AI/ML Hiring Is Up 20%, but IT Hiring Is Down 4%. Is an AI Career the Smarter Choice?

September’s hiring data points to a shift towards specialised skills, but one month of growth is not a guarantee of job security.

Imagine choosing between two job paths: one sits inside a sector where hiring is down, while the other is seeing a sharp rise in demand. That is the contrast in India’s September white-collar hiring data: AI/ML roles grew 20% year on year, even as IT/Software Services hiring fell 4%. It makes an AI career worth a closer look. But the numbers do not mean every AI job is safe, or that traditional IT skills no longer matter.

THE BIG TAKEAWAY

AI/ML demand is growing faster than the wider hiring market, including within IT. The smarter choice is to build AI skills on top of strong technical fundamentals, rather than treating AI as a shortcut to a job.

What does the September hiring data actually say?

KEY TAKEAWAY
AI/ML is growing in a mostly steady market, but the 20% headline and the 11% figure within IT measure different things.

The Naukri JobSpeak Index put overall white-collar hiring at 3,053 in September, up 2% from 3,002 a year earlier. AI/ML roles rose 20% year on year, while IT/Software Services hiring declined 4%. Within IT itself, AI/ML hiring grew 11%. These figures show that AI-related hiring is holding up better than broader IT demand, though they are not a direct count of vacancies or a guarantee of future growth.

Does the data mean AI is a safer career than traditional IT?

KEY TAKEAWAY
The data supports stronger current demand for AI/ML, not a blanket conclusion that AI jobs are safer than all IT jobs.

Hiring is shifting towards specialised capabilities. Info Edge MD and CEO Hitesh Oberoi described September’s market as steady but more selective, with demand moving towards specialised skills, particularly AI, and experienced professionals.

That matters for career planning, but there are limits to what a monthly index can tell you. It doesn't reveal how many roles are permanent, how competitive each opening is, what salaries employers offer, or how long demand will last. AI/ML hiring is also not limited to people with “AI” in their job title: software, data, cloud, cybersecurity and product teams may all use AI-related skills.

A USEFUL WAY TO READ THE SIGNAL
Treat AI as a growing opportunity, not a replacement for programming, data handling, problem-solving, or domain knowledge.

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Who is seeing the strongest AI/ML demand?

KEY TAKEAWAY
Experience still matters, but September’s data also showed growth in fresher AI/ML hiring.

The AI/ML experience breakdown is a useful reminder that employers are not hiring only senior specialists:

• 13–16 years of experience: AI/ML hiring grew 54% year on year.

• 8–12 years: hiring grew 28%.

• Freshers: hiring grew 19%.

• 4–7 years: hiring remained stable.

The strongest growth was among experienced professionals, which may reflect demand for people who can apply AI to real business problems, assess outputs and make technical or product decisions. 

Fresher growth is encouraging, but it does not mean entry-level opportunities are abundant or easy to secure.

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What should you learn if you want to enter AI?

KEY TAKEAWAY
Build a foundation first, then add practical AI skills and evidence that you can use them.

A sensible starting point is to choose skills based on the kind of role you want, rather than collecting AI tools or certificates without a clear goal.

1. For AI/ML or data roles: learn Python, statistics, data preparation, model evaluation and the basics of machine learning. Practise explaining why a model works and where it can fail.

2. For software roles: strengthen programming, APIs, databases, testing and system design, then learn how to integrate AI models into useful applications.

3. For business or marketing roles: learn to use AI tools responsibly, evaluate outputs, work with data and measure whether an AI-assisted workflow improves results.

Projects matter because they show how you apply what you learn. Build something small, document your decisions, test it, and be ready to discuss its limitations. Also check job descriptions in your target city and role: employer requirements can differ significantly.

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So, is an AI career the smarter choice?

KEY TAKEAWAY
For someone interested in the work and willing to build the foundations, AI is a promising direction. The smartest move is to add AI capability to a durable skill set, not to chase the 20% figure alone.

September’s numbers make a credible case for paying attention to AI/ML: hiring rose 20% overall and 11% within IT while the broader IT/Software Services category fell 4%. Yet career decisions need more than a monthly trend. Look at the roles you want, the skills they repeatedly ask for, your interest in the work, and the quality of projects or experience you can build.

AI may be the smarter choice for some candidates, but it is not automatically the best choice for everyone. A strong software engineer, data analyst or domain specialist who can use AI well may be better positioned than someone who knows AI tools but lacks the fundamentals.