EDITOR’S QUESTION
HOW CAN
BUSINESSES
SEIZE VALUE
FROM ARTIFICIAL
INTELLIGENCE?
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By Cyril Per ducat, Executive Vice President of Internet of Things and
Digital Offers, Schneider Electric
L
ast year, Forrester noted that: “The
honeymoon for enterprises naively
celebrating the cure-all promises of
Artificial Intelligence (AI) technologies is
over . . . AI and all other new technologies
like big data and cloud computing still
require hard work.”
Given that 70% of enterprises expect to
implement AI this year, including Schneider
Electric, I would like to offer three concrete
ways companies can seize the business value
I strongly believe AI promises.
Lesson 1: Be pragmatic
Integrating an AI strategy can seem like a
daunting task as Forrester analysts point
out, so we recommend that any company
embarking on this journey start with a
pragmatic approach to individual AI projects.
Ask upfront: “Which problem can I solve
with an AI-enabled digital solution?” This
question always prompts our R&D process to
lead with the customer challenge in mind.
help customers understand what it really
means to push forward new digital business
models in a disruptive yet profitable way.
Take long-time machine builders or Original
Equipment Manufacturers (or OEMs) as an
example. Most OEMs build highly specialised
equipment, such as the smaller-footprint
coffee pod machine we co-innovated with
our customer SOMIC.
In many cases, though, the CapEx
commitment for such tailored machines is
high. But what if a machine builder could
leverage AI, coupled with remote monitoring
capabilities, to begin offering ‘uptime as
a service’ to its end-users? This is a way to
lower the CapEx burden for end-users.
Only AI makes this business model possible,
as trained data models can qualify whether
a machine’s downtime is really a machine
issue vs. human or other error.
Lesson 3: Build strengths on top of
your domain expertise
data. Most companies are not AI experts;
channeling domain expertise it what will
make AI projects relevant to companies and
their customers.
This is really what we see as the of AI’s
golden value: turning data into insights.
Schneider Electric’s EcoStruxure
architecture is founded on our own
deep domain expertise across industry,
buildings, data centres, grid, plant and
machine. We drill down even more to the
segment level to ensure that our customer-
driven AI projects have a worthwhile
business impact.
My point here is to create AI project teams
that include an AI expert, a computer
scientist, and, just as crucial, a domain
expert. It is the domain expert who can ask
the right questions for AI to solve and, more
importantly, know how to best respond to
what the AI models reveal (e.g. predictive
maintenance applications).
AI’s promising future is here
Lesson 2: See the value in new digital
business models enabled by AI
For all of us, Digital Transformation at large
is about finding ways to create new business
value from digitisation. AI applications can
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INTELLIGENTCIO
Having strong domain expertise is critical
to making AI projects successful. Do not
underestimate its value. Why? Data overload
is a known reality, so it’s clear that we don’t
need more data. What we do need are much
better ways to tap the business value of that
So is the honeymoon for AI over? With
the proper attention to integration and
deployment issues, we believe that AI as
the next wave of IoT innovation has only
just begun.
www.intelligentcio.com