Why Fresh Graduates Struggle to Match AI Job Needs in India

Every year, India produces lakhs of engineering graduates. But when it comes to landing jobs in Artificial Intelligence (AI), Data Science, and Machine Learning (ML), only a small fraction are truly job-ready.

The reason is simple: a gap between classroom learning and industry demands.

AI is moving at lightning speed. New tools and frameworks arrive every few months, while traditional college curricula often take years to update. This leaves fresh graduates with plenty of theory but very little practical experience.

As Anshuman Singh, Co-Founder of Scaler & Scaler School of Technology (SST), explains:

“AI is no longer futuristic, it’s already a super-assistant in the workplace. To stay relevant, professionals must stay a step ahead of AI, guide it with precision, and translate it into real business value.”

What Students Really Need to Succeed

If graduates want to make a mark in AI and ML careers, they need more than just degrees. Singh points out three essentials:

• Strong foundations in maths, problem-solving, and data structures.
• Hands-on experience with the latest tools and frameworks.
• Adaptability, because AI keeps changing, and so must the learner.

At SST, the curriculum is built with inputs from over 100 industry leaders at companies like Amazon, Google, and Uber. This means students aren’t stuck with outdated textbooks—they learn with the same tools shaping the future of work.

The results speak for themselves. The first batch of SST students, now in their second year, achieved a 96.3% internship placement rate across 96 companies. The highest stipend? A staggering ₹2,00,070 per month.

Why the Curriculum Gap Still Exists

The truth is, AI evolves every six months—but university syllabuses take years to change. Academic rules are designed for stability, not speed.

This is why many graduates have theoretical knowledge but struggle with execution. They know the concepts but can’t always apply them to real-world problems.

At SST, students are trained differently. They:

• Debug real machine learning models under strict deadlines.
• Deploy AI systems at scale.
• Optimise pipelines for cost and performance.

By the time they graduate, they already know how to work in an industry environment.

Making Graduates Future-Ready

Preparing graduates for tomorrow’s tech jobs requires teamwork between academia, industry, and government.

• Colleges need to bring real-world projects and tools into the classroom.
• Companies must provide more internships, mentorships, and apprenticeships.
• Governments can help by recognising industry-led training and incentivising digital upskilling.

At SST, courses are co-designed with practitioners. This ensures students graduate with experience solving the same problems companies are struggling with today.

The Skills Companies Value the Most

Employers hiring for AI and ML roles are clear about what they want:

• Ability to execute on modern tech stacks.
• Problem-solving under tight deadlines.
• Collaboration and communication in teams.
• Quick adaptability to learn new tools.

As Singh puts it:

“Being able to debug a machine learning model in production or optimise a pipeline for cost and speed is just as valuable as theoretical knowledge.”

Final Thoughts

The AI revolution is already here. To thrive, students need more than just a degree—they need practical skills, industry exposure, and the mindset to keep learning.

With industry-integrated programmes, shared responsibility from colleges, companies, and governments, and a strong focus on execution, India’s graduates can be truly future-ready in AI and beyond.

Students can now turn ideas into apps just by describing them—AI writes the code!
Read more 👉 https://krsyara.com/vibe-coding-the-new-ai-trend-thats-changing-how-students-build-apps/