The headlines were stark: 25,000-30,000 jobs cut across TCS, Infosys, and Wipro in 2025. But buried beneath the layoff numbers is a more nuanced story. Fresher hiring is recovering to 82,000 in FY2026. AI, cloud, and cybersecurity roles are up 45%. The skill gap has widened from 18% to 25%. India's IT industry isn't dying—it's transforming. Here's what you need to know to navigate the transition.
The 2025 Reality Check
The Layoff Numbers
| Company | 2025 Layoffs | % of Workforce |
|---|
| TCS | ~12,000 | 2% |
| Infosys | ~8,000 | 2.5% |
| Wipro | ~5,000 | 2% |
| Tech Mahindra | ~3,000 | 2% |
| HCL Tech | ~2,000 | 1% |
| Total | ~30,000 | ~2% |
What's Being Cut
Not all roles faced equal risk:
| Role Category | Risk Level | Primary Driver |
|---|
| BPO/Call center | Critical | AI chatbots, voice automation |
| Manual testing | Critical | AI-powered testing tools |
| L1/L2 support | High | Automated incident management |
| Junior development | High | AI code generation |
| Bench resources | High | Utilization optimization |
| Mid-level management | Medium | Flattening structures |
What's Being Hired
Simultaneously, demand surged in other areas:
| Role Category | YoY Growth | Average CTC Increase |
|---|
| AI/ML Engineers | +67% | +35% |
| Cloud Architects | +45% | +28% |
| Cybersecurity | +52% | +30% |
| DevOps/SRE | +38% | +22% |
| Data Engineers | +41% | +25% |
| Full-stack (AI-enabled) | +35% | +20% |
The Skill Gap Crisis
The Numbers
| Year | Skill Gap | Definition |
|---|
| 2023 | 18% | Workers lacking skills for current roles |
| 2024 | 22% |
| 2025 | 25% |
| 2026 (projected) | 28-30% |
: 1 in 4 IT workers lacks the skills their current role demands.
Skills in Deficit
| Skill | Demand vs. Supply Gap |
|---|
| Generative AI/LLMs | 4:1 |
| Cloud-native development | 3:1 |
| Kubernetes/Container orchestration | 3:1 |
| AI/ML Operations (MLOps) | 5:1 |
| Cybersecurity (AI-aware) | 4:1 |
| Data Engineering (modern stack) | 3:1 |
Skills in Surplus
| Skill | Supply vs. Demand Ratio |
|---|
| Manual testing | 2:1 surplus |
| Basic Java/.NET maintenance | 1.5:1 surplus |
| Traditional DBA (non-cloud) | 1.5:1 surplus |
| Basic tech support | 2:1 surplus |
The Fresher Paradox
Hiring Is Recovering
| Fiscal Year | Fresher Hiring (Top 4) | Change |
|---|
| FY2022 | 225,000 | (Peak) |
| FY2023 | 110,000 | -51% |
| FY2024 | 60,000 | -45% |
| FY2025 | 45,000 | -25% |
| FY2026 | 82,000 | +82% |
But the Bar Is Higher
The freshers being hired are different:
| Old Hiring Criteria | New Hiring Criteria |
|---|
| Engineering degree | Engineering + AI/ML coursework |
| Basic coding ability | Proven project portfolio |
| Aptitude test scores | Hackathon/competition wins |
| Mass campus recruitment | Selective, skill-based hiring |
Package Bifurcation
| Category | Package Range | Notes |
|---|
| Standard fresher | Rs. 3.6-4.5 LPA | Mass hiring roles |
| AI-skilled fresher | Rs. 8-12 LPA | Specialized roles |
| Top-tier (IIT/NIT + AI) | Rs. 15-25 LPA | Premium placements |
| Super-specialists | Rs. 25-50 LPA | Rare, exceptional talent |
: The same graduating class sees 7x package differences based on AI skills.
Company Strategies
TCS
Approach: Massive internal reskilling
| Initiative | Details |
|---|
| AI training | 350,000 employees trained in AI/ML |
| ignio | AI platform for IT operations |
| GenAI agents | 150+ purpose-built AI agents |
: Reduce fresher intake, upskill existing workforce
Infosys
Approach: GenAI-first transformation
| Initiative | Details |
|---|
| Topaz | AI-first platform across services |
| GenAI projects | 75% YoY growth |
| AI co-pilots | Deployed across delivery |
: Selective fresher hiring, aggressive lateral AI hires
Wipro
Approach: AI360 commitment
| Initiative | Details |
|---|
| AI360 | $1 billion AI investment program |
| NVIDIA partnership | AI infrastructure development |
| Reskilling | 200,000 employees targeted |
: Net negative headcount, AI-focused additions
The New IT Career Playbook
For Freshers
Reality check: The path that worked for previous generations (mass recruitment → 3 years experience → lateral moves) is closing.
What works now:
- Build before you graduate
- GitHub portfolio with AI projects
- Contributions to open-source
- Kaggle/competition rankings
- Get certified strategically
- AWS/Azure/GCP cloud certifications
- Google/Microsoft AI certifications
- Not just accumulating certs—demonstrating projects
- Target GCCs, not just IT services
- GCCs now account for 27% of IT hiring
- Higher packages, more innovative work
- Direct exposure to global enterprises
- Consider tier-2 cities
- Hyderabad, Pune, Chennai have growing AI ecosystems
- Lower cost of living, improving opportunities
For Mid-Career Professionals (5-15 years)
The squeeze: This cohort faces the toughest transition. Too experienced for fresher roles, too expensive for companies cutting costs, and often lacking cutting-edge skills.
Survival strategy:
- Aggressive upskilling (not casual learning)
- 10-15 hours/week minimum
- Structured programs, not just YouTube
- Build demonstrable projects
- Domain + AI combination
- BFSI + AI = Premium compensation
- Healthcare + AI = Growing demand
- Manufacturing + AI = Underserved niche
- Consider the GCC path
- GCC hiring for experienced professionals is strong
- Transfer internal IT skills to captive centers
- Consulting/advisory pivot
- AI transformation consulting is booming
- Experience + new skills = high value
For Senior Professionals (15+ years)
The opportunity: Leadership roles in AI transformation are undersupplied.
Positioning strategy:
- Become the AI transformation leader
- Understand AI at strategic level (not just tactical)
- Lead reskilling initiatives
- Bridge technology and business
- Advisory and board roles
- AI governance expertise is rare
- Companies need experienced leaders who understand AI
- Startup ecosystem
- Angel investing in AI startups
- Advisory roles combining domain + AI strategy
Reskilling: What Actually Works
The 40-Hour Problem
Most IT workers spend fewer than 40 hours annually on upskilling. This is catastrophically insufficient.
Benchmark for relevance:
- Minimum: 200 hours/year (4 hours/week)
- Competitive: 400 hours/year (8 hours/week)
- Transformational: 600+ hours/year (12 hours/week)
Effective vs. Ineffective Learning
| Ineffective | Effective |
|---|
| Watching tutorials passively | Building projects |
| Accumulating certificates | Applying knowledge |
| Learning in isolation | Learning in communities |
| Breadth without depth | T-shaped skills |
| Theoretical understanding | Hands-on implementation |
Recommended Learning Paths
Path 1: AI/ML Engineering (600 hours)
text
Months 1-3: Python + ML fundamentals
Months 4-6: Deep learning + PyTorch/TensorFlow
Months 7-9: LLMs + Generative AI
Months 10-12: MLOps + production deployment
(500 hours)
text
Months 1-3: AWS/Azure/GCP fundamentals
Months 4-6: Cloud-native development
Months 7-9: AI services integration
Months 10-12: Solutions architecture
(500 hours)
text
Months 1-3: Modern SQL + Python
Months 4-6: Spark + distributed computing
Months 7-9: Data pipelines + orchestration
Months 10-12: AI data infrastructure
The GCC Alternative
Why GCCs Are Winning
| Factor | IT Services | GCCs |
|---|
| Hiring share | 73% → declining | 27% → growing |
| Avg. package | Rs. 8-15 LPA | Rs. 12-25 LPA |
| Innovation exposure | Client-dependent | Core business |
| Job security | Project-based | More stable |
| Career growth | Pyramid structure | Flatter, merit-based |
Top GCC Employers for AI Roles
| Company | AI Focus | Hiring Volume |
|---|
| JP Morgan | Risk analytics, fraud detection | High |
| Google | Core AI research, products | Medium-High |
| Microsoft | Azure AI, Copilot | High |
| Goldman Sachs | Trading AI, automation | Medium |
| Amazon | AWS AI, Alexa, logistics | High |
| Walmart | Supply chain AI | Medium |
How to Get In
- Referrals matter more than ever
- Technical interviews are harder (LeetCode + system design + AI knowledge)
- Domain expertise valued (especially finance, healthcare)
- Communication skills critical (direct interaction with global teams)
Industry Outlook: 2026-2028
Employment Projections
| Scenario | Net IT Jobs by 2028 |
|---|
| Pessimistic | -5% (250K net loss) |
| Base case | +3% (150K net gain) |
| Optimistic | +8% (400K net gain) |
: Total jobs may grow, but distribution shifts dramatically toward AI-enabled roles.
Compensation Trends
| Role Type | 2026-2028 Trajectory |
|---|
| AI specialists | +15-25% annually |
| Cloud/DevOps | +10-15% annually |
| Traditional IT | +0-5% annually |
| Legacy maintenance | Flat to declining |
Action Plan by Timeline
This Month
- [ ] Assess current skills vs. market demand
- [ ] Identify 1-2 high-demand areas to pursue
- [ ] Commit to learning schedule (hours/week)
This Quarter
- [ ] Complete one foundational certification
- [ ] Build one demonstrable project
- [ ] Update LinkedIn/resume with new skills
This Year
- [ ] Achieve proficiency in new domain
- [ ] Contribute to open-source/community
- [ ] Secure role that applies new skills (internal or external)
Conclusion
The 25,000 layoffs in 2025 aren't the end of India's IT industry—they're the painful middle of a transformation. The companies laying off workers are simultaneously hiring for AI roles at premium salaries. The skill gap isn't closing because too few professionals are reskilling at the pace the market demands.
For individuals, the message is stark but actionable: the 40-hour-a-year learning approach is no longer viable. Those who invest 200-400+ hours annually in AI, cloud, and modern development skills will find abundant opportunities. Those who don't will face continued pressure.
The IT industry that emerges from this transition will be smaller in traditional roles but larger in value creation. The question isn't whether you'll be part of it—it's what role you'll play.
The reskilling window is now. It won't stay open forever.
Sources:
- Business Standard (Tech Layoffs 2025)
- CNBC (India IT Layoffs Analysis)
- Taggd IT Hiring Trends
- NASSCOM Industry Reports
- Company quarterly earnings reports