Artificial Intelligence is an enormous field. It comprises of various disciplines and a variation of tools and platforms. There is no boundary to what these artificial intelligence techniques can be applied across numerous business domains. Let’s unpack and take a stab at the importance of learning artificial intelligence

1. Why Should You Learn Arti cial
Intelligence Like A Maniac?
Yogesh Malik
Jan 16 · 7 min read
It looks as if a day cannot go by without a new story warning that
arti cial intelligence is coming for our jobs or arti cial intelligence will
change the face of humanity. If you want to be part of this radical
transformation you do not need to wait for your
professor/manager/mentor to tell you to learn arti cial intelligence. It
is the skill of the century. This article broadly touches why one should
Photo by Kyle Loftus on Unsplash

2. learn arti cial intelligence and di erent methods and learning
frameworks that I have personally applied to my learning.
Arti cial Intelligence is an enormous eld. It comprises of various
disciplines and a variation of tools and platforms. There is no boundary
to what these arti cial intelligence techniques can be applied across
numerous business domains. Let’s unpack and take a stab at the
importance of learning arti cial intelligence.
👉 AI IsThe Skill OfThe Future
Despite recent exponential growth in the eld of arti cial intelligence,
there is skill shortage. To prepare yourself with a future-proof career
you will require pro ciency in arti cial intelligence.
As arti cial intelligence can be applied to a lot of problems and
di erent markets so it should be seen as a fundamentally new approach
to every problem and situation.
My article 🔗How To Reinvent Your Career By Learning Arti cial
Intelligence explains how learning arti cial intelligence will prepare
you to take advantage of unseen opportunities and pave the path for
the personal vision for success.
There are many job pro les and specializations for an arti cial
intelligence engineer. Following are few examples of these pro les: -
◼ Design arti cial intelligence enabled products and services
◼ Explore real-world problems where arti cial intelligence technology
can be applied
◼ Evaluate various algorithms
◼ Specialized research to advance current technologies
◼ Industry-speci c data mining and data analysis to create more value
◼ Software design and information architecture

3. ◼ Professional/managed services
👉 Learning AI: Formal Quali cation or
Do-It-Yourself Way
What can be more exciting than learning a skill that will give you more
opportunities and widen your view around the future of work and
business? On the face of it appears simple that you can join some
university, get a degree in arti cial intelligence and you are done, but
here is the ironic thing—In a traditional career track, education, skills,
work experience, and job roles: should be aligned as much as possible,
but a profession in Arti cial Intelligence can be realized in many
paradigms and in practically all industries. Healthcare, telcos, military,
art, research, manufacturing, marketing, nance, and transportation—
all these industry sectors need arti cial intelligence skills. Alternative
areas of massive opportunities embrace ethics, philosophy, policy
making, and civic planning.
In my earlier article 🔗 Learning Arti cial Intelligence—Formal
Education or Online Self-learning (Ph.D. or MOOC), I have
explained the challenges and also concluded that if you crave to join
research or academia and contribute to the development of arti cial
intelligence then a formal education would be a good t; and if you are
someone who prefers to build some great product/feature and launch it
within the next 18 months then you can learn arti cial intelligence by
attending structured and specialized online courses.
To accomplish any form of learning, recognize your areas of strength
and weakness, identify what environment suits your learning and what
distracts you. Then only, you will be better prepared to meet the answer
to your most important question—Formal arti cial intelligence
education or online-learning? A Ph.D. in Arti cial Intelligence or
MOOC

4. In the same article, I have discussed the comparison between formal
quali cation and do-it-yourself kind of online courses.
👉 Choosing A Learning Approach Based
OnYour Current Role
With so much hype about the eld of arti cial intelligence, it is
surprisingly easy to get it mistaken. Arti cial intelligence eld is so
wide that it is easy to hit a roadblock because you started learning it in
the wrong way (or a di cult way) without assessing your current role
and readiness. Complex emerging technologies like arti cial
intelligence, machine learning, and the neural network have the
potential to create whole new business models. Sales, marketing,
technology, support—leaders, and employees from all domains, need
to learn arti cial intelligence—but di erently.
In the article 🔗Choosing The AI Learning Approach Based On Your
Current Role I created three roles and charted out di erent high-level
learning approach for each role. Below is the snapshot of the same:
Role1: Executives and leaders—should be prepared to act quickly to
make informed decisions on how to use arti cial intelligence for their
own business, or how to employ arti cial intelligence to increase
customer value propositions.
Role2: Specialists from similar elds—having a high level of
information technology awareness around their domains, familiar with

5. data, statistics, and programming—but very new to arti cial
intelligence. Wants to do hands-on within a week after learning
arti cial intelligence.
Role3: Experienced or fresh graduates—ready to transform/create
a career out of arti cial intelligence. People can spend around 20 hours
per week in learning new skills for a career transformation.
For detailed information on each of these three roles, you can refer to
my article on the same.
👉 AI Careers And Job Roles
Small or big, organizations can’t ignore arti cial intelligence.
Enterprise level organizations will have their own 🔗Center of
Excellence in AI dealing with various emerging technologies like
advanced arti cial intelligence, machine learning, robotics, quantum
computing, internet of things, cognitive computing etc.
Organizations won’t protect jobs that are made redundant by
technology automation, nobody can. Some companies recognize the
concern towards their employee and encourage them for exibility and
re-skilling. Do not decline any such opportunity to learn future-ready
skills. It won’t be pleasant because there is a lot of uncertainty about
the future with people losing jobs due to automation.
This article barely hints the technological view of Arti cial Intelligence,
but the best-known attempts to understand arti cial intelligence are
not about technology as AI is more than coding, automation tools, and
algorithms.
Whether you choose to become a data engineer, data scientist, AI
researcher, machine learning engineer or a social scientist—a career in
arti cial intelligence can be realized in a variety of settings including
public organization, private corporates, scienti c research, government
agencies, and military.

6. Future of Arti cial Intelligence
Research data from McKinsey Global Institute says that there is large
potential for AI to contribute to global economic activity. 70 percent of the
organization would have adopted at least one type of AI technology by
2030. Arti cial Intelligence based technologies has the potential to deliver
additional global economic activity of around $13 trillion by 2030, or
about 16 percent higher cumulative GDP compared with today.
The impact of arti cial intelligence might not be linear but could build
up at an exponential pace over time. On the negative side, arti cial
intelligence will widen the gaps between countries, companies, and
workers. China and the US would be top positioned and would face AI
war for years to come. Bene ts of arti cial intelligence will be
distributed inappropriately.
On a much larger scale, Arti cial intelligence enabled radical growth
will going to change how humanity thinks about the role of culture,
god, faith, reality and ourselves. The ultimate aim of arti cial
intelligence research is a technological singularity- the point at which
technology overtakes the human. What it will bring and how it will
transform it we won’t realize until it’s arrived.
Machines will become excessively successful at persuasion and can
drive humanity to a common goal or it can formulate its own long-term
goal that does not act in accordance with human values.
Great power comes with great responsibility. The
prospect of arti cial intelligence with superhuman
intelligence and superhuman abilities presents us
with the extraordinary challenge—how to deal with
biases and ethical issues?
We don’t know the 🔗ultimate goal of arti cial intelligence but the
sure thing is that AI is going to be one of the most competitive bene ts
in the business in the near future and each organization should have a
plan, not to just apply arti cial intelligence, but to continuously think,
adapt and innovate how arti cial intelligence can help in the journey.

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