Here’s what the numbers are screaming, minus the drama: by October 1, 2025, global tech layoffs have crossed 180,094 people. The biggest knives this year? Intel, Microsoft, and TCS. That’s not rumor-mill gossip—it’s backed by public trackers and mainstream reporting.

If you work in tech in India, or your team sells to tech, this matters. Not because “tech is dying” (it isn’t), but because the industry is shedding low-leverage roles and doubling down on AI, data, security, and cloud economics. The story is less apocalypse, more rebalancing—with a lot of pain in the middle.

The scoreboard (so far)

·    Global tally: 180,094 tech roles cut as of Oct 1. That figure aggregates big-ticket reductions from Intel, Microsoft, and TCS, among others.

·    Microsoft: Multiple rounds since May—6,000 in May alone, with local filings and reports pointing to ~15,000 cuts across the U.S. so far in 2025. Engineering-heavy roles took a hit; gaming and Copilot/Windows orgs saw restructuring.

·    Intel: A sweeping reset through 2025, widely reported as ~24–25k roles in play as part of a deep restructuring and cost discipline push.

·    TCS: India’s bellwether cut ~12,000 roles (~2% of workforce) with tiered severance—sparking tough questions on skills and redeployment. Also, there are very real tax implications on severance Indian employees should factor in.

Trackers vary on totals (they always do), but the direction is consistent: 2025 is another heavy layoff year, with dozens of fresh entries every month.

The why (the blunt version)

Companies aren’t allergic to people; they’re allergic to costs without clear ROI. Three forces are doing the heavy lifting:

1.  AI-first allocation: Budgets are migrating from generalist headcount to GPUs, data centers, and AI platform talent. That means cutting middle layers and consolidating overlapping teams while still hiring aggressively for AI/ML, data, and platform reliability. Microsoft’s cadence is the most visible example.

2.  Capex shock + margin math: Chipmakers and hyperscalers are staring at capex bills that look like small-country GDPs. If the revenue ramp lags the spend, headcount gets “optimized.” Intel’s restructuring is exhibit A.

3.  Demand normalization: The post-pandemic sugar high is over. Sales/CS and mid-level IC roles that thrived on expansionary budgets are being trimmed as companies return to saner growth. Layoff trackers across the U.S. and EU show the pattern.

What this means for India (and you)

India’s IT and GCC ecosystem sits right where the tectonic plates meet: plenty of delivery work, rising AI mandates from clients, and thin margins. The TCS move isn’t an outlier; it’s a message: reskill or get resized. If your role depends on manual glue work, repetitive ops, or “owning the process” rather than automating it, the clock is ticking.

Where the hiring is still hot (and will likely stay that way):

·    AI & Data: MLEs, data engineers, platform/infra folks who can ship production-grade models and pipelines (not just notebooks).

·    Cybersecurity: Identity, cloud security, and AI safety—board-level priorities.

·    FinOps / Cloud cost engineering: Anyone who can cut a seven-figure cloud bill without breaking SLAs.

·    Product+Platform fusion roles: PMs and architects who can translate model capabilities into reliable features and measurable revenue.

A brutally practical playbook (Indian context)

1) Convert “experience” into outcomes. Most resumes list responsibilities. Hiring managers want impact. Rewrite bullets as: problem → action → quantifiable result. (If it’s not measured, it didn’t happen.)

2) Become expensive to fire. Pick one revenue-facing or cost-killing competency and go deep:

·    FinOps (AWS/GCP/Azure cost levers),

·    Retrieval + evaluation pipelines (LLM apps with guardrails),

·    Observability + SRE for AI workloads (latency, drift, hallucination metrics),

·    Data quality engineering (contracts, lineage, SLAs).

3) Get AI-native, not just AI-adjacent. If you’re in testing, CS, marketing, or finance ops—learn to automate your own work with internal LLMs, agentic workflows, and RAG. The safest roles own the automation. (Borrow a sandbox and start with one reliable workflow win.)

4) Hedge with credentials that travel. For Indian candidates eyeing global roles: stack one vendor cert (say, Azure AI Engineer) with one open credential (Kubernetes, CNCF data/ML tracks). Pair it with a public repo showing a small, productionized AI feature (tests + telemetry + cost notes).

5) Cashflow reality check. If you’re on a bench or at a shaky org, build a 6–9 month runway. Indian severance is taxable and has caveats—don’t sign anything blind. Talk to a CA; read the fine print.

6) Network like it’s your job (because it is). Two targeted referrals beat 200 generic applications. Aim for teams shipping AI features customers actually pay for.

Final word

No, tech isn’t dying. It’s editing itself. The market is voting for people who can ship AI-infused, cost-aware, resilient systems. If your current job is mostly status updates and spreadsheet wrangling, consider this your nudge. The future is hiring—just not evenly.

Sources

Key figures and developments were verified from:

·    Global 2025 layoff total and top cutters (as of Oct 1): Gulf News.

·    Microsoft 2025 cuts: The Verge (6,000 in May); KIRO7 (≈15,000 YTD via filings); engineering impact: The Register; org areas hit: CRN.

·    Intel 2025 restructuring scale: Yahoo Finance / Fortune coverage; Intellizence summary.

·    TCS layoffs and severance structure; tax treatment of severance in India.

·    Broader tracker context: TrueUp, Channel Futures roundup.