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eyond self-driving cars, drones, intuitive home appliances,
healthcare devices, dating apps and dozens of emerging
products, there's a new corporate world of artificial intelligence.
AI and its allied technologies of machine learning, deep learning, cognitive computing, computer vision, natural language processing and
neural networks are reshaping business practices and retail strategies.
Predictive engines (such as those that generate Netflix viewing recommendations) and conversational interfaces - such as Amazon's Echo and
Google Home - are at the consumer-facing vanguard of AI. Plus, they are
also finding enterprise homes. Companies are implementing AI systems for
business processes and management decision-making as well as customer
relationship management and retail/inventory planning.
AI is driving "the transformation of firms from being product-centric to
customer-centric," says Dr. Peter Fader, a marketing professor at the
University of Pennsylvania's Wharton School and co-director of the Wharton
Customer Analytics Initiative. "As we let the computer make these decisions
for us, it gives us more capability to do things at a customer level and to let
algorithms drive that decision making in a way that humans are not very
comfortable doing right now."
Fader is also a co-founder of Zodiac Inc., a New York B2B software platform provider that uses customer analytics and predictive behavioral
models for marketing and management processes. Zodiac works with traditional and ecommerce retailers. "We ingest historical transaction information and tell companies when customers will return, how often they will
return, and how much they will spend." Fader explains the predictions are
"at the individual customer level, not at a segment or aggregate level.
"With this degree of granularity, businesses can make better decisions when
it comes to budgeting, acquisition and retention," he says. Zodiac's "Customer
Lifetime Value" (CLV) calculates the net value of the relationship a business
has with a customer. Its AI features enable a retailer to determine how an
individual shopper will remain loyal compared to what Fader calls the
60 percent-plus customers who are one-time buyers. "The core model for
our predictions requires nothing more than RFM (recency, frequency,
monetary value)," Fader says.
Joshua Montgomery, CEO of Mycroft AI, believes, "Voice assistants are the
purest form of artificial intelligence." His company foresees AI opportunities
in both the enterprise and consumer markets. Montgomery characterizes its
product as "the world's first open source assistant," able to run on a desktop
computer, inside an automobile or on a Raspberry Pi.
"AI is going to take over any applications where you have a human translating for a computer," Montgomery says, citing call centers, retail stores
and the automotive industry - "anywhere there are repetitive actions."
He expects that as applications evolve, "We'll get extra features, including
"virtual assistants capable of interacting with each other." In the process,
there will be several silos, he says.
"We're building a full AI [system] that interacts exactly like a person," he
explains. "There are a lot of deep learning technologies behind it." To accelerate development, Mycroft has plunged into the hardware sector, building
a stand-alone device with an anthropomorphic base. The Mark 1 device is
now available, and Mark 2 with advanced (but not yet disclosed) features will
be out in late 2018.
"It's extremely early in the AI market," Montgomery agrees. "The types
of assistance will change radically in the coming decade."

DIGGING INTO THE NUMBERS

Corporate enthusiasm for AI has spurred a spate of research. A September
Capgemini study, Turning AI into Concrete Value, found that 79 percent
of senior executives worldwide agreed that AI will bring "new insights
40

JANUARY/FEBRUARY 2018

and better data analysis." Similar levels
said that AI would make "our organization more creative" (74 percent)
and "make better management decisions" (71 percent).
Artificial Intelligence for Marketers
2018: Finding Value Beyond the Hype,
an eMarketer/emarsys research
report in October, cited the "explosion
of internet-connected devices collecting and sharing various types of structured and unstructured data including
text, speech, images and videos" as
a critical factor in training AI systems.
It identified current and near-term
AI applications in marketing intelligence, lead generation and customer
acquisition, marketing optimization,
customer experience management,
brand building and "content creation
and dynamic creative." The latter
includes automated writing and
image video production that "creates
specific content for targeted audiences
based on learning algorithms."
A McKinsey & Co. analysis found
that global corporate investment in AI
projects totaled about $12 billion in
2016 - a figure that is growing. The
McKinsey study listed natural language processing, natural language
generation, speech recognition,
machine learning (including deep
learning), decision management, virtual agents (including chatbots and
digital virtual assistants), robotic process automation and computer vision
as the top categories for AI efforts.

AI AT HOME, ON THE ROAD
AND EVERYWHERE

As the business opportunities for AI
take shape, consumer AI products are
proliferating - most visibly as voice
response systems in the home and
in smartphones and smart cars. AI is
also at work in daily digital activities,
from Netflix recommendations to
matchmaking and dating sites.
Spotify uses a combination of AI tools
to create its personalized recommendations. Its Discover Weekly feature
uses collaborative filtering, natural
language processing and audio recognition, which analyzes the raw audio
tracks of new music.
Olivier Malafronte, founder/CEO
of PocketConfidant AI, a French
I T I S I N N O VAT I O N

i3 - January/February 2018

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