatics has integrated its own RPA and OCR
capabilities, which provide a relatively good starting point for conversations with
customers. This contrasts with most other vendors, which require customers to
license separate OCR products. Datamatics licenses its TruOCR tool separately, as
well as bundled with TruBot.
■
The control panel — TruBot Cockpit — module has a relatively modern,
web-based UI. The Windows recorder element — TruBot Designer — incorporates
functionality to create scripts that interact with web, desktop, mainframe and Citrix
systems. The product captures interactions with third-party applications using
these recorders, which are then modified for more generic use and converted into a
C# script. Customers accustomed to manually developing their own automation
scripts will find this easier to use.
■
Datamatics is not widely known in the RPA marketplace and
has limited distribution and sales support for worldwide coverage. Historically, most
customers were acquired through the system integration aspect of its business and
have a local presence in the Asia/Pacific (APAC) region. Datamatics also failed to
effectively demonstrate support for one of the key use cases identified in this
research. Despite the success of its system integrator (SI) and business process
outsourcing (BPO) businesses, the question remains whether Datamatics can focus
on the RPA market and scale its product operations. Given its small starting point
and the resources available to competitors, it will struggle without major
investment.
■

EdgeVerve Systems appears in the Challengers quadrant. As a wholly owned
subsidiary of Infosys, EdgeVerve can access major client relationships with many
primary buyers of RPA in more than 50 countries. Alongside its RPA product,
AssistEdge Robotic Process Automation, the company also delivers Infosys Nia — a
set of components focused on machine learning and AI. Based in Bengaluru, India,
EdgeVerve has approximately 700 employees at the time of this research, with most in
professional services roles. This analysis is based on AssistEdge RPA Version 17, and
the AssistEdge Smart User Environment (SE) Version 17. All components are licensed
and priced separately.
As is common in relatively small vendors, some reference
customers cited usability issues with the dashboard, limited control mechanisms
and breadth of integration functionality, as well as challenges in conﬁgurability and
change management. None of the reference customers indicated that they were
using the current version of the product.
■
The tool is relatively simple, compared with other products in the market.
Variables are all manually created in each integration. The desktop tool packages
up the scripts and related elements in a project, but then relies on the ﬁle system to
control those artifacts during deployment. Where developers feel the need, they can
drop into C# coding, which may make things easier for them, but will break the
model-driven nature of the development environment.
■
EdgeVerve have a modern graphical user interface (GUI) and leading
capabilities around maintaining a repository of widely deployed bots across a major
enterprise. Clients cite ease of use at the product level, and consider it secure,
scalable and resilient — with strong management information and control
dashboards.
■
EdgeVerve has a relatively strong vision for AI and
machine learning. It exhibits a mature and nuanced understanding of the
opportunities in the RPA market; however, it needs to articulate how this narrative is
realized through integration with the related Infosys Nia product.
■
In line with the parent company’s philosophy of targeting the needs
of major corporations, EdgeVerve’s engagement model is designed to leverage the
existing SI and outsourcing relationships of Infosys. That provides a quick
advantage and positions EdgeVerve well to grow its business at the expense of the
incumbent leaders in this market.
■

HelpSystems appears in the Niche Players quadrant. Based in Minneapolis,
Minnesota, HelpSystems provides a variety of IT management products alongside its
RPA offering. It has established a significant client base and has around 750
employees, of which just under 40 focus exclusively on RPA. With significant traction
for RPA in banking, finance and healthcare, HelpSystems sets out to provide an
affordable RPA offering to enterprise and midmarket customers. This review is based
on HelpSystems’ Automate Enterprise Version 11.1.10.
Although the ownership and contacts of Infosys are a boon for
direct customer engagement, they also inhibit the capabilities of EdgeVerve in
striking effective partnership deals. Many of those that might become partners are
also direct competitors to Infosys. Sooner or later, that which enables the initial
scaling of the organization will become a constraint.
■
An overemphasis on internally sourced consulting resources
has negatively affected the vendor ratings from customers. This manifests in
comments such as “The dependency on Infosys resources to program in
AssistEdge is too high” and “The learning curve for developers outside of EdgeVerve
is too high.”
■
Although the AssistEdge product is supposed to be
complemented by the Infosys Nia machine learning capability, none of the
references had used any of the machine learning, NLP or other AI capabilities
claimed. Although the marketing materials contain a compelling narrative, the
boundaries between the products were not clear. EdgeVerve also needs to
demonstrate how these capabilities can successfully work together.
■
HelpSystems received above-average ratings for overall
customer experience in Gartner’s customer reference survey, with most citing ease
of installation and initial configurations. Customers also cited that the product
consistently supports the basic functions of RPA, such as task automation, UI
interaction and administration.
■
HelpSystems’ pricing model is affordable to customers
who can’t justify investment into more expensive enterprise-level RPA solutions.
Licensing is oriented around traditional software-licensing models (rather than
somehow substituting for a notional full-time equivalent human worker). This has

Jacada appears in the Niche Players quadrant. It is based in Israel with 120
employees, of which slightly fewer than 50 are focused on RPA. Jacada’s focus on
attended automation grew out of its 30-year history in customer service operations.
Jacada points to higher customer transaction volumes in front-office operations as
against the general back-office processes targeted by most of the RPA vendors. This
review is based on Jacada Integration and Automation (JIA) Version 3.0, Repository
Builder v.3.0 and Interact v.10.
enabled customers to find better value in its RPA product than those of larger, more
established RPA competitors.
■
Reference customers of HelpSystems cited the product’s “easy to
integrate” feature equipped with a library of predefined actions and connectors.
They also commended its business-user-friendly editor and good dashboard for
performance overview.
■
The version of HelpSystems’ RPA product that we assessed fails to
leverage machine learning and NLP, and it only provides minimal OCR functionality.
Although this is on the roadmap for 2019, many RPA competitors are aggressively
investing in these areas. HelpSystems will need to accelerate its developments in
these areas to remain competitive.
■
Reference customers cited the RPA product’s usability issues around
some common RPA features, such as easy integration with password vaults, the
ability to develop personal task templates and monitoring.
■
HelpSystems needs to ramp up its operations and market
presence within and beyond the U.S. and European geographies. Although its
customer relationships in the system management arena give it a good starting
point for the future, without significant investment, HelpSystems will face
significant challenges in the race to scale its RPA offering to support global
enterprises.
■
Jacada focuses on contact center automation through its
Customer Service RPA offering. Jacada helps customers leverage attended
automation to assist users where there are no APIs to integrate disparate systems
on the desktop or offer self-service customer interactions.
■

Kofax appears in the Niche Players quadrant. It has a big opportunity to grow, based
on its large, established base of client relationships and extensive partner ecosystem
for its Kofax Capture products. Moreover, with its other assets such as the Kofax
TotalAgility (KTA) BPM platform, as well as machine learning and analysis tools, Kofax
is well-positioned to deliver on the promise of end-to-end automation. Kofax is based
in Irvine, California, with approximately 650 employees dedicated to RPA at the time of
this research. Our analysis is primarily based on Kofax RPA (formerly Kofax Kapow)
Version 10.3, although we also considered capabilities from KTA and the document
capture OCR products.
Jacada focuses on selling RPA as a service with a clearly deﬁned, usage-
based pricing model providing customers options to implement RPA without taking
on long-term commitments.
■
Some reference customers cited above-average service with
Jacada’s project team proactively solving customer issues. They referred to strong
project execution support from Jacada resources delivering RPA projects, including
multiple integrations.
■
Unlike most other RPA vendors, Jacada does not depend on the
broader SI partner ecosystem. The company provides professional services to
assist customers with initial setup, development and deployment of automations.
Although some reference customers surveyed by Gartner cited this as a strength,
others identiﬁed a lack of technical expertise and project management skill sets as
contributing to their project delays.
■
Jacada’s support coverage was also cited as a challenge for
many of its reference customers. This will continue unless the vendor expands its
geographic footprint and ramps up its operations.
■
Some of the reference customers cited challenges with the basic features
of Jacada’s RPA platform, such as the development environment, ease of setup,
process orchestration, product usability and dashboards. A new version of the
product was released just after the cut-off date for this Magic Quadrant. Potential
customers should validate whether the overall usability and capabilities of
development environment meet their needs.
■

Kofax RPA has a fundamentally different approach to virtual desktop
integration. RoboServers ingest the UI into a centrally managed container that
emulates the application without needing to run a remote desktop on an agent
desktop. This lowers the cost of the associated infrastructure. Kofax RPA also
leverages a rich legacy in document and image capture, as well as delivering native
OCR capabilities. For many customers, it is less expensive to buy a bundled Kofax
RPA and OCR solution than an alternative RPA product that then requires separate
OCR licensing.
■
Kofax RPA can enable direct consumption of any automation via a
Representational State Transfer/Simple Object Access Protocol (REST/SOAP)
interface. This means customers can embed its automation capabilities in third-
party applications, without having to worry about “scheduling” via a control panel as
is common in other products. Along with a solid graphical process-modeling
environment that reuses existing “snippets,” Kofax RPA has strong support for
structured data types and data objects across multiple automations. Each
automation can have a set of data types (with embedded variables), and/or a
private set of data variables. These features provide customers with a solid
foundation for the easy reuse of automations and compares well with other leading
products.
■
The large number of customers for its image capture products
provides a major market opportunity for the introduction of Kofax RPA. Kofax also
has developed strong internal capabilities around helping customers establish RPA
centers of excellence (COEs) to implement Kofax RPA tooling. This foothold
provides a solid basis for growth and expansion.
■
Kofax had below-average scores in our customer reference
survey. Enhancing product support is a clear opportunity for Kofax, based on the
feedback of its customers. Customers highlighted the need to improve customer
and partner communication, as well as internal communication across Kofax
operations. Kofax also needs to focus attention on its underlying operational
support processes and practices. Some customers commented that they were
unaware of new product releases until months after they had been made available.
■
Kofax has focused on cross-selling existing Kofax customers
to use the Kofax RPA technology; however, to some extent, this has been at the
expense of growing the capabilities of its partner ecosystem. Kofax needs to

Kryon appears in the Niche Players quadrant. It is based in Tel Aviv, Israel, with fewer
than 100 employees at the time of this assessment. Kryon has support for attended
and unattended RPA, with a strong differentiation around automated discovery of task
work patterns in processes. This analysis pertains to Kryon RPA Platform v.5.25.1 and
Kryon Process Discovery.
numerically increase its partner ecosystem and help all partners grow their own
implementation and consulting skills.
■
Customer references cited limited innovation and a disparate portfolio of
loosely integrated products. Virtually all references made it clear that their use of
the product did not cover several of the areas we asked about. Beyond document
capture, the use of machine learning and NLP is limited. Customers should validate
that the vendor can effectively support their business needs.
■
Alongside its core Kryon RPA Platform, the vendor has strong capabilities
around process/task discovery. In that context, it uses machine learning to derive
sophisticated task descriptions based on captured keystrokes, mouse clicks, data
inputs and outputs of business users. This discovery-oriented tooling provides
visibility and insight into how tasks are completed, the result of which is then used
to conﬁgure the automation of those tasks.
■
Kryon has successfully built relationships with a range of large
customers across industry to support employees in their daily work (mostly
attended automation), where exception handling is critical. The company has also
deployed its technology to solve some unusual problems in areas such shipping,
and the logistics industry.
■
Kryon recently took a further round of investment that should
enable it to expand its market presence and accelerate its planned innovations. This
should be put into context against the recent funding rounds of other larger
competitors. Kryon’s strong vision includes creating a bot exchange marketplace,
better employee productivity analysis, predictive and preventive analytics, and in-
product communication to streamline collaboration and coordinate RPA
implementations.
■

NICE is positioned in the Challengers quadrant. NICE is a software technology provider
of workforce engagement management (WEM) solutions for customer service
applications, case management and employee engagement. It is based in Hoboken,
New Jersey, with approximately 350 employees dedicated to RPA (not including Tier 1
and Tier 2 support, which are split across products). Its RPA offering augments its
WEM capabilities, with an emphasis on attended RPA. This analysis is based on the
NICE Advanced Process Automation v.7 suite, which includes NICE Robotic
Automation, NICE Desktop Automation and NICE Desktop Analytics.
Some reference clients located in other time zones cited
poor customer support. Kryon has ameliorated this problem to some extent through
the recent introduction of 24/7 support, which went live in 2019.
■
The language used by Kryon around “process discovery” can
confuse potential customers looking for “process mining.” The intention of Kryon
Process Discovery is to find processes and tasks to automate with RPA. On the
other hand, process mining solves a different problem — the identification of long-
running business processes that are typically automated with an iBPMS (which may
require RPA integration to support discrete tasks or activities). These are subtly
different, but complementary, concepts. Communicating that nuance requires
carefully worded language.
■
Kryon lags the market in some product areas, such the lack of a web-
based modeling tool — Kryon Studio is a Windows-native product. Although runtime
deployment can operate in cloud-based environments, at the time of the research,
there was no public cloud offering. It also has limited introspection capabilities,
other than those based on a surface-level integration of HTML.
■
Several reference customers cited above-average customer
support and good relationship management. NICE also offers a simple, flexible, all-
inclusive pricing model, with the options of perpetual licensing or subscription
models. Most of the customers rated NICE’s pricing model and ease of contract
negotiation highly. Moreover, NICE Advanced Process Automation is offered on-
premises and as SaaS, as well as public and private cloud options. This provides
customers with a good deal of flexibility and choice.
■
NICE’s go-to-market strategy targets large-enterprise
customers — organizations with more than 1,000 employees and more than $1

NTT is positioned in the Niche Players quadrant. NTT’s RPA product was developed by
NTT Group (through the holding company’s labs), NTT Advanced Technology (NTT-AT)
and NTT DATA. NTT-AT and NTT DATA are now responsible for ongoing development
and go to market. NTT Group is based in Tokyo, Japan, with more than 280,000
employees. It does not break out the number of employees focused on RPA. This
analysis involves WinActor v.5.2, a personal-client-based RPA tool; WinActor Manager
billion in revenue. This leverages its strong global footprint with direct support in 25
countries. NICE Advanced Process Automation also includes specialized attended
bots to augment its workforce management functionality across a range of vertical
industries, including finance, banking, telecom and manufacturing.
■
NICE Advanced Process Automation includes an embedded
conversational agent, known as NICE Employee Virtual Attendant (NEVA). NEVA
delivers process/task discovery and predictive analytics. From an AI perspective,
NICE has several built-in capabilities, including real-time speech guidance, NLP-
based text analytics and unsupervised machine learning.
■
Although some references gave good customer experience scores,
others described it as not providing a cohesive customer service experience, with
“disconnected” operational units. For example, many cited a clear disconnect
between frontline customer support and technical services teams.
■
Although NICE has focused on building AI and task/process discovery
features, some reference customers complained that basic product features did not
meet their needs in areas such as easy initial configuration, security and resilience.
Customers cited overall complexity of development as a key factor driving the need
for professional services and resulting in increases in total cost of ownership
(TCO). Almost all the reference customers complained about difficulties in
debugging and error handling.
■
NICE will need to move beyond its core focus on attended
RPA and front-office operations. This multifaceted challenge demands that the
company build an ecosystem of partners and customers that will allow NICE to
compete effectively with larger RPA providers. For long-term success, NICE must to
enhance its online search presence and grow brand recognition, as well as
strengthen its efforts around building an effective user community.
■

v.1.0, an administrative web-based tool; and WinDirector v.1.5, a Windows-based
administrative tool.
NTT differentiates its WinActor product as one of the simplest RPA tools
to use in the market. A simple, drag-and-drop, graphical modeling tool enables users
to record their actions, creating the basis for these automations, which can then be
enhanced through grouping and looping constructs. Although the tool can
incorporate enterprise applications and interaction with websites, it is best-suited to
the automation of stand-alone, PC-based tools.
■
NTT-AT has strong backing from its parent company NTT, allowing
it to develop a pervasive market presence in the Japanese market for this sort of
personal knowledge worker RPA tool. Although limited in scope, this is an extremely
fast-growing market. Furthermore, NTT provides Japanese, Chinese and English
language support for the product itself, manuals and support services.
■
NTT provides its technology for a relatively low-cost
annual license fee. Bulk purchase options are available for enterprises. A
consumption-based pricing model is on the product roadmap.
■
NTT targets an enterprise RPA market with a tool that’s primarily
focused on automating repetitive tasks that use common ofﬁce productivity tools,
such as email and spreadsheets. The emphasis is on support for individuals and
their desktop tasks, rather than the centralized governance and a scalable server
architecture needed for enterprise applications and long-running processes.
Customers looking for an enterprise-grade RPA solution should satisfy themselves
that the NTT product meets their needs.
■
NTT still has considerable gaps in its offering, compared with other
vendors in this research. In comparison to other offerings, there is poor scalability,
limited master data functionality, very basic integration and limited AI. Although the
WinDirector tool uses a database to store information that it then uses to
control/coordinate WinActor resources, deployment is still predominantly ﬁle-
based. NTT recently started to support the cloud, and, during this assessment, it
released a cloud-based administrator tool. However, there is no publicly available
cloud service.
■

Pegasystems appears in the Visionaries quadrant. It offers RPA as a stand-alone
product, as well as a feature of its enterprise iBPMS product. They are delivered on-
premises and in the cloud through its Pegasystems Infinity offering. Instead of seeing
RPA as only a stand-alone product, Pegasystems is in a good position to gain from its
long-term vision of integrating RPA tightly with its BPM suite and related CRM
applications. Pegasystems has slightly more than 4,300 employees, but does not
break out the number dedicated to RPA. This analysis is based on Pega Robotic
Automation v.8.0.1086.
Almost all clients of NTT are based in the APAC region.
Prospective customers outside the APAC region should investigate local product
support and local implementation partners.
■
Pegasystems’ long-term view of RPA as a subset of a broader
BPM strategy resonates well with customers that have a DigitalOps mindset
focused on digital transformation, rather than optimization. Pegasystems offers a
stand-alone RPA option for task automation, as well as a complement to its iBPMS
product — Pega Infinity — for longer-running process choreography and business
rule capabilities. As an established player in the iBPMS market and a growing
presence in CRM, Pegasystems has a relatively large customer base to accelerate
the adoption of its RPA product.
■
The strength of the Pegasystems robotics platform lies in its ability to
augment traditional integration mechanisms to source data for the core object
model of the Pega Infinity iBPMS platform. That data can then leverage its longer-
running process and decision management capabilities, while making use of its
native machine learning and AI capabilities.
■
Pegasystems has global reach, with worldwide offices and a
well-structured ecosystem to spread its brand, technologies and practices. These
ecosystem programs include a broad array of implementation partners with strong
business and vertical industry capabilities.
■
Pegasystems’ product focus for RPA is on attended RPA, rather
than the fully automated focus of unattended RPA products. Although Pegasystems
supports unattended automation through the direct insertion of code into third-

Servicetrace appears in the Niche Players quadrant. It has focused its offering on
delivering a secure end-to-end environment in which unattended and attended
automations can run at scale. Servicetrace is based in Darmstadt, Germany, with
approximately 75 employees at the time of this analysis. This evaluation is based on
the Servicetrace XceleratorOne (X1) RPA platform v.5.0.1.
party applications, long-running process support is better provided by Pegasystems’
core iBPMS product. Therefore, a singular focus on Pegasystems RPA tooling may
not align with your organization’s needs for broader process automation. This may
necessitate a larger investment in the core iBPMS platform.
■
Based on customer reference reviews and Gartner inquiry,
many customers have had challenges in RPA implementations, combined with
inadequate customer support for the RPA functionality. Pegasystems claims a
“unified” BPM and robotics platform, but the customers we surveyed point to issues
such as independent releases, where the latest versions of RPA tooling work poorly
with the latest version of the iBPMS platform. These references also maintain that
support is 100% separate, and obtaining an action plan for enhancements has been
unattainable.
■
Pegasystems’ pricing and contract models are complex.
Although the RPA product is available stand-alone, the offering is usually bundled
with its core Pega Infinity platform at a relatively small markup, based on the cost of
that iBPMS platform. The emerging consumption-based pricing model — of its Pega
Infinity platform — has created confusion among prospects who are often unclear
about the long-term TCO. Customers surveyed also cite costly limitations to the
licensing of the RPA software.
■
The Servicetrace product delivers a secure environment within which to
run automations. The X1 Server dynamically provisions any number of parallel X1
Bots that run as a Windows service. These services execute either on a user’s
desktop or are completely hidden in the background. The entire environment — from
a clustered server all the way to execution of target automations on target
machines — is secured through strong encryption. For customers focused on
operating highly secure, scalable environments, this a key differentiating factor.
■
Servicetrace bundles an embedded BPM engine (based on Camunda),
which enables a flexible approach to the longer-running business processes, rather
than limiting the scope to short-term tasks. This engine also imports standard

Softomotive appears in the Niche Players quadrant. It is based in London, U.K., with
approximately 160 employees at the time of this research. The Softomotive RPA
platform consists of two different tools, ProcessRobot and WinAutomation.
ProcessRobot is the enterprise-level environment that supports distributed
business process model and notation (BPMN) 2.0 XML process deﬁnitions.
Although this sounds innocuous, that BPM environment enables Servicetrace to
effectively manage the overall collaboration and deployment life cycle; it also
facilitates direct process-mining capabilities delivered by another vendor in the
ecosystem.
■
Servicetrace customers were highly supportive of the vendor.
Some of its reference customers also selected this product over larger and more-
well-established RPA competitors.
■
Servicetrace is well-established in the German-speaking
(DACH) region of Europe. Outside of that, the organization works with partners, but
has no other direct ofﬁce presence. Compared with larger and more established
competitors, Servicetrace has limited ability to directly engage with, and offer
support to, customers and partners. To compete long term, scaling to address the
needs of the wider market, Servicetrace will probably need external funding;
otherwise, it will struggle to keep up with larger competitors.
■
As with other similarly sized vendors, there are aspects of
overall customer experience that need improvement. In our reference survey,
customers were asking for some form of forum to share best practices and tips and
tricks. It seems Servicetrace was listening, because it has since created suitable
engagement initiatives. Local technology support was also cited as important to
customers. Outside the DACH region, this is delivered through partners. Therefore,
customers outside this area will need to satisfy themselves of the capabilities of
the local partners.
■
Although there is some discussion of AI and machine learning in its
response, there is no clear narrative about how this technology is employed in the
product, or the value it delivers to customers. Rather than developing their own
AI/machine learning componentry, via the Camunda BPM engine, Servicetrace has
sensibly opted for integration with third-party AI/machine learning platforms from
the major cloud vendors.
■

architecture and central management of RPA implementations. WinAutomation is a
stand-alone, self-contained RPA tool designed for rapid deployment. This evaluation
pertains to ProcessRobot v.2018.1.2 and WinAutomation v.8.0.
Softomotive’s product was designed from the ground up to scale vertically
and horizontally. The development environment uses a modern UI that supports
drag and drop, in-line recording, comprehensive testing and exception handling,
along with effective reuse mechanisms at the data level. The ProcessRobot Control
Desk application also includes native functionality to control deployment, test for
error-free execution and manage concurrency policies.
■
Softomotive has a relatively well-developed market
understanding and market engagement strategy underpinned by a comprehensive
RPA market survey undertaken in the latter stages of 2018. This has helped it
deliver differentiated messaging to key RPA user types/personas and is now further
informing its product strategy and overall direction.
■
With a recent funding round, Softomotive moved its headquarters
from Greece to the U.K., and it has signiﬁcantly grown its international presence.
The organization is now relatively well-positioned for further growth internationally,
with a solid product and capable components. Of course, this should be put into
context against other larger competitors’ recent funding rounds.
■
Historically, Softomotive focused on the small to midsize business
(SMB) sector. The organization now has a “People1st” strategy designed enable the
organization to become the market leader in the underserved midmarket segment,
and to help large enterprises accelerate the deployment of RPA. Although the recent
funding round will make it easier to engage large enterprises, Softomotive’s ability
to resource direct customer interactions at this level may limit its growth.
■
Softomotive recently moved its headquarters, and it is still
establishing some aspects that affect customers. In our customer reference survey,
customers cited the need for improvement in training and the service provider
network, and the creation of a community/forum to share best practices. Others
cited the need for better efﬁciency in implementation support. Although these sorts
of things are in hand, they are not as well-developed as those of some of the larger,
more established competitors.
■

UiPath is positioned in the Leaders quadrant. It has a strong partner ecosystem, active
investor backing, focused brand building and a loyal customer base. The company is
headquartered in New York City, with approximately 1,900 employees distributed
worldwide. This evaluation is based on UiPath v2018.3.1 and UiPath Go!
Softomotive’s UI supports drag and drop, making it appeal to citizen
developers for simple automations. However, as is common for most RPA tools,
sophisticated automations and scale require a rigorous and highly structured
design approach, which demands more expert developers. Customers also cited the
need for better OCR capabilities in the product.
■
UiPath’s well-structured partner ecosystem includes more than
100 technology partners that offer complementary technology and tools. This
enables it to support integrations with major products and applications covering
BPM, process mining and AI. The company has penetrated a wide variety of
industries and has representation in 19 countries. In our customer reference survey,
almost all customers cited UiPath’s product performance, ﬁnancial viability and
strong product roadmap as the top factors inﬂuencing their purchasing decisions.
■
UiPath’s RPA platform provides an intuitive user experience across a range
of RPA personas, including business users, citizen developers and seasoned IT
developers. It has relatively strong security, resilience and integration options.
■
In our customer reference survey, users gave UiPath mostly
above-average scores across almost all dimensions of customer satisfaction.
Customer references cited strong integration features, security and resilience
capabilities. UiPath also looks to drive customer success by encouraging users to
collaborate and solve problems through its UiPath RPA Academy, its Community
Forum and Slack Community channel. Across these engagement mechanisms,
more than 30,000 active users have developed more than 200 reusable
components.
■
Although UiPath has a goal of creating a user-friendly tool for business
and tech-savvy developers, some of Gartner’s reference customers had challenges
with its orchestrator and dashboard experience. Customers cited that the
dashboard features are not purely low-code/no-code. In many cases, even though

WorkFusion appears in the Visionaries quadrant. This reﬂect its roots in machine
learning and AI research. It is based in New York City, with just under 300 employees
at the time of this research. Leveraging its patented Process AutoML technology,
WorkFusion seeks to democratize machine learning for business people by
eliminating the time-consuming and costly data science work associated with
cleansing data, training models and validating automated work. This review relates to
WorkFusion Intelligent Automation 2018 (“Lumen” release), which incorporates RPA
Express and enterprise-focused Smart Process Automation (SPA).
the product collected the data, customers had to develop their own representations
of that information.
■
UiPath lags on its cloud strategy. As of the 2018.3
release, UiPath’s Cloud Enterprise RPA offering had not rolled out, although UiPath
operates a hosted cloud for its community users and enterprises conducting POCs
and pilots. UiPath plans to roll out its RPA cloud version in 2019, and it had existing
customers deployed at the time of this research. It is still unproven, compared with
other vendors with established cloud offerings.
■
Despite UiPath’s narrative around AI/machine learning, NLP
and chatbot integration, customers cite the product’s lack of maturity in the AI
space. In many cases, customers expected an easy-to-consume, plug-and-play
machine learning feature. However, they found they had to build/enhance their
machine learning models more than they expected. Many customers cited lack of
direct API connectors when integrating with major ERP and CRM platforms.
■
WorkFusion employs a sophisticated machine learning capability in
support of RPA objectives. In comparison with the other products we reviewed,
WorkFusion showed superior capabilities and vision with regard to how AI and
machine learning can be used in the context of RPA.
■
An integrated BPM canvas allows developers to coordinate RPAs, with
clear looping and machine learning elements. Analytics are strong with the ability to
drill down into individual cases and identify the causes of errors that are affecting
machine learning and process execution.
■
The vendor offers clear and simple pricing information with
different rates for tooling that incorporates integrated machine learning versus

Vendors Added and Dropped
This is the first year for this Magic Quadrant, so this is not relevant.
The inclusion criteria represent the specific attributes that analysts believe are
necessary for inclusion in this research. Vendors need to satisfy the following
inclusion criteria:
straightforward RPA. Having proved its business model and go-to-market strategy,
the vendor is in a good position to aggressively scale its operations.
■
The challenge for WorkFusion is to now win the race to scale.
Although the vendor has a strong product, its limited sales and marketing
resources, compared with its bigger rivals, will affect its ability to service customers
worldwide. It must invest heavily to compete here and develop meaningful
international operations, including better localized support outside the U.S.
■
By default, automations that require humans in the loop must also use the
WorkFusion portal environment to track and execute tasks. The vendor should put
more emphasis on preintegrated components that bridge to broader BPM
environments, rather than assuming customers will want to use WorkFusion to
support the entire spectrum of their process automation needs.
■
Customers outside North America and Europe, such as those
in Latin America and the APAC region, will need to check the availability of effective
local guidance and support. WorkFusion will need to focus on its partner
development activities to overcome its own resource constraints.
■
Providers must have 2017 audited/reported annual tool licensing revenue of more
than $8 million per year. have more than $5 million during the first half of 2018 in
audited/reported tool licensing revenue. appear in the vendors considered
section by at least 10% of Gartner Peer Insight review in this market.
■
Independent software vendors (ISVs) must have tools positioned to address the
market for RPA tools (using Gartner’s definition of RPA). Such tools must address
all three common use cases, as well as possess all the core capabilities and most
of the critical capabilities (see the Market Definition/Description section of this
research).
■

Honorable Mentions
The following vendors are not included in this research, because they do not meet one
or more of the inclusion criteria. Some of them were, however, included in the
reference survey, are appropriate for certain situations and, sometimes, compete
against the vendors covered in this Magic Quadrant:
Vendors must have active customers buying RPA tools during the past 12 months in
at least two major global regions, which are deﬁned as Europe, the Middle East and
Africa (EMEA); the APAC region; North America; and South America.
■
Vendors must permit Gartner to acquire survey data from 10 customers. These
customers should represent production deployments of the product version shown
in the vendor brieﬁngs and in customer production for at least three months.
Similarly, the product version on which the questionnaire response and the use case
demos are based must have been generally available to all customers for purchase
since 1 December 2018.
■
Cognizant HPA
■
Contextor — recently acquired by SAP (November 2018)
■
EnableSoft — recently acquired by Nintex (March 2019)
■
Epiance
■
Jidoka
■
LEAPWORK
■
Makeitright
■
OpenConnect
■
Option3
■
Qruize
■
Thoughtonomy
■
Verint
■

Vendors in Magic Quadrants are evaluated on two axes: Ability to Execute and
Completeness of Vision. These relate to their performance in 2018 and their vision for
the following years. Vendors are scored according to the Gartner methodology for
Magic Quadrants, and these scores define each vendor’s position. Vendors are invited
to provide the data for the evaluation criteria via questionnaires and briefings;
however, evaluations also include the results of Gartner customer surveys and analyst
information from client inquiries.
We evaluated the capabilities of the vendors’ products separately with an exhaustive
analysis of their functionality. Subcriteria used were based on the Critical Capabilities
of the tools. They include:
In assessing the capabilities of the product, we also asked vendors to describe
separately their support for areas that are often associated with, but are not central to,
our definition of RPA, including:
How users would go about developing automations.
■
The scope and features of the product’s out-of-the-box
integration.
■
How the environment is monitored and controlled.
■
Mechanisms for reuse and management over time.
■
Features provided to handle
changes in the environment.
■
Overall integrity of the environment and how it
handled errors.
■
The features that helped secure the environment, including credentials,
data security and access control.
■
How the tools leveraged AI technologies, covering
how they were implemented, and the value that was delivered to organizations as a
result.
■
Any support for wider business process
automation and/or business rules.
■
How documents are assessed and the technologies that support this need.
■

Ability to Execute
Gartner analysts evaluate technology providers on the quality and efficacy of the
processes, systems, methods or procedures that enable performance that is
competitive, efficient and effective, positively affecting revenue, retention and
reputation. Ultimately, technology providers are judged on their ability and success in
capitalizing on their vision. Table 1 shows the ability to execute criteria.
Source: Gartner (July 2019)
Several factors contribute to the vendors’ positions on the Ability to Execute axis:
Because this market includes several small or midsize vendors with highly variable
functionality and uncertain futures, financial viability was an important factor. In
support of that, a key factor was whether the vendor had sufficient investment
capital to allow it to scale effectively. Organic growth is valued more highly than
growth by other means, including growth by acquisition or by securing additional
funding.
■
We evaluated the vendors’ ability to attract and grow new business, and the way
that their marketing narrative translated into features that mattered to customers.
This includes responsiveness in sales engagement, deal management, pricing and
negotiation, presales support and the overall effectiveness of the sales channel.
■

Completeness of Vision
Gartner analysts evaluate technology providers on their ability to convincingly
articulate logical statements about current and future market direction, innovation,
customer needs and competitive forces, and how well they map to the Gartner
position. Ultimately, technology providers are rated on their understanding of how to
exploit market forces to create opportunities for the provider.
We judged the customer experience by assessing rollout and adoption programs,
reviewing the extent to which the vendors support their largest enterprise
customers and by surveying users identiﬁed as reference customers by the
vendors. Given the large volume of customer inquiries, we also incorporated the
views we derived from these interactions. Vendors earned higher marks for an
excellent track record of successful implementations. We looked for relationships,
products and services/programs, including RPA process consulting services that
support client success with the products.
■
From an operations point of view, we assessed how the organization to meet its
goals and commitments. Factors included the quality of the resources, the
organizational structure, skills, experiences, programs, systems, underlying
infrastructure and other vehicles that enable the organization to operate effectively
and efﬁciently on an ongoing basis.
■

Source: Gartner (July 2019)
We evaluated the vendors’ Completeness of Vision by examining customers’
requirements for RPA usage and purchasing, and by assessing how the products
aligned with these requirements:
Quadrant Descriptions
Leaders in a market combine an insightful understanding of the realities of the market,
a reliable record, the ability to inﬂuence the market’s direction, and the capability to
attract and keep a following. In the RPA market, leadership implies an understanding
of the demands of the enterprise and the opportunities of adding additional
functionality, products and services to the core RPA offerings. Leaders must have
demonstrated market-leading vision and the ability to deliver on that vision.
At this point in the development of the RPA market, only three vendors have sustained
excellence in both execution and vision long enough to demonstrate effective
leadership. With continued growth from vendors in the Challengers and Visionaries
quadrants, we expect additional vendors to advance in this direction during the next
two years.
To evaluate vendors’ marketing and product strategies, we looked at the narrative
that they use to position their products and whether their products adequately
address the chosen positioning. We assessed their understanding of the emerging
use cases of RPA and their tactics for dealing with the constraints of RPA. We also
considered the way in which the vendor engaged with common personas
associated with use of RPA products.
■
From a product-offering perspective, we evaluated the critical capabilities of the
RPA tool alongside the integration and bundling of other adjacent third-party
aspects, such as OCR and machine learning. We evaluated vendors’ product
innovation and ability to address the trends we expect to see in the RPA market
(with their associated weightings and content).
■
We also explored the customers’ geographic and vertical market strategies and
their plans to support the global market. We also examined the ability of the vendor
to support a global installed base.
■

Customers should note that a Leader is not always the best choice. A focused, smaller
vendor can provide excellent support and commitment to suit individual needs. Other
vendors may provide a certain capability — such as enhanced security, and a
commitment to specific features or functions — that is important to your organization.
These market segments include call center or individual desktop use cases today. This
also applied to scenarios when deployed by a service partner in your specific industry
market or geography. This more focused type of vendor would not appear as a Leader
in the overall RPA market, but, within a specific segment, it may well be treated as
such.
Challengers in a market excel in their ability to attract a large user following, but this
ability is limited to a subset or a segment of the market. For that target audience,
Challengers are effectively Leaders, but that specificity presents a barrier to adoption
for those outside that subsegment. For example, in the RPA market, a Challenger may
have a strong proven presence or following in attended RPA, but lack traction,
commitment or sophistication in the broader unattended RPA market. A Challenger
must demonstrate a sustained excellence in execution and must have amassed a
significant following, which is hard to achieve in this new and still-evolving market.
Two vendors are rated as Challengers in the RPA market this year, which indicates the
relatively early stage of the RPA market itself. These players were not as aggressive in
targeting clients as the Leaders were during the past five years, when the RPA market
evolved into the mainstream force it has become.
A Challenger can evolve into a Leader if it adopts aggressive, innovative strategies to
expand to the full breadth of the target market. It needs to demonstrate exceptional
insight in understanding the market direction and retain the capability to deliver on
this vision. It may also evolve into a Visionary by sacrificing growth for new features
and capabilities that are ahead of the market.
Visionaries in a market are innovators that drive the market forward by responding to
emerging, leading-edge customer demands and by offering new opportunities to
excel. Typically, these vendors appeal to leading-edge customers and may even have
minimal mainstream presence or name recognition. Their ability to deliver sustained
and dependable execution in the mainstream enterprise market is not sufficiently
tested. The vision of a vendor is not expressed solely in its technological innovation.
The vendor must also show insightful understanding of market trends, as well as
visionary marketing, sales, along with related product and business management
strategies.

In the RPA market, there are three Visionary vendors, including a classic BPM vendor, a
machine learning vendor with an RPA offering and a former professional services
business. Generally, Visionaries are investing in leading-edge RPA offerings that are
not yet readily adopted by mainstream enterprise customers. They support
capabilities in their other related tools, such as AI and chatbot capabilities, as well as
process management. Visionaries excel in understanding the demands of enterprises
that are looking for fully inclusive automation support.
Visionaries should eventually grow to become Leaders. Alternatively, they may decide
to limit their target markets to focus on their core competencies, core technologies or
existing customers and become Niche Players. They could also develop their
specialties to advance in execution and become Challengers.
Niche Players in a market typically specialize in a vertical or functional area.
Alternatively, they might have a strong product that is limited to a specific area or
subset of the market. The 10 Niche Players in this market either:
Several of these vendors are in transition from other markets. Generally, to progress in
this market, they need to focus fully on RPA.
Because of their relatively smaller size, Niche Players can often represent the best
choice for a specific category of buyer, or for a particular use case. They typically offer
specialized expertise, focused support practices, flexible terms and conditions, lower
costs, and greater dedication to a particular market segment and its customers.
Some Niche Players are poised to improve their Ability to Execute and enterprise
features allowing them to evolve into Challengers. Others will discover innovative
solutions that attract interest beyond their niche segments, emerging as Visionaries.
Some will look to strengthen and broaden their businesses to challenge the Leaders.
In this fast-evolving and consolidating market, opportunities exist for all comers.
Have focused their attention on related tools — such as process discovery or
machine learning — rather than RPA capabilities per se.
■
Lack the execution capabilities needed or have limited geographic reach.
■
Exhibit a vision that is not market-leading, or focus on a subset of use cases.
■
Represent startups making initial forays into the market that have yet to
demonstrate success.
■

RPA tools enable the enterprise to use a full range of developer personas — citizen
developers (most commonly business analysts, as well as business end users);
departmental developers; and enterprise IT professionals — and to develop
integrations that range from tactical to strategic. Three RPA use cases follow.
Use Case No. 1: Integration Using an Application’s UI
Organizations have a plethora of existing systems. Citizen developers and business
analysts can quickly extract related data from System 1 and make it available in
System 2:
Use Case No. 2: Large-Scale Data Migration
An automation extracts data automatically from several systems, using carefully
structured scripts to access existing systems and other data sources for a new target
system. This involves:
Use Case No. 3: Augment Knowledge Workers
Automations extract information from related documents and systems, shaping it and
preparing it for consumption by knowledge workers at the point of need. While
interacting with a customer or external stakeholder, data and information from many
systems might be required. A knowledge worker typically accesses multiple systems
to assemble this material. That worker may also need to interact with many
Data transfer and/or matching between systems. Systems can be legacy systems,
enterprise applications or personal productivity tools (e.g., Excel).
■
Integration where no back-end integration or API is available — i.e., it is only
possible via the application’s UI.
■
May also apply to scenarios in which automation is later embedded in third-party
applications.
■
System migration and (re)conﬁguration involving multiple data sources.
■
New systems development involving third-party applications and long-running
processes.
■
Pruning data from applications to ensure that only the relevant information is used
(e.g., only relevant emails, relevant cases, relevant news from news or other
evolving websites).
■

colleagues, each of whom have systems to deal with, which can take a long time and
affect the customer’s experience significantly. This involves:
Ultimately, this could lead to a situation in which a chatbot is interacting with the
customer directly, only handing off to a human knowledge worker when things
occur outside its ability to handle directly.
As these different usage scenarios become more complicated, they may need more of
the tangential capabilities that are outside of our core definition of the RPA market.
These include NLP, machine learning, longer-running processes and OCR
integrations/features.
The RPA tool market itself consists of a diverse range of vendors, each with different
histories and approaches. This creates confusion in the market — especially in
purchasing departments — because each vendor uses seemingly contradictory
language to describe its version of:
Prechecking and structuring data for easy consumption.
■
Provision of contextual information to support the customer case, which may
include advice on the best next action, or related scenarios.
■
Delivering output to relevant applications depending on the data, or steering actions
on a website/chatbot.
■
The scope of the RPA market.
■
Unattended versus attended deployment.
■
Crafting of “instructions” for the automation script to run.
■
The sorts of integration it supports.
■
Any use of AI and/or machine learning capabilities.
■
Appropriate price points and supporting licensing agreements and related
restrictions.
■
The definition of what a “bot” is — some use the term to represent the script itself,
others for the software elements that run the script.
■

The RPA Magic Quadrant displays a diagonal bias from Niche Players to Leaders,
representing two market factors:
However, we feel that investors are perceiving RPA as a key gateway mechanism for
organizations to easily consume AI from the major cloud vendors. Whether this will
prove to be realistic remains unclear. AI makes more sense within the context of the
wider business process and an iBPMS, rather than the confines of a short-running
integration with a legacy system.
Market Adoption Trends
Market adoption for RPA is highest in:
These bigger players outspend the rest of the market; the smaller
vendors have yet to achieve a strong market presence. Therefore, they have weaker
sales volumes. These smaller vendors have to find a route to market. They have a
difficult balancing act — developing an effective narrative and making sales,
investing in new product and features demanded by their customers, and scaling
their operations across geographies. These vendors become the targets of
acquisitive vendors looking to enter the RPA market.
■
As a result,
the range of the Depth of Vision dimension across vendors is more restricted, when
compared with many other Magic Quadrants. This lack of differentiation has caused
hype surrounding RPA and the use of AI. As we’ve already noted, there are limited
opportunities for AI in RPA as it now stands.
■
An organization’s propensity to use RPA is directly related to the number of
existing applications and the automation tools already in use.
■
The finance sector has led the way in RPA for
operational processes, with wide adoption across the world’s major banks.
Insurance, utilities, retail, manufacturing and government industries have rapidly
followed.
■
This is especially true for finance shared
service centers and BPOs that focus on finance and accounting services.
■
These are closely followed
by Japan, Europe, Asia and Australia.
■

RPA market growth is fueled by the large number of organizations struggling to
automate mundane work. There are several contributing factors:
The net result is a tremendous pent-up demand within businesses to move data
among applications. RPA has now provided the opportunity to democratize
automation and integration. However, without proper governance, this will drive a wave
of shadow IT, probably creating as many problems as it solves.
RPA Market Developments
RPA is still relatively small market with a total revenue of slightly less than $850
million in 2018. However, RPA is the fastest-growing software subsegment ofﬁcially
tracked by Gartner, with year-on-year growth of over 63% in 2018.
The buying frenzy of RPA software is driving sky-high valuations of the biggest
vendors — our Leaders are valued at more than $11 billion between them. UiPath
raised its Series A round in April 2017 at a valuation of $140 million and, most recently,
raised its Series D round at a valuation of around $7 billion. That’s a growth of
approximately 50 times in slightly more than two years. And just before we started the
research for this Magic Quadrant (in November 2018), its Series C round valued the
company at more than $3 billion. It is not alone: Automation Anywhere was valued at
Few of these systems were ever set up to share data. Those in the
business side of the organization have become increasingly frustrated by the slow
pace of IT in automating connections among these systems. They ﬁnd the long wait
times posted by IT departments for the attention of expensive IT resources to
respond to their needs incredible.
■
The plans of the
business are often held up by an inability to link the transactions and experiences of
their customers to the data locked in those legacy applications. That has meant
employing more and more humans to handle the work and has inhibited the ability
to scale the business.
■
This is especially the case
when compared with other, slower options, such as developing effective APIs or
replacing those legacy applications. Business people now believe that they can
develop their own automations without having to rely on IT developers. And given
the marketing narrative around “robots” replacing expensive human resources, they
also believe that ROI is easy to attain from RPA.
■

$2.6 billion in November 2018. Blue Prism, the only publicly quoted RPA company, has
a market cap at the time of writing of slightly more than $1.4 billion.
In November 2018, we saw SAP buy a small French RPA player, Contextor, for an
undisclosed sum. And at the beginning of March 2019, Nintex acquired EnableSoft for
an undisclosed sum. Although we don’t know the details of these acquisitions, they
are likely to represent just a small fraction of the massive valuations applied to the
Leaders.
We expect to see:
They will do this through acquisition (as SAP did), by adapting the
positioning of some of their existing products or by attempting to ring-fence the
market with complementary offerings (as IBM has done).
■
These may include
software-testing vendors rebranding, as well as iBPMS and low-code application
platforms establishing complementary offerings. For example, Pegasystems did
this three years ago with its acquisition of OpenSpan. Other BPM vendors have
mostly partnered with RPA vendors, preintegrating them into their broad process
automation platforms. Oracle, Bizagi and Appian have all developed offerings that
integrate RPA tools into their wider iBPMS coverage.
■
This is effectively
what Infosys have done, creating EdgeVerve as a go-to-market vehicle. Datamatics
has done the same, with its TruBot offering. Other BPOs and SIs are creating
comprehensive offerings that embed the products of one or more RPA technology
tools.
■
The claims of some of these vendors really do need
careful examination before jumping on their bandwagon.
■
The costs of licensed RPA tools is so high that some large organizations have
developed their own RPA approaches. Some of those organizations are now
productizing their capabilities and selling the service to their enterprise customers.
Although this is not a large proportion of the market, it highlights the relatively high
cost of commercial RPA tools.
■
RPA is already offered by several of
the vendors. And, as is the case with any cloud service, when offered with fair

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