The Reality
of Artificial
Intelligence
How AI and unstructured data
are illuminating the Connected
Intelligence Age
A post-webinar report brought to you by Sapient Global Markets and Luminoso
AI represents a new business paradigm
An investor contacts a financial advisor to discuss the
investor’s asset portfolio. The advisor reviews portfolio
performance, current holdings, recent trades and so
on. The investor asks questions. The advisor responds
dutifully and adds commentary about the volatility of the
current market.
This exchange between advisor and client is typical
in every way except one. While the client was a real
person, the advisor was a robo-advisor equipped with
artificial intelligence (AI). AI technology is advancing
rapidly, moving from simple, automated allocation tools
to virtual assistants customizing investment advice for
individuals—all within the next 12 months, according to
Josh Sutton, Global Head, Data & Artificial Intelligence at
Publicis.Sapient.
So what’s driving the increasing adoption of AI? What
CONTRIBUTING EXPERTS
Josh Sutton
Global Head, Data & Artificial
Intelligence
Publicis.Sapient
compelled Google CEO, Sundar Pichai, to state earlier
this year, “We will move from mobile first to an AI first
world.”
Before we answer those questions, let’s consider what’s
at stake. Forrester, one of the most influential research
and advisory firms in the world, believes that 25 percent
of job tasks in the world will be impacted by AI in some
fashion within the next three years. What’s more, while
AI will produce many winners, there will be noteworthy
losers. Every two weeks a company on the S&P 500 is
delisted.
AI isn’t just another new technology. It represents
a new business paradigm. This report features two
leading voices in Data and Artificial Intelligence in a
lively discussion about AI and its impact on business and
societies worldwide.
CONTRIBUTING EXPERTS
Dr. Catherine Havasi
CEO, Co-Founder
Luminoso
Welcome to the Connected Intelligence Age
We are witnessing an evolution from Industry 3.0,
the Information Age, to Industry 4.0, the Connected
Intelligence Age. While the Information Age lasted
roughly 40 to 50 years, the Connected Intelligence Age is
only expected to span 10 to 15 years.
That’s because it’s evolving exponentially rather than in
the linear progression we’ve typically seen in the past.
For one, technological breakthroughs are occurring at
a much faster pace, lending to the notion that we are
entering unchartered waters. For another, there’s been
a shift to more ubiquitous user interfaces and machine
intelligence.
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Another sure sign is big data platforms. “I really think
about data as the fuel for all of the capabilities we’re
talking about,” said Sutton.
attributes to help identify the right message and the right
time to deliver that message to particular consumers for
a much more impactful result.
For instance, an early AI use case relates to leveraging
unstructured data for advertising—sifting through
mountains of unstructured data to uncover actionable
insights from consumers. Historically, advertising has
favored segmentation models with broad messaging
for a wide array of consumers. With AI, companies can
boil down massive amounts of data into individual level
The goal of advertising is still about reaching a consumer
in a way that’s relevant and meaningful. By moving
away from legacy models built on group messaging to a
model that targets specific individuals, which can only
be achieved through machine learning, companies could
potentially reduce ad costs by 15 to 20 percent.
Industry 3.0 | Information Age
Industry 4.0 | The C onnected Intelligence Age
Mobile Connected Population
TBD…
Machine Intelligence
User F riendly GUI
Mainframe Computers
© Copyright Publicis.Sapient | Confidential
Desktop
Computers
Business Value Created
Business Value Created
Internet
Decades
Ubiquitous User Interfaces
Big Data Platforms
Machine Learning
WE ARE H ERE…
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The rise in unstructured data
Unstructured data—data that falls outside of database
fields such as enterprise text information, social media
posts, mobile text messages and web content—makes up
the majority of data in the world today, roughly 80 to 90
percent. With the amount of unstructured data doubling
every year, it’s easy to come to the conclusion that within
two years, there will be more unstructured data created
than all the data currently in existence.
That’s not something companies will able to translate
into structured data. They will need alternative methods
to process and develop actionable insights from this
growing data segment.
One such solution is the use of virtual assistant
technology—the ability for virtual assistants (the next
level of chatbots) to listen to open-ended questions and
engage in a dialogue similar to typical human
interaction. This type of interaction could lay the
foundation for capturing unstructured data (i.e., insight
about what customers are looking for) at the individual
level to provide tailored information or
recommendations based on insights generated from a
virtual conversation.
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Keys to AI success
Having helped many companies implement AI,
Dr. Catherine Havasi , CEO and co-founder of Luminoso,
an AI company helping large Fortune 1000 companies
extract value from unstructured data, has seen AI
become more than just an interesting conversation piece.
“I think AI has really come of age,” said Dr. Catherine
Havasi, CEO and co-founder of Luminoso. “It’s become
something that companies in financial services, consumer
electronics or any other vertical can operationalize within
their organizations.”
“It’s become something
that companies in financial
services, consumer
electronics or any other
vertical can operationalize
within their organizations.”
According to Havasi, there are four keys to AI success:
1. INVOLVE ALL STAKEHOLDERS
Because AI ingrates customer data, many departments
within an organization are impacted. It’s imperative that
all stakeholders involved in the process are brought in
at the very beginning so they understand the power of
AI and the amount of data coming in to enable valuable
analysis.
2. COMBINE CASUAL AND MACHINE
LEARNING SYSTEMS
Both casual and machine learning have received media
attention. But what if the power of machine learning was
combined with casual, everyday language? By putting
the two together, machine learning becomes easy to use,
and useful to the enterprise, generating meaningful and
actionable insights from things like customer interaction
with virtual assistants.
3. CUSTOMERS GIVE YOU THE DATA.
DON’T WASTE IT.
When customers give your company feedback, they
expect you to consider that feedback in your decision
making. Sharing this information with the customer
and leveraging feedback for improvement makes the
customer feel like they’ve been heard and that they
matter. At present, companies collect customer feedback,
but very few engage individual customers in a dialogue.
That will change with AI.
4. DON’T BE SENTIMENTAL ABOUT
SENTIMENT ANALYSIS.
Sentiment analysis identifies and categorizes opinions
in text by the writer’s attitude toward a given topic
expressed as positive, negative or neutral. As we’ve
progressed with AI, we see that sentiment analysis falls
short on the deep questions that customers have and
companies can design solutions around.
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w w w . l u m i n o s o . c o m
AI Advances
With calls that we are entering a new business paradigm,
the devil’s advocate in the room chimes in, “Is this hype
or real?” For those who need a little more concrete
evidence beyond Gartner, Google and Forrester, some
examples of recent advances in AI add clarity and
underscore its importance to the future.
The first advancement is term embeddings, which is
often referred to in the media as “deep learning.” Term
embeddings turn language into math, enabling more
quantitative analysis to take place. These representatives
are fed into an algorithm. While text by humans often
includes slang and analogies, term embeddings allow for
a more natural interaction system. AI can identify how
concepts are related to each other, how they influence
each other and, perhaps most importantly, how they
drive potentially numeric key performance indicators
(KPIs).
Another important AI advancement is the increase in
unsupervised systems. AI takes in information from
consumers talking in a very naturalistic way. People use
slang, jargon, metaphors and comment off-handedly
about world view changes. A big AI breakthrough is using
unsupervised teams to automatically understand how
consumers naturally communicate.
TERM EMBEDDINGS:
The Al innovation that makes this possible
Expense
Cashier
Person
Supermarket
Spend
Buy
Groceries
Cook
Building
Buy
Money
Bank
type of
Produce
Wallet
Groceries
location
Pocket
Company
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True Innovation
Most innovations are iterations of existing products
—better but not breakthrough. AI’s impact is potentially
much greater. “AI doesn’t just let you do the things you
used to do faster. It lets you do more,” said Havasi.
With AI, companies can build high-touch customer
programs that never existed before. What took days with
traditional approaches can be processed in five minutes
using AI.
Not only can you do more with AI, you can also eliminate
things like inherent bias that occurs when people
interpret the results.
Where we are now with AI is exciting. Where we could be
in a matter of months with AI could simply be amazing.
About
Luminoso Technologies, Inc. is a leading natural language
understanding analytics company that enables clients to
rapidly discover value in their unstructured text data. Our
company has deep roots in the artificial intelligence and
natural language processing space, having been founded
at MIT Media Labs in 2010 after a decade of research.
Luminoso’s artificial intelligence-based software uniquely
produces the most accurate and unbiased, real-time
understanding of what people are saying, including insights
that were not anticipated. These insights are used to
increase marketing performance and build better customer
experiences. Luminoso provides multilingual, flexible
software that can be deployed to meet client needs in either
a standalone Cloud or On Premise solution or integrated
into an end-to-end client platform via an API solution.
Sapient Global Markets, a division of Sapient®
(NASDAQ: SAPE), is a leading provider of services to
today’s evolving financial and commodity markets. We
provide a full range of capabilities to help our clients
grow and enhance their businesses, create robust and
transparent infrastructure, manage operating costs, and
foster innovation throughout their organizations. We
offer services across Advisory, Analytics, Technology,
and Process, as well as unique methodologies in program
management, technology development, and process
outsourcing. Sapient Global Markets operates in key
financial and commodity centers worldwide, including
Boston, Chicago, Houston, New York, Calgary, Toronto,
London, Amsterdam, Düsseldorf, Geneva, Munich,
Zurich, and Singapore, as well as in large technology
development and operations outsourcing centers in
Bangalore, Delhi, and Noida, India. For more information,
visit www.sapientglobalmarkets.com
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