If you're scanning the overall hiring numbers and wondering why the job market feels slower than the AI headlines suggest, the latest data from Naukri's JobSpeak Index explains the gap. In September 2026, the index — which tracks white-collar job postings across India — stood at 3,053 points, up just 2% year-over-year from 3,002 in September 2025. That's a modest, almost flat, overall growth rate. But within that same data set, AI and machine-learning job postings grew 20% year-over-year, by far the fastest-growing category tracked.

A month earlier told a similar story, at a bigger scale

August 2026's index reading was 3,028, up from 2,664 a year earlier — a 14% year-over-year jump, led by hiring in auto, healthcare, and retail. Zooming out further, fiscal year 2026 (April 2025 to March 2026) closed with 8% annual hiring growth overall. Put together, the picture is one of a labor market growing steadily but unevenly: healthy in aggregate, but with AI/ML roles consistently outrunning every other category by a wide margin.

It's not unique to India

A similar pattern shows up globally. DataCamp's State of AI Careers 2026 report, which analyzed more than 2 million deduplicated job postings across 85 regions from January 2024 through April 2026, found that data and AI hiring grew 80.2% year-over-year — a far steeper curve than the broader job market in nearly every region studied. The report's framing is worth noting: it argues automation is primarily hitting specific tasks within roles, rather than eliminating whole job categories outright, which helps explain why AI-adjacent hiring and overall workforce disruption can both be rising at the same time without one simply canceling out the other.

What this means if you're job hunting

• If your current role touches data, analytics, or software development, even informally, highlighting any AI/ML-adjacent work — model evaluation, prompt engineering, data pipeline work, automation scripting — is worth foregrounding on your resume right now, given where the actual postings growth is concentrated.
• Sector matters as much as skill: auto, healthcare, and retail were called out specifically as hiring leaders in August's data, so if you're in one of those industries, the broader demand may already be working in your favor.
• A flat-looking headline hiring number doesn't mean a flat market everywhere — it usually means growth is concentrated in fewer categories, and AI/ML is currently the clearest one of those categories in India's data.

The takeaway isn't that every job seeker needs to become a machine learning engineer. It's that the categories absorbing hiring growth right now are identifiable in the data, and tailoring where you apply — and how you frame existing experience — to match them is a reasonable, evidence-backed strategy rather than a guess.