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REPORT: OFFERING OVERVIEW
Infosys Nia Changes the Game for Enterprise BPO/ITOInfosys Nia Makes Enterprises More Efficient,
Powered by Machine Learning/Artificial Intelligence
Holger Mueller Vice President and Principal AnalystContent Editors: R “Ray” Wang Copy Editor: Maria ShaoLayout Editor: Aubrey Coggins
Produced exclusively for Constellation Research clients
June 6, 2017
© 2017 Constellation Research, Inc. All rights reserved. 2
TABLE OF CONTENTS
EXECUTIVE SUMMARY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
REQUIREMENTS FOR AI SUCCESS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
THE INFOSYS NIA LINE AGE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
KE Y DIFFERENTIATORS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
ASSESSING INFOSYS NIA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
RECOMMENDATIONS: FOCUS ON BUSINESS OUTCOMES . . . . . . . . . . . . . . . . . . 19
ANALYST BIO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
ABOUT CONSTELL ATION RESE ARCH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
© 2016 Constellation Research, Inc. All rights reserved. 3
E X ECU TIV E SU MM ARY
This offering overview introduces the key capabilities
of Infosys Nia, a new Machine Learning- and Artificial
Intelligence-powered platform, which affects the way
enterprises operate.
This report describes the platform’s key capabilities and
evaluates Infosys Nia using Constellation’s four criteria
for Machine Learning (ML) and Artificial Intelligence
(AI) platforms: data management of a large corpus of
data, computing capacity, data science, and time. The
report includes an overview of how Infosys Nia stacks
up against the competition and closes with selection and
implementation criteria that CxOs should keep in mind
when implementing next-generation applications using ML
and AI.
REQUIREMENTS FOR AI SU CCE S S
Constellation views four core capabilities and assets as
being essential to developing powerful AI skills (see
Figure 1):
1. A large corpus of data is the first requirement. It’s not
the case that he who has the most data wins; the goal
is to build the largest graph that maps the connections
Infosys Ltd.
· Headquarters: Bangalore, India
· Founded: 1981
· Type: Public
· Revenue (FY 2016): $10.2 billion
· No. Employees (FY 2016):
200,364
· Website: www.infosys.com
· Twitter: @infosys
Business Themes
New C-Suite
Data to Decisions
Future of Work
Digital Safety and Privacy
Technology Optimization
Next-Gen Customer
Experience
© 2017 Constellation Research, Inc. All rights reserved. 4
to data. More data should improve the
precision of insights and allow for more
patterns to emerge. Data is used to test
and train algorithms and models, but the
data should be connected in some way so
that patterns and behaviors show up. The
patterns then should provide accurate
recommendations and suggested or
automated actions. The data exhaust of
these systems is also brought back into
the data store to support self-learning and
continuous learning (see Figure 2).
2. Massive computing capacity is the second
requirement and it’s closely tied to the
ability to ingest, store and quickly analyze
data at scale. Public clouds have changed the
scale and economics of computing, making
it possible to tap vast computing capacity on
demand. Winners will own or have access to
vast computing power.
3. Data science, the third requirement, refers
to intellectual property (IP), skills and
experience. The discovery of patterns,
creation of new algorithms and the ability to
apply human intuition to computing require
great math talent. The skills range from the
basics of data management, data cleansing,
integration and transformation to the
ability to mine data and apply advanced
statistical methods as well as machine and
deep learning to any amount of data. IP
includes algorithms, models and related
proprietary capabilities.
4. Time is the fourth requirement and it boils
down to the people-years that can be poured
into research and development. There is
no substitute for time. Early adopters gain
an advantage of time. Algorithms need
time to improve. Companies can try to buy
time by hiring more people or acquiring
Figure 1. Four Requirements for Developing Artificial Intelligence Capabilities
Source: Constellation Research
© 2017 Constellation Research, Inc. All rights reserved. 5
firms that have already sunk years into
research and development. But successful
delivery of capabilities depends on time
spent generating and learning from data,
understanding computing requirements
and iteratively advancing the math and
data science behind AI-based systems
and applications.
Other emerging and differentiating
requirements of AI include:
• Industry-specific expertise to improve the
relevance of specialized AI systems.
• Natural user interfaces to take advantage of
human voice, visual and gestural interaction.
• Robust recommendation engines that take
the output of AI and present choices that
accelerate decision making.
Figure 2. Continuous Learning Unlocks a Spectrum of Seven Outcomes for AI
Source: Constellation Research
© 2017 Constellation Research, Inc. All rights reserved. 6
THE INFOS YS NIA LINE AG E
On April 26, 2017, Infosys launched Nia, the
second generation of Infosys ML/AI platforms.
Nia means “purpose” in Swahili, which Infosys
saw as a good name for its purposeful AI
offering for the enterprise. The product is the
update to the Infosys Mana offering.
The Infosys Nia offering has six components:
1. Infosys Mana. Infosys Mana was the
first generation ML/AI platform introduced
in 2016.
2. Infosys AssistEdge. This is the Infosys
Robotic Process Automation (RPA)
product that automates formerly human-
operated processes and other processes
through software.
3. Skytree Algorithms. In the spring of 2017,
Infosys acquired technology and talent from
Skytree, enabling data scientists or non-data
scientists to create machine learning models.
4. Infosys Infrastructure Management
System. This is Infosys’ infrastructure
management system, which manages
physical servers, storage and
networking landscapes.
5. Optical Character Recognition (OCR)
capabilities. Infosys brings internally
developed OCR assets built on top of
requirements from customer engagements.
6. Natural Language Processing (NLP)
capabilities. NLP capabilities come from
organic intellectual property (IP) assets.
While Infosys first generation of ML/AI, Mana,
was mainly focused on IT, simplification,
efficiency and cost, Infosys Nia is expected
to allow Infosys to address new ML/AI use
cases in the areas of forecasting (revenue and
product demand), understanding customer
behavior, deeper understanding of contracts
and legal documents as well as compliance
and fraud. As of May 2017, more than 60
customers have gone live on these capabilities
and there are more than 160 ongoing
© 2017 Constellation Research, Inc. All rights reserved. 7
engagements with customers on these
specific capabilities.
Constellation Point of View (POV). Infosys
has shown continuous innovation in Machine
Learning and Artificial Intelligence over
the past 12 months. The new portfolio of
products and services should reduce the
cost of implementation, accelerate go-
lives and improve synergies of the offering.
Constellation sees the move as positive.
Constellation will evaluate early customer
references on how well the products and
services are working together in the suite.
The fact that each component has a positive
track record when working standalone is
encouraging. But CxOs making decisions about
ML/AI platforms need to assess each product
within a suite also as a standalone offering,
given the novelty of products in the ML/AI
area. For example, picking an inferior NLP
capability can substantially hamper the overall
success of an ML/AI platform suite.
In May 2017, it was too early to assess the
power of the overall Nia suite, given its novelty.
Based on conversations with clients at Infosys
Confluence, many of the implementations
are still in early stages and need more time
to mature. This is common to all ML/AI
deployments that are data- and knowledge
base-centric, as enterprises discover
challenges in their data quality as well as
algorithm selection. These are challenges that
are addressed over time.
KE Y DIFFERENTIATORS
Infosys Nia is a platform designed for
enterprises seeking to deploy Artificial
Intelligence for IT efficiencies, predominantly
in system management and system monitoring
(see Figure 3).
The Infosys Nia platform has several
capabilities that differentiate it in the
marketplace. Here are some of the key ones:
© 2017 Constellation Research, Inc. All rights reserved. 8
Knowledge Management (KM)-
Powered AI Platform
Infosys Nia addresses an organization’s
growing needs for more efficient processes
and knowledge-based approaches. The Infosys
first-generation ML/AI platform provided
a starting point for Infosys customers.
By amassing the digital exhaust from log
files, tickets, interactions, transactions,
conversations, images and other digital assets,
Infosys Nia amasses valuable data and signals
in volumes that humans cannot fathom nor
manage. Today, formalized actions for humans
are stored in knowledge bases, the incarnation
of Knowledge Management (KM). The
combination of digital assets, digital exhaust
and KM assets provides the starting point
from which Nia develops and expands upon its
AI capabilities:
• KM powers AI. Infosys Nia has a Knowledge
Management DNA built from its early ML/
AI platform lineage. The system starts
Figure 3. Differentiators for Infosys Nia – Services, IP and Business Model View
Source: Infosys
© 2017 Constellation Research, Inc. All rights reserved. 9
with knowledge accumulated from years
of working and supporting IT and business
processes with deep domain expertise.
That knowledge powers the Infosys Nia AI
capabilities, enabling the desired “brain-to-
machine” automation.
• Abstraction models processes.
Understanding and abstracting business and
IT processes are fundamental to collecting
the necessary and appropriate information
and outcomes to power an AI platform.
Infosys Nia models processes in a flexible
and adaptable way, allowing the capture of
the relevant information to build the best-
fitting processes and outcomes with the
help of AI.
• Cognitive capabilities deliver outcomes.
Infosys Nia operates a set of cognitive
capabilities on top of the ever-evolving
data fabric underlying business and IT
operations. The result - new insights,
automation and outcomes. Using multiple
cognitive mechanisms simultaneously is key
for superior insights and outcomes.
• AI adds self-healing ability. Infosys Nia
empowers highly desirable next-generation
AI capabilities, such as self-healing actions,
where the AI system acts automatically
when confronted with adverse events. For
example, Nia has the ability to throttle or
slow down an IT system that is operating
in an earlier phase of a supply chain to
compensate for a system further down the
chain not working as expected.
By combining these capabilities, enterprises
have already seen positive outcomes using
Infosys’ first-generation ML/AI platform.
For example, at an apparel manufacturer,
prediction models have reduced IT costs
up to 90 percent. In product development,
the Infosys first-generation ML/AI platform
was able to reduce product lifecycle times
by approximately 50 percent, cutting down
the number and length of iteration phases
between product design and manufacturing.
Constellation POV. Getting the underlying
architecture right for a new category of
software is never easy, especially for AI
platforms. Given the Infosys track record of
© 2017 Constellation Research, Inc. All rights reserved. 10
established implementations in both business
and IT deployments – the abstraction as well as
automation on the platform - and its delivery
of desired outcomes, Infosys has delivered
60 customers. What sets Infosys Nia apart
is the approach of Knowledge Management
by default. Infosys starts with a live, active
and vibrant underlying knowledge base that
in many cases is actively used by its teams
for information technology outsourcing and
business process outsourcing. This head start
beats starting with a data dump and then
regular data imports that consume valuable
resources and time.
The first-hand experience of its teams for
information technology outsourcing and
business process outsourcing gives Infosys an
advantage. When a product has to be proven
for internal operations as well as customer
use cases, it usually creates a higher validation
hurdle to prove itself. In the case of Infosys
Nia, it would be hard to convince enterprises
to use the platform if Infosys was not able to
show positive returns from its in-house use
cases. Infosys’ outsourcing scenarios provide a
mutual transparency between the enterprise
customer and Infosys. Enterprise CxOs making
decisions on AI platforms can see the benefits
of Infosys’ Nia usage.
Deep Domain Expertise that
Fosters Success
Infosys helps enterprises become more
efficient. In many engagements, the company
has become a partner to the client. The
many engagements over three decades
of operation has helped Infosys create a
deep understanding of successful business
processes, including what makes them
appropriate, compliant and successful. This
expertise has been captured in Infosys
Knowledge Bases for many years.
Infosys Nia aims to achieve automation of
business and IT processes based on this
repository. The focus on Knowledge Bases
gives most AI offerings by services vendors
like Infosys a jump start over AI offerings from
independent software vendors. Infosys Nia is
no exception. Nia can seamlessly operate with
© 2017 Constellation Research, Inc. All rights reserved. 11
little to no delay on top of the Knowledge Base
that Infosys has built for both customers and
its own internal users.
Constellation POV. Building a software
platform in an area of deep domain expertise
reduces the risks of overall product creation.
Combining that with Infosys’ more than
three decades of human expertise and rich
knowledge base helps to instantly validate
the Nia platform. As support professionals
monitor the system, they will validate
suggestions and actions offered by Infosys’
first generation ML/AI platform.
Infosys professionals working with enterprises
in outsourced situations will be able to quickly
discern if an early implementation of Nia is
working appropriately and creating intended
value for the client. The codified knowledge
and instant validation of Nia help enterprises
have trust in handing over partial or full control
of AI products.
For enterprises, this low-risk approach enables
a trusted handler to monitor Nia actions,
intervening, correcting, and stopping actions as
needed. CxOs who have to approve the go-live
of AI platforms and struggle with putting their
company’s operations (and their reputations)
on the line gain peace of mind.
More importantly, Infosys disrupts itself with
Nia. In this case, Infosys changes from being a
services provider to a combination technology
and services provider, which is a major market
positioning change. Adding capabilities beyond
services means that Infosys can gain a greater
share of clients’ wallets and more integration
synergies with clients. Infosys’ transition from
services to technology-based AI-enabled-
processes makes it easier for clients to shift
from human- to AI-powered services, all
supported by the same vendor.
Constellation remains concerned about
the relatively heavy reliance on offering
services rather than software in Infosys
implementations to date. Hopefully, Infosys
Nia will help shift more of Infosys’ business
toward offering software.
© 2017 Constellation Research, Inc. All rights reserved. 12
Flexible Licensing that Allows
Scalable Consumption
Licensing is always an area that enterprises
consider when looking for next-generation
applications, as it drives a key percentage of
Total Cost of Ownership (TCO). Infosys offers
three flexible licensing options for Infosys Nia:
1. Standalone license. A stand-alone Infosys
Nia license offers the freedom to deploy
the product on premises or on a compatible
cloud infrastructure.
2. Managed service. Infosys Nia can be set
up as a managed service, in which Infosys
manages the product for the customer
either at the customer site or in the
public cloud.
3. Prebuilt solutions. Customers may
consume Infosys Nia as part of a prebuilt
solution that is embedded into the clients’
existing software – the equivalent of a
runtime license.
Constellation POV. Flexible licensing and
deployment models give organizations
choice. Some customers seek on-premises
deployments because they prefer running
software locally, often motivated by data
residency regulations, data privacy rules,
performance factors and existing datacenter
and server capacity. Not surprisingly, Infosys
offers a managed services option - true to its
own organizational DNA but also matching
the demands and needs of large parts of its
client base.
Open Source DNA that
Targets Innovation
Infosys Nia is built on top of popular and
proven open source technologies like Apache
Spark. The platform could not have been made
available and extended so quickly if not for
open source technology. Open source-based
technology not only can lead to superior
innovation speed, but it also has the
advantage of abundant validation – both by
vendors creating solutions and by companies
using the technology in everyday next-
generation applications.
© 2017 Constellation Research, Inc. All rights reserved. 13
Open source innovation has allowed Infosys
Nia to “stand on the shoulders of giants”,
as Infosys CEO Vishal Sikka often pointed
out at the Infosys Confluence conference
in 2016. That allows the vendor to focus on
what matters most – domain expertise and
its realization in a modern architecture that
enables greater customer success through AI.
Moreover, the decision to make Infosys Nia
based on open source offers other possibilities
for customers:
• Extending with partners. Given the
popularity of open source, many potential
partner solutions run on the same
foundation, giving both customers and
vendor many partnering options.
• Innovating with academia. Much of the
leading innovation is happening in academia,
and Machine Learning and Artificial
Intelligence are no exceptions. The academic
world uses the same open source-based
technologies, thus making the transfer of
innovation easier to a platform such as
Infosys Nia.
Constellation POV. Open source has leveled
the playing field between traditional software
companies and all other players. By taking
the underlying architecture and operational
necessities out of the equation for building
a new product, open source has allowed an
innovation drive by existing and new market
players like no other technology improvement.
Infosys’ advantage is that it can build on a
modern platform and make years of knowledge
and experience available as a differentiator
without losing time and investment on the
basic blocking and tackling that ultimately all
products require.
On-Platform IP that Accelerates
Implementation Speed
Time to go-live remains a critical aspect for all
enterprise applications as substantial benefits
hinge on timely implementation and smooth
operation. Infosys provides several Intellectual
Property (IP) assets on the Infosys Nia
platform that help enterprises launch quickly.
© 2017 Constellation Research, Inc. All rights reserved. 14
Infosys packages the following assets with the
Nia platform:
• Adapters. Next-generation applications
generally do not operate as standalone
offerings but are integrated with other
applications used by enterprises. Infosys
provides adapters for the most popular
ones, such as applications from SAP, Oracle
and Salesforce. This allows enterprises
to worry about less in operating and
integrating an AI platform, with the
software vendor taking ownership of
integration and managing updates.
Enterprises can focus on improving
processes and investing strategically.
• Automatic correlations and insights.
While enterprises could build their
own Machine Learning, analytical and
statistical applications, it is always faster
to use something that is already
available. Infosys makes out-of-the-box
correlations and several insights available
on the Nia platform.
• Ontologies. Creating and maintaining
ontologies is a cumbersome and expensive
process for anyone – especially enterprises.
Jumpstarting the ontology availability
process is valuable for enterprises, and
Infosys makes ontologies available to clients.
• Scripts and workflows. Every software
product has several scripting capabilities
and equally needs some degree of workflow
automation. Not having to start with Line
One in these coding efforts is important
for enterprises to achieve an earlier
launch date, so Infosys makes these code
assets available.
Constellation POV. Time to go-live is essential
when enterprises use strategic software
applications that change the way they operate
– internally and externally. Any help to
launching more quickly and more effectively
is of immense value. Ingestion of large bodies
of data has emerged as a significant challenge
with ML and AI systems adoption. Infosys’
systems integrator DNA helps its customers
by expanding the pre-built IP asset offerings
to improve go-lives. This approach helps
© 2017 Constellation Research, Inc. All rights reserved. 15
differentiate Infosys Nia from competitors that
discover many of these capabilities in a later
phase of the product lifecycle.
A S S E S SIN G INFOS YS NIA
The success of AI platforms hinges on the four
criteria introduced earlier - data, computing
capacity, data science and time.
Data
While more data helps, making sense of
the data and making it actionable is more
important. The KM-based DNA of Infosys
Nia provides a very favorable feature, as
information that comes from the KM-based
system has already been organized, normalized
and made available for both machine and
human interaction. Moreover, through
its business process and IT outsourcing
businesses, Infosys knows what works and
what does not, so it doesn’t have to establish
the business validity of ingested data before
formulating actions. On the voracity aspect,
when putting more data into Infosys Nia, the
flexible deployment of the platform is a key
advantage. Enterprises can decide where
to operate Nia on the whole spectrum of
deployments – from on-premises all the way to
the public cloud.
Computing Capacity
Organizations need to run many models of
the data and of the numerous permutations
on subsets of that data. This key capability of
the AI platform requires a lot of computing
capacity. Often, many models run without
generating much value, until they fire up one
fine day. Access to cheap computing capacity
in the public cloud enables hyper-scaling of
resources as well as subscription pricing.
Data Science
The quality of algorithms and the innovation
on the algorithm front can give enterprises
a substantial leg up on the competition. The
search for the uber-algorithm that can predict
the right algorithm to run on the right subset of
data to automate decisions is in full swing. The
© 2017 Constellation Research, Inc. All rights reserved. 16
brightest minds in the discipline are working
hard to come up with the first and the best
solutions that use such algorithms.
Infosys has made substantial investments in its
data science practice and has many respected
data scientists on its payroll. But it would be
a surprise if the uber-algorithm came from
Infosys or any other technology outsourcing
firm, as the services DNA is likely too strong
and would overshadow the level of R&D
required. But when it comes to innovation, you
never know what will happen and these new
algorithms may come from Infosys as well as
from anybody else researching them.
Time
It takes time to get all the ingredients for
success in AI right. Infosys is in a good position
when it comes to KM-based AI for business
process and IT outsourcing use cases. The
stakes in this field remain high, though, and all
players need to invest substantially to remain
at the top of the game.
Constellation POV. Across the four criteria
for success in AI, Infosys Nia scores well for
handling use cases related to business process
and IT outsourcing. Business process and IT
outsourcing services will be the sweet spot
for Nia in the near future. Over time, Nia will
have to prove it can provide validated benefits
beyond these use cases.
Infosys is at a disadvantage with data and
computing capacity when it comes to AI
competitors that are also IaaS providers.
Infosys or its customer will have to pay
a premium to procure data storage and
computing capacity, compared to the IaaS
vendors’ native AI offerings. But by making
Nia a multi-cloud product, effectively giving
customers a choice to deploy Nia across a
variety of IaaS providers, neither Infosys
nor its customers should be held hostage to
unfavorable terms by a public cloud platform.
On the flip side, data privacy and residency
requirements are in Infosys’ favor, as the
flexible deployment options of Nia allow the
use of code close to the data – with no public
cloud exclusivity.
© 2017 Constellation Research, Inc. All rights reserved. 17
On the data science side, Infosys has no
data science “superstars” on its payroll, but
it is less likely that a current superstar will
be tomorrow’s superstar when it comes to
innovative data science ideas. Partnering
with smart minds in academia is a good
alternative strategy.
Finally, Constellation sees Infosys Nia scoring
well on the time dimension. It is certainly in
a very good position compared with systems
integrators as well as with pure software
product vendors. But Infosys must make sure
that it keeps investing into Nia as a product,
resisting the potential organizational urge to
return to being purely a services organization.
Competitive Positioning
The field of ML/AI is rapidly getting
crowded with vendors coming from diverse
backgrounds. It’s important for enterprises
to understand where each vendor started
its ML/AI journey, as there are pros and cons
associated with each point of origin. Here are
some common paths:
• SaaS/ERP vendors shift to AI. This group of
vendors has all the key data of the system
of record and powers the transactions that
create those records. Increasingly, these
vendors are moving away from traditional
business intelligence and data warehouse
solutions to address their customers’ need
for business insights and they are acquiring
and/or launching their first Machine
Learning and Artificial Intelligence offerings.
• IaaS/platform vendors have first-mover
advantage. ML/AI is computing intensive,
and as such, attractive to IaaS vendors.
Enterprises are building next-generation
applications using ML/AI and therefore
expect the platform vendors to allow the
creation, operation and support of these
applications. This group was the first to get
to the market.
• Business intelligence/data warehouse
vendors must make the shift. The vendors
in this group were the traditional software
providers to enterprises, helping them
understand what was happening in their
businesses. These vendors were driven by
© 2017 Constellation Research, Inc. All rights reserved. 18
human intelligence and talent, but now face
an innovation challenge in making machine-
driven processes real in their products.
• Systems integrators/business process
outsourcing providers seek new
opportunities. BPO providers have talked
about robotic process automation for over
a decade with their customers, seeking
to ensure consistent, cost-effective and
scalable service to them. In the past, this
was usually a rules-based approach; now
ML/AI provides a better and more effective
platform to address these needs. Infosys
falls in this category.
• Startups address innovation gap. Fast-
growing software fields, especially those
with a lot of potential for enterprises, always
attract startups that can tackle innovation
through ML/AI.
Constellation POV. Infosys Nia is well
differentiated among offerings from these five
groups of vendors. As a systems integrator/
business process outsourcer, Infosys enjoys
early-to-market advantages. Compared
to the SaaS and ERP vendors, Infosys can
look broadly at data across these vendors,
something that well reflects the reality of the
installed base in enterprises.
Compared with IaaS/platform vendors, Infosys
offers a complete solution for the needs of
enterprises, not merely a platform on which
they can build a next-generation application
with ML/AI. Compared with business
intelligence/data warehouse vendors, Infosys
is not weighed down by a demanding installed
base that often still requires outdated business
practices. Instead, Infosys can start with a
clean slate to tackle ML/AI.
And lastly, compared with startups, Infosys
has global reach, a blue-chip customer base,
deeper capital investment budgets and, first
and foremost, a service delivery capability that
startup vendors traditionally lack.
However, Constellation believes ML/AI-
powered platforms are in their early days.
All vendors have to address gaps and fill in
offerings quickly as the space quickly evolves
and matures. Infosys must address functional
© 2017 Constellation Research, Inc. All rights reserved. 19
gaps when moving into other ML/AI use cases
such as customer experience and “know your
customer” use cases.
With its ML/AI offering, Infosys can help
customers automate their processes for better
business outcomes. Infosys’ deep domain
expertise and existing business process and
IT outsourcing business have produced valid
benefits with the first-generation ML/AI
platform, which now becomes part of Infosys
Nia. This means that Infosys Nias a strong
solution of value for business process and
IT outsourcing use cases. When the robotic
process automation of Infosys AssistEdge is
added, Infosys Nia only becomes stronger.
As for additional ML/AI use cases, Infosys
Nia still has to show that it can create value
for enterprises in real-world engagements.
The good news is that these are currently
underway. Before making a systems decision,
CxOs should ask Infosys for customer
references for their specific use cases.
RECO MMENDATIO NS:
FO CUS O N BUSINE S S
OU TCO ME S
Organizations should focus on business
outcomes first. Prioritize which business
problems are the biggest ones.
Identify and understand what the organization
needs to address and to achieve before
considering Infosys Nia or any other ML/AI
application or portfolio. Don’t experiment
with ML/AI before addressing more urgent
priorities and don’t force fit an off-the-shelf
application into a service if the solution doesn’t
promise desired business outcomes.
Consider these factors when selecting an ML/
AI-based solution:
• Organizational fit. The solution needs
to fit the challenges and capabilities of
the organization. The best product in the
market may not be the best product for an
organization because the product needs to
be deeply embedded in the value creation
and service chains of the organization.
© 2017 Constellation Research, Inc. All rights reserved. 20
• Solution fit. Simply put, it has to work. The
beauty of an ML/AI solution is that if a
business user sees results, he will be very
fast at discerning the quality of the solution
- whether it’s a positive surprise, simply
interesting, or a waste of time. Capitalize on
the business user’s ability to very quickly
perceive if there is value in a solution.
• Landscape fit. The solution needs to fit
into an enterprise’s systems landscape. It
needs to relate to the rest of the automation
portfolio, as organizations don’t want to
create a stand-alone solution. Instead, work
toward an integrated portfolio that elevates
the enterprise’s overall capability and helps
employees make better decisions.
• Cost versus benefit. Measure new
innovative technologies such as ML/AI
with a cost/benefit ratio. Consider all
factors in how the technology supports the
business models.
© 2017 Constellation Research, Inc. All rights reserved. 21
ANALYST BIO
Holger MuellerVice President and Principal Analyst
Holger Mueller is vice president and principal analyst at Constellation Research, providing guidance for the
fundamental enablers of the cloud, IaaS, PaaS, with forays up the tech stack into big data, analytics and SaaS.
Holger provides strategy and counsel to key clients, including chief information officers (CIO), chief technology
officers (CTO), chief product officers (CPO), investment analysts, venture capitalists, sell-side firms and
technology buyers.
Prior to joining Constellation Research, Holger was VP of products for NorthgateArinso, a KKR company. He
led the transformation of products to the cloud and laid the foundation for new business-process-as-a-service
(BPaaS) capabilities. Previously, he was the chief application architect with SAP and was also VP of products for
FICO. Before that, he worked for Oracle in various management functions - both of the application development
(CRM, Fusion) and business development sides. Holger started his career with Kiefer & Veittinger, which he
helped grow from a startup to Europe’s largest CRM vendor from 1995 onwards. Holger has a Diplom Kaufmann
from University of Mannheim, with a focus on Information Science, Marketing, International Management and
Chemical Technology. As a native European, Mueller speaks six languages.
@holgermu | www.constellationr.com/users/holger-mueller
www.linkedin.com/in/holgermueller
© 2017 Constellation Research, Inc. All rights reserved. 22
A BOU T CO NS TELL ATIO N RE S E ARCH
Constellation Research is an award-winning, Silicon Valley-based research and advisory firm that helps organizations
navigate the challenges of digital disruption through business models transformation and the judicious application of
disruptive technologies. Unlike the legacy analyst firms, Constellation Research is disrupting how research is accessed, what
topics are covered and how clients can partner with a research firm to achieve success. Over 350 clients have joined from an
ecosystem of buyers, partners, solution providers, C-suite, boards of directors and vendor clients. Our mission is to identify,
validate and share insights with our clients.
Organizational Highlights
· Named Institute of Industry Analyst Relations (IIAR) New Analyst Firm of the Year in 2011 and #1 Independent Analyst Firm for 2014 and 2015.
· Experienced research team with an average of 25 years of practitioner, management and industry experience.
· Organizers of the Constellation Connected Enterprise – an innovation summit and best practices knowledge-sharing retreat for business leaders.
· Founders of Constellation Executive Network, a membership organization for digital leaders seeking to learn from market leaders and fast followers.
www.ConstellationR.com @ConstellationR
[email protected] [email protected]
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