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 .
Tech Roles Facing Significant Challenges
1. Basic Software
Testing
2. Traditional Data
Analysis
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.
3. Basic
Programming and
Web Development
4. IT Support (Level 1)
5. Basic Content
Management
While some roles are challenged,
many tech careers are not just
surviving, they are thriving in the
age of AI. These jobs tend to involve
higher order thinking skills,
creativity, or specific knowledge
base that is enhanced, not
replaced by AI.
Tech Careers
Thriving in the AI Era
The Transformation
of Traditional Roles
Many classic tech jobs are
not vanishing but
changing evolutionarily.
Software Development
From: Code line by line through keyboard
commands on a laptop to: Architectural thinking,
prompt engineering, and working with AI pair
programming.
1. AI Specialists and Engineers
2. Advanced Data Scientists
3. Cloud Architecture Specialists
4. Cybersecurity Experts
5. UX/UI Designers with Research
Focus
6. DevOps and site reliability
Engineers
7. Technical Depth Product
Managers
8. ML Operations (MLOps)
Specialists
Quality Assurance
From: Executing manual testing and basic test
automation, to: Designing testing strategies,
exploratory testing, and managing AI-powered test
suites.
Systems Administration
From: Manually configuring and troubleshooting
systems, to: Infrastructure as code, exception
handling, and policy design.
From: Manually configuring and troubleshooting
systems, to: Infrastructure as code, exception
handling, and policy design.
Technical Writing
How Students and
Professionals Can Prepare
To create a career that will weather the
storms of change, you need to build skills
and practices that will augment, but not
compete with, AI:
1. Build T-Shaped Skillsets
You need the depth of knowledge in one area, but also breadth of
knowledge in parallel areas of relevance. This ability to be versatile is
crucial as technology develops.
2. Develop Human Skills
Develop skills that AI cannot, including creativity, ethics, empathy,
communication and collaboration, leadership and complex problem-
solving.
3. Learn How to Work with AI
The most successful people will be those with the ability to work
alongside AI tools, knowing what the tools can do and what they cannot.
4. Create Cross-Domain Knowledge
There are enormous new values available to professionals who can
integrate technological knowledge with sectors such as health, finance,
education, sustainability, etc. They hold a key zone of value that distinct
technologist do not.
5. Build Continual Learning
The half-life of any technical knowledge is getting shorter, we need to
establish habits and systems of continual skill development, not focus on
static knowledge.
6. Focus on Outcomes Versus Activities
As AI will automate more and more tasks, the value it creates will shift to
outcomes and solutioning problems, not task based activities.
CASE STUDY 2: THE RISE OF THE DATA
ANALYST
Maya started her career running SQL
queries and creating basic dashboards.
As these tasks became easier due to
automation, she began to invest time
learning causal inference, experimental
design, and thinking through business
strategy. Today, she is a decision scientist
who looks at the “why” behind data, and
has abstracted her analyses to allow
business strategy decisions to be made.
CASE STUDY 1: THE NEW SOFTWARE
DEVELOPER
Real-World Examples of
Evolution and
Adaptation
Five years ago, Alex had a job title of full-
stack developer, and a majority of his day was
spent writing code. Today he may still have a
job title of full-stack developer, but the
nature of his job has changed. He spends a
lot more time defining problems clearly,
architecting designs, and enlisting the help of
AI assisted coding programs. His productivity
increase has improved 5 fold, which has
allowed him to take on even more ambitious
projects.
EDUCATIONAL PATHWAYS FORWARD
1.Practical application over theoretical
knowledge — Students work on real-world
projects that demonstrate the practical
application of AI technologies
2.Collaborative problem-solving — Learning to
work in diverse teams that reflect modern
workplace environments
3.Ethical considerations — Understanding the
social implications and responsible use of
emerging technologies
4.Adaptability and learning methodologies —
Teaching students how to learn continuously
throughout their careers
Our graduates don’t just learn current
technologies; they develop the adaptability and
critical thinking needed to evolve alongside
technology throughout their careers.
Finding the right educational partner is essential in this changing
landscape. The best EdTech companies offer programs that prepare
students for the future of work, not just for today’s job market.
At Pedestal Techno World, our curriculum focuses on building
adaptable skills through immersive learning experiences. Our AI
training courses are designed with future-readiness in mind,
emphasizing:
The Human-AI Partnership
The most productive vision of the future isn’t one where AI replaces
humans but where human-AI partnerships achieve outcomes neither
could reach alone. We’re entering an era where the most valuable
technical professionals will be those who effectively:
Identify appropriate uses for AI tools
Communicate effectively with AI systems through well-crafted
prompts and interactions
Verify and improve AI outputs
Focus their human creativity and problem-solving on areas where AI
falls short
Design systems where humans and AI work together seamlessly
While AI will certainly transform the tech industry, this
transformation creates as many opportunities as
challenges. By developing the right skills and mindset,
today’s students and professionals can position
themselves for careers that evolve alongside AI rather
than being replaced by it.
The tech roles of tomorrow may have different titles and
responsibilities than those of today, but the need for
human creativity, ethical judgment and interpersonal
collaboration will remain. The most successful tech
professionals won’t be those who avoided AI’s impact
but those who embraced it as a powerful collaborator in
solving humanity’s most pressing challenges.
A word from me
Conclusion: Adaptation,
Not Extinction
www.pedestaltechnoworld.com
9929934909
info@pedestaltechnoworld.com
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