AI Job Replacement: Which Tech Roles Will Survive?

AI Job
Replacement:
Which Tech
Roles Will
Survive?

In an ever-evolving technological environment, artificial
intelligence has become a tool in the marketplace, along with a
threat to traditional tech careers. As students preparing to enter
the workforce, or professionals considering a career change,
we need to determine which roles will evolve or emerge, along
with roles that may cease to exist. We are committed to
ensuring that you are empowered to navigate this dynamic tech
environment at Pedestal Techno World, best edtech company .

The AI Revolution:
What does it really
mean?
While there are alarming
headlines about AI taking
the place of human
workers, the reality is
ultimately much more
nuanced and complex. For
example, some repetitive
tech roles will face
massive disruption, but at
the same time, AI is
creating entirely new
opportunities and
augmenting existing roles
and jobs in ways we barely
even imagined just a few
short years ago.
This transformation is
not so much about
replacement as it is
about evolution—a
fundamental change in
our outlook on how we
do technical work,
along with the skills
required and which
skills we are
anticipating will matter
and be most important
in the not so far future.
Let’s explore this
together.

Tech Roles Facing
Significant
Challenges
1. Basic Software Testing
The traditional role of a manual software
tester, which focused strictly on
executing the same repetitious tests
repeatedly, is being replaced with many
opportunities for automation. New AI
software testing tools can execute
thousands of test cases in minutes,
extract relevant test results and even
self-heal broken tests. Testers will
increasingly find that jobs that involve
blind repetition of executing pre-defined
test scripts, without offering strategic
insights reflecting good testing practice,
will gradually dissipate.
Impact:
Companies that once employed
scores of low-level manual
testers are now relying on fewer
specialist test roles bucked by
decisions around usage of AI
tools.

2. Traditional Data Analysis
The AI tooling of today are getting
better and faster at processing,
cleaning and visualizing data. The
days of data producers only
gathering basic insights through
simple reporting are nearly gone.
Modern business intelligence
platforms use AI to automatically
create the same deep data insights
that once took a rigourous human
data analyst to assemble and
produce.
Entry-level data analysis roles are
becoming more sophisticated, with
underlying expectations that those
commencing in these roles will be
attaching data analysis skills
beyond simple reporting.
Impact