Setting up a COE ( Center of Excellence ) for AI ( Artificial Intelligence ) could be a daunting task. Lack of skills and quality data sets could hold you back. But still you should not wait any longer and start with what you have, build skills by training people, and move ahead in gettering executive approval for building an artificial intelligence center of excellence

1. Yogesh Malik
Exponential Thinker | Technology Evangelist | Digital Futurist @ https://FutureMonger.com/ &
https://welcome2050.com/
May 1 · 8 min read
How to Set-up an Arti cial Intelligence
Center of Excellence inYour Organization?
Harnessing the potential of arti cial intelligence as part of a digital
transformation strategy will be the key component in creating the
intelligent enterprise of tomorrow. Arti cial intelligence is already
rising to play a signi cant role in helping enterprises re-imagine their
products and services, drive revenue, realize business e ciencies, and
enrich the customer experience.
Photo by Venveo on Unsplash

2. Andrew Ng is one of the most recognizable names in the Arti cial
Intelligence community. He is Chief Scientist of Baidu. Andrew formed
the Google Brain deep learning AI system while at Mountain View.
Once he expressed: -
In the past, a lot of S&P 500 CEOs wished they had
started thinking sooner than they did about their
Internet strategy. I think ve years from now there
will be a number of S&P 500 CEOs that will wish
they’d started thinking earlier about their AI strategy.
But how do you start arti cial intelligence related initiatives in your
organization? What problems will it solve? Stick with me here, because
in this article we will be talking about those things.
. . .
Why DoYou Need an Arti cial Intelligence
COE inYour Organization?
It may seem that there are no immediate advantages of using Arti cial
Intelligence in your organization and you may hesitate and ask, “Is
there an AI solution to every business problem?”. Like the Internet
revolution a decade ago AI is not optional anymore. Any delay is
dangerous and if you want your organization to survive for another
decade, you need to start embracing AI today. We already know that
algorithms are ruling the world—from sorting cucumbers to curing
cancers arti cial intelligence based algorithms are doing everything
With this in mind let’s turn our attention to how today’s organizations
can start AI Initiative within a minuscule group that can expand
throughout the organization. But, is there a size that ts all solution?
Small and medium size companies—Can they ignore AI? If not, then
how do they start Center of Excellence for Arti cial Intelligence? No
matter, what your think of AI but recent technological development
associated with new patterns of globalization is threatening to create a
new tomorrow—forcing businesses to re-imagine their products and

3. services, realize business e ciencies and drive customer experience to
an altogether di erent level.
You need to develop a team of inspired and talented, take initiatives for
developing AI systems in your organization. This would take executive
sponsorship, capturing benchmark that can demonstrate values—all
focused on organization needs, making you propel AI initiatives from
conceptualization to implementation
. . .
Strategy for Arti cial Intelligence Center
of Excellence
You need to bring in research orientated tech expertise and establish a
platform that can catalyze the growth of the deep technology
ecosystem and present the stimulus for innovation in the elds of data
science and arti cial intelligence.
This new team should function like an extended team to the external
units to deliver excellence by scaling up existing/new product/project
activities build around arti cial intelligence technology.
From value creation to value realization, this new AI COE should
deliver minimum viable product (MVP) with original ideas by
experimenting with emerging technologies. A key step towards
preparing COE for its success in the organization is to build prototypes
with a long-term view and enhance ecosystems and partnerships to
promote purposeful arti cial intelligence
The people, process and technology must be in alignment for any
new venture to be competent and holistic. These three components are
the key steps towards a successful organizational transformation
Executive sponsorship: Senior management people play a signi cant
role in the organization and an e ective sponsorship from them is
required so that you can improve collaboration across the organization.
This will bene t you stay aligned on the strategic priorities. Once you
secure their commitment sponsors can function as a point of escalation
—but make clear you don’t engage them for day-to-day tactical issues

4. Finding the right team: This could be your biggest trouble. Getting
people on-boarded for the right skills could make or break your center
of excellence strategic plan. How do you source these people? Internal
hire or external, local to your COE region or a mobile/remote worker
from some another country’s o ce
Capture benchmark that can demonstrate value: If you can’t
measure it you can’t manage it. Your leadership want to see measured
progress and you need to have a dashboard to represent internal
performance. Make it transparent and comprehensive.
Finding the right problem: Be it your organization internal problem
or customer use case, you need to research multiple launches. You need
a design thinking before you act on building an AI platform. Talk to
sales, interview clients, know their business pain points that can be
solved by the adoption of arti cial intelligence. Problem need to be
thoroughly investigated so that you can apply the right AI tool to iron
out, and present COE value proposition even for the early pilot launch.
Leveraging the data to solve it: The importance of data availability
and data quality are of pivotal value. Arti cial Intelligence provides a
whole di erent meaning to the importance of data. The collection,
distribution, and validation of data are thus important issues in the
formulation of solutions involving AI
Build a repeatable AI solution: A repeatable solution that can be
o ered to others in the company or marketed to the customer, drives
value to the business. A template approach that can be applied to the
di erent situations is invariably favorable. Center of excellence leaders
need to hook up with numerous product owners, designers, business
analysts in building horizontal or industry speci c o ering solutions

5. . . .
Challenge No #1: BuildingTheTeam
Getting the right people with the right skills could be your single most
prominent and serious challenge. Your current technology leaders and
team members may be nding themselves in the corners. Where do you
start? How do you source AI skills?
Arti cial Intelligence, machine learning, data science and
programming, people with these skills need to work together along
with domain/industry expert because arti cial intelligence approach is
not just about technical function alone. Recruiting and retaining AI
talent could be a nightmare and this can continue for months. You need
to get HR involved in nding individuals with arti cial intelligence
skills and convince executive sponsors on this or your business take the
risk of being left behind.
You may uncover that the re-skilling of your current open-minded tech
team could be a valuable option, so encourage them to take various

6. courses on arti cial intelligence and machine learning. Learning and
research platform for your internal COE members, provisioning of new
AI tools and test beds for existing and new projects, all this takes rather
a bit serious thinking in terms or research work and
operational/organizational skills.
Go for few people who are cross-skilled, multi-skilled and harmonized
with non-technical skills like communication, creativity and versatility.
If you want to extend your AI portfolio beyond proof-of-concept and
sandbox implementation, you will require real AI experts and those
skills come at a price.
Not just new AI skills, organizational level behavioral changes are
needed, not just business knowledge and technology innovation but
human insight need to bring in the products and features for
developing highly successful long-term strategies
. . .
Challenge No #2: Making Data Actionable
Many companies do not realize that they are sitting on the pile of data
that could be a virtual goldmine if managed properly. On the other
hand, lack of quality data could cost you a huge money if you want to
get it xed. But the chances are that most of the data your organization
has might not be all bad, but it won’t be able to solve the problem that
you have. Having quality data requires building e cient data strategies
and robust data management infrastructure. Your customers, partners,
employees and brand ambassadors—data is everywhere. It is up to you
how you to make data actionable by fetching insights and intelligence
out of it.
Lack of quality data might hamper your AI project as machine learning
algorithms require a massive amount of data. So if you want to write a
brand new data strategy for your organization, do not hesitate to put
required e orts in doing so.

7. Identify various types of data available; its meaning, location,
origin & structure.
How data will be stored, analyzed, processed and protected.
How various data will be packaged for reuse? What policies to
implement for e ective data governance?
Once done, do not consider it done. Make data review and
measurement an ongoing process. Your data strategy is a roadmap and
a key component for your arti cial intelligence projects. More than
ever, your ability to manage data could be the single more critical
component to your company’s success.
•
•
•
. . .
OverToYou Now
Start with what you have. Create building best practices, get your team
trained on AI skills and collaborate with others to build minimum
viable product for a pilot problem given the right dataset. Use cloud-
based AI stack from AWS, Google or Azure if you don’t want to invest in
hardware and licenses. You need to invest time and money in hiring
AI-COE Project Lifecycle

8. skilled resources and keep your current team engaged in continuing
learning new skills.
So, tried old management advice on starting a COE won’t cut it, your
approach must be unique and strategic for AI initiatives. Building an “AI
rst” culture or “AI rst” policies could be very challenging, but without
any delay you need to start looking at your organization’s existing
products and services through the lens of arti cial intelligence. You
need to start building good data strategies and create unique data sets
so that you are ready with a failure-proof arti cial intelligence center of
excellence.
. . .
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