This document summarizes an article about artificial intelligence from The Smart Manager magazine. It discusses: 1) How AI is becoming more advanced through machine learning, computer vision, speech recognition, and natural language processing. These technologies are being applied in many industries like banking, insurance, retail, and IT. 2) Examples of how AI is being used, such as chatbots, image recognition for online shopping, and data analysis tools that generate reports. Sectors like marketing, customer service, and recruiting are utilizing AI. 3) That organizations must adapt to technological changes and adopt AI in order to stay relevant and not become obsolete as AI capabilities continue to rapidly improve.

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ARTIFICIAL
INTELLIGENCE
Disruption in the making
Into the neural depths
Machine power
Bots at your service
S t r a t e g y M a r k e t i n g A n a l y s i s R e s o u r c e s T e c h n o l o g y
India’s first world-class management magazine
NOV-DEC 16 VOL 15 ISSUE 6
R100nov-dec16joesarnoshawnhunterøysteindfjeldstadknuthaanaesmorgenwitzel
DAVID COLLIS
on lean strategy
for entrepreneurs.
[ PAGE-73 ]
BILL MUNN
on how to leverage
your strongest
attributes.
[ PAGE-54 ]
84

2. www.thesmartmanager.com24 The Smart Manager Nov-Dec 2016
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3. cover story
The Smart Manager Nov-Dec 2016 www.thesmartmanager.com 25
Artificial Intelligence is lending businesses a new
vigour. But can it outsmart humans who have
created it?
Experts explore the multiple facets of AI and
its implications:
 disruption in the making: Kalpana B
 into the neural depths: Philip M Parker
 machine power: Dr Pradeep Pendse
 bots at your service: Leslie Timmy

4. www.thesmartmanager.com26 The Smart Manager Nov-Dec 2016
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5. The Smart Manager Nov-Dec 2016 www.thesmartmanager.com 27
cover story
Artificial Intelligence (AI) is an idea that has oscillated through many hype cycles over many
years, as scientists and sci-fi visionaries have declared the imminent arrival of thinking machines.
But it seems we’re now at an actual tipping point. AI, expert systems, and business intelligence
have been with us for decades, but this time the reality almost matches the rhetoric, driven by the
exponential growth in technology capabilities (e.g., Moore’s Law), smarter analytics engines, and
the surge in data*.
A look at how AI has made tremendous inroads into the realm of businesses as well as our
everyday lives.
disruption in the making
usinesses these days have leapfrogged by
harnessing technology, and the way they
are operating in the present dynamic and
competitive environment is stranger than
fiction. Customer experience is improving as marketing
techniques are getting increasingly scientific. Software
tools were enablers until innovators created technology
platforms (in a recent digital episode) that not only target
the ‘how’ of the improvements but also the ‘who’.
Robotic process automation employs software robots
that execute repetitive and rule-based processes, while
advanced technology dedicated to digital labor beckons
intelligent robots to take up a portion of judgment-based
B
decision-making. The advanced side of this digital labor
consists of an array of technologies such as Artificial
Intelligence (AI), machine learning, natural language
processing, and so on. We will lay emphasis on the smarter
aspect of the digital labor spectrum and on what the future
holds for us.
Moore’s Law summarizes the observation made by
Intel co-founder Gordon Moore in the year 1965 that
the processing power of computers will double every two
years. The Fourth Industrial Revolution by Klaus Schwab
deliberates that if this holds true in the future too,
computers will attain the same level of processing power as
humans in 2025.
KALPANA B
IS PARTNER AND HEAD OF ROBOTICS AND
COGNITIVE AUTOMATION AT KPMG IN INDIA

6. www.thesmartmanager.com28 The Smart Manager Nov-Dec 2016
the concept
Let us first attempt to disentangle the intricacies of
technology and understand its wider applicability in
shaping the future of businesses.
AI is the simulation of human intelligence by
computers in different ways such as vision, speech, and
decision-making abilities; it encompasses self-learning,
reasoning, and self-optimization. Machine learning is a
branch of AI that enables computers to learn without being
explicitly programmed and choose an effective course
based on the learnings and experience.
To understand this phenomenon better, let us assume
that an academy dealing with online courses is piloting a
digital marketing campaign in different parts of a country, for
instructor-led and self-learning modules. During the course
of the campaign, if the machine learning program observes
that the self-learning course module is not preferred in a
particular region, then automatically the marketing attention
will shift to instructor-led courses. In the future, the
program will extend this knowledge to other regions sharing
similar demographics too, for effective campaigns.
Machine vision is the ability of a computer to ‘see’
just like humans, while speech recognition is the ability
of computers to ‘hear’ and understand dictation. Through
vision abilities, the application can be extended to
understand videos, images, and pictures. This opens a huge
window of opportunity to make sense of vast amounts of
data present in the format of images and videos. Speech
recognition ability allows interpretation of human speech
and spoken languages, thereby using the knowledge base
to take business decisions. Another technology that has
extensive application is natural language processing (NLP),
which can understand and generate languages that humans
use naturally with computers.
what has happened so far?
Banking, insurance, retail, IT, and telecom have been
early adopters of technology. Since technology has been
the medium and basis of executing transactions, for
long, data captured over the years acts as a natural
foundation to adopt smarter technologies. We can
expect these sectors to adopt smarter technology sooner
than others.
A few growth drivers of Artificial Intelligence are
increasing number of internet and smartphone users,
increasing traffic in online business, advancements in
big data analytics, cloud computing, proliferation of
business apps, talent, and fierce competition. AI has
entered our day-to-day lives, as business, personal, and
social worlds have shrunk within a device for users.
Whether they are automated chats about interacting with
customers to understand their problems or intelligent
segregation of pictures based on weather, appearance, and
personality traits, AI has numerous manifestations. Other
recent applications of AI that one might have experienced
are speech-to-text conversion, face recognition, age
prediction, retina recognition, and fingerprint security
scanners.
As individuals access bespoke applications, they
cursorily permit personal data to be sent to a cloud, leaving
behind a digital trail. The magnitude of personal and
business-relevant data being generated is humongous and
corporates are using it wisely to target the various user
segments. Through a shift from data elitists to amateurs,
machine learning is becoming accessible to professionals
as it is being presented by innovators in a more usable,
as-a-service package. With the mushrooming of startups,
the idea of making it a practical solution to actual problems
is becoming even more realistic.
Machine vision is the ability of a computer to ‘see’ just
like humans, while speech recognition is the ability of
computers to ‘hear’ and understand dictation.

7. disruption in the making Kalpana
The Smart Manager Nov-Dec 2016 www.thesmartmanager.com 29
Organizations will have to reshape themselves by making
the most of the overwhelming development in technology,
to rise above the noise and provide true value to the
consumer and society at large.
The views and opinions expressed herein are those of the author and do not
necessarily represent the views and opinions of KPMG in India.
applications
Vital and time-intensive areas such as onboarding
new candidates are being offered through AI-powered
recruiting and hiring solutions. Fields such as telemedicine
are being transformed by AI solutions for improved
diagnosis and lowered costs. Certain approaches are
focusing on enriching the online shopping experience
through the convenience of chatting on an integrated
chatbot platform. Image recognition technology finds huge
applicability in e-retail for refining online purchase choices.
Analyzing data has been predominantly done by humans
over the years, but intelligent platforms today are not only
analyzing structured data but also generating reports that
communicate in spoken English text.
AI platforms also help B2C sectors such as telecom,
banking, and retail in digital marketing campaigns by
generating customer-specific content throughout the
customer life cycle—by analyzing the demographics
and customer touchpoint data. Another potent area of
application is contact center automation where cognitive
solutions automate inbound and outbound calls. The
areas we discussed are sketchy reflections of the countless
applications of AI, and this technology is increasingly
making a material difference across the operating models of
many sectors today.
obsolescence
We no longer use landline telephones, telegraphs, hand-
held calculators, pagers, floppy drives, and CDs. The next
generation may not even be acquainted with these terms.
Technology is changing fast and we have to keep pace
with it to avoid being obsolete. As businesses have evolved
over past decades, society has also shown keen interest in
adopting newer technology. Organizations that were slow
to recognize this fact became outdated and finally struggled
to exist.
We are surrounded by AI—whether it is choreographed
searches or automatic advertisement feed, we have
experienced AI in different sizes and proportions.
Moore’s Law is not just a theory that suggests the speed of
advancements, but a thrilling indication that even society
needs to progress in a synchronized way. Competition
is no longer with just other incumbents or contestants
in the market, but with oneself too. Organizations will
have to reshape themselves by making the most of the
overwhelming development in technology, to rise above
the noise and provide true value to the consumer and
society at large.
what could possibly help us in the journey
n Choose the right capturing mechanisms
n [Study] the relevance and reliability of data
n Stay data-hungry—the accuracy of these systems
improve with the variety and size of data sets
n Imbibe current learnings
n Interlock safety with the solutions—embed control
mechanisms to reduce the impact of failure
n Hire the right talent mix and build a motivated team
n Select the right partners
n Stay updated—keep your ear to the ground
n Be innovative—linking data sets and extracting
unapparent associations between them could prove
progressive for your business
n Make AI an enterprise-wide priority 
*https://hbr.org/2015/03/artificial-intelligence-is-almost-ready-for-business