Will AI Replace Your Job? I Built a Calculator to Find Out

Every conversation I have with engineers in 2026 eventually reaches the same question: "Is my job safe from AI?"

The internet is full of hot takes. Tech influencers tell you AI will replace everyone. Enterprise executives tell you AI is just a productivity tool. Neither view is useful when you're an Indian Project Manager with 8 years of experience trying to decide whether to upskill, pivot, or stay the course.

So I built a calculator. Not a clickbait quiz — a transparent scoring framework backed by published research. You can try it here, and this post explains exactly how it works so you can decide whether to trust the output.

Why a Framework Beats a Prediction

Nobody can predict which specific jobs will exist in 2030. What we can do is identify the factors that increase or decrease displacement risk, weight them based on research, and produce a relative score.

The goal isn't to tell you "you'll lose your job in 18 months." The goal is to tell you:

• Which parts of your current role are most automatable
• How your score compares to the average for your role
• What specific actions would reduce your risk

That's the difference between fortune telling and career planning.

The Six Factors

The calculator combines six weighted factors:

1. Role Base Risk (40% of the score)

Every role has a base risk score derived from a blend of WEF Future of Jobs 2025, NASSCOM Strategic Review 2026, and McKinsey's State of AI 2026. The scores range from 10 (CTO, ML Engineer) to 75 (Manual QA Tester).

Why this matters for Indian developers: I deliberately included roles that are ubiquitous in the Indian IT industry but rarely represented in US-centric analyses. Project Managers (base risk: 50), Business Analysts (55), Scrum Masters (55), Delivery Managers (45), and Technical Writers (70) all get explicit treatment. If you've ever felt like global AI displacement reports don't capture your reality, this is why.

2. Work Composition (25% of the score)

This is the factor most calculators get wrong. They treat "Project Manager" as one thing — but a PM who spends 70% of their week on status reports and stakeholder coordination has a very different risk profile than one who spends 70% on strategic planning and technical decision-making.

The calculator asks you to break your week into four categories:

• Technical work (coding, design, architecture) — reduces risk
• People management (1:1s, coaching, hiring) — reduces risk
• Clerical work (status reports, meetings, docs) — increases risk
• Strategic decisions (prioritization, trade-offs) — reduces risk

The more clerical your week, the higher your score. This is the single most actionable insight — you can't easily change your role overnight, but you can change what you spend your time on.

3. Experience (15% of the score)

Experience reduces risk, but not linearly:

• 0-2 years: +12 risk (most automatable)
• 3-5 years: +4 risk
• 6-10 years: -4 risk
• 10-15 years: -10 risk
• 15+ years: -15 risk

The logic: AI is great at replicating patterns that exist in training data. Junior work follows well-documented patterns. Senior work involves judgment, context, and tradeoffs that don't fit neatly into training sets.

This doesn't mean juniors should panic — it means juniors need to move up the value chain faster than previous generations did. The traditional "learn the basics for 2 years" approach is no longer enough.

4. AI Skills & Adaptation (20% of the score)

Every AI skill you've picked up reduces your risk, because the people using AI aren't being replaced — they're multiplying. The calculator gives reductions for:

• Daily use of AI coding/writing tools (−8)
• Having built something with LLM APIs (−6)
• Understanding RAG, fine-tuning, or prompt engineering (−6)
• Having deployed AI features to production (−8)
• Being active in AI community (−4)
• Leading AI adoption at work (−6)

If you check all six, that's a 38-point reduction — enough to move most roles from "High Risk" to "Moderate" or "Low."

5. Technical Depth

The calculator asks: does your technical work involve implementing well-known patterns, a mix, or novel problems with little precedent?

• Known patterns: +5 risk
• Mixed: neutral
• Novel problems: −8 risk

Novel problem-solving is expensive to train AI on because there's less pattern data. If you're the person your team asks when the docs don't have the answer, you're in the protected category.

6. Industry Context

Regulated industries slow AI adoption (healthcare, legal, finance → risk reduction). Commodity services accelerate it (BPO, outsourcing → risk increase). Your industry is a 3-5 point modifier, not a make-or-break factor.

What the Output Looks Like

Your score (0-100) maps to four tiers:

Alongside the score, you get:

• A breakdown showing exactly how each factor contributed
• A comparison bar showing your score versus the average for your role
• 3-5 personalized recommendations with links to specific guides and tools

Real Examples I Tested

I sanity-checked the calculator against realistic profiles:

"Rakesh" — Manual QA Tester, 1 year, 60% clerical, no AI skills, BPO → Score: ~88 (Critical) → Recommendation: Transition to Automation QA immediately "Priya" — Project Manager (Indian IT services), 8 years, 50% clerical, no AI skills → Score: ~62 (High) → Recommendation: Pivot toward Technical Program Management "Arjun" — Engineering Manager, 15 years, 20% tech + 60% management, uses AI daily → Score: ~12 (Low) → Recommendation: Lead AI adoption on your team "Meera" — Frontend Developer, 3 years, mixed work, uses Copilot daily → Score: ~38 (Moderate) → Recommendation: Build something with LLM APIs

The scores align with what I'd intuitively expect based on my experience managing teams through the last three years of AI adoption.

Limitations I Want to Be Honest About

This is a framework, not a prediction. Here's what it doesn't capture:

Macro-economic shifts. If there's a major recession or a regulatory crackdown on AI, all bets are off. The calculator assumes the current trajectory continues. Company-specific factors. Your employer matters. Working for a product company with strong AI strategy is safer than working for a services firm that's still debating whether to adopt Copilot. Geographic nuances. A senior engineer in Bangalore faces different pressures than one in San Francisco. The calculator uses global data with India-specific role weights, but it can't fully capture your local market. Your personal agency. The biggest factor in whether AI replaces you is what you do in the next 12 months. No calculator captures that.

Use the score as a starting point for thinking, not an answer.

How I'll Keep It Current

A calculator with 2024 data in 2027 is worse than useless — it's actively misleading. Here's my maintenance plan:

Quarterly data refresh — Every three months I review the latest WEF, NASSCOM, and Stack Overflow data. If role risks shift meaningfully, I update the base scores and bump the version. Version transparency — The tool footer shows "Last updated: [month]" and "v[version]" so you can see when data is fresh. Reader feedback loop — The "Disagree with your score?" link sends me real-world data. If Indian Scrum Masters with 5+ years experience keep telling me their score feels too high, I investigate and adjust. New roles get added — As the industry evolves, I'll add emerging roles (AI Product Manager, Prompt Engineer, AI Reliability Engineer) and remove obsolete ones.

What This Means for You

If you take one thing from this post, make it this: your displacement risk is more about what you do than who you are.

• A Manual QA Tester who learns automation and AI tools can move from Critical to Moderate in 12 months.
• A Project Manager who shifts from status reporting to strategic decisions can cut their risk by 15-20 points.
• A Senior Developer who doesn't adopt AI tools is slowly eroding a position that should be safe.

The calculator gives you a starting point. The next 12 months is where you write the rest of the story.

Try It Yourself

→ Launch the AI Job Risk Calculator

If you want deeper reading while you're here:

• AI Job Apocalypse? The Data Says Otherwise — the macro picture of AI and employment
• India's IT Industry at a Crossroads — specifically what AI means for Indian IT
• High-Paying AI Skills Indian Developers Should Learn in 2026 — concrete actions for Indian developers
• The 'AI is Just a Fad' Mindset — why waiting on the sidelines is the biggest mistake

And if you disagree with your score — tell me why. Reader feedback is how this stays useful.