What You’ll Learn
- Technology WAT Topics: The 2025 Landscape
- WAT Technology Topics: AI & Automation
- WAT Topics on Space Technology
- WAT Topics on Technology: Digital Society & Data
- WAT Topics on Ethics in Technology and AI
- Recent WAT Topics on Technology and AI
- GD Topics on Technology: Complete List
- GD Topics on AI and Technology
- The IMPACT Framework for Tech Essays
- Sample Responses That Scored 8+
“Six months ago, I lost my job to an AI tool. Today, I train that same tool.” This opening from an IIM convert’s essay captures the essence of technology topics in WAT—they’re not abstract debates anymore. They’re lived realities that demand nuanced, evidence-based responses.
Technology WAT topics now account for nearly 30% of all questions across IIMs, making them one of the most critical categories to master. But here’s what evaluators see repeatedly: generic essays that either praise technology unconditionally or dismiss it as dangerous. Neither scores well.
Most common at: IIM Bangalore, IIM Calcutta, IIM Indore, ISB
Winning approach: Balance optimism with risks, use recent Indian examples, consider societal impact, and avoid the false dichotomy trap. “AI will replace jobs” vs “AI will create jobs” is a false binary—the sophisticated answer addresses both simultaneously.
Technology WAT Topics: The 2025 Landscape
Understanding the current state of technology WAT topics helps you anticipate what IIMs will ask and how to prepare strategically.
Topic Distribution in 2024-25
| Technology Sub-Category | % of Tech Topics | Primary Schools |
|---|---|---|
| AI & Automation | 35% | IIM-B, IIM-C, IIM-I, XLRI |
| Digital Society & Social Media | 25% | IIM-B, IIM-C, ISB |
| Data Privacy & Surveillance | 20% | IIM-B, IIM-C, XLRI |
| Space & Scientific Innovation | 12% | IIM-I, IIM-A (AWT) |
| Technology Ethics | 8% | XLRI, SPJIMR |
Why Technology Topics Are Increasing
When the topic says “Will AI replace human jobs?”, they list facts about AI. But evaluators want to see your reasoning: What assumptions underlie this question? Which jobs? Over what timeframe? What does “replace” even mean—elimination or transformation?
Challenge the false dichotomy. “AI replaces vs creates jobs” isn’t an either/or. The sophisticated answer is: AI will eliminate some roles, transform others, and create new ones—and policy must address all three simultaneously. That’s the thinking that scores 8+.
WAT Technology Topics: AI & Automation
WAT technology topics on AI dominate the technology category. Here are the key topics with strategic approaches:
Top 15 AI & Automation Topics
| Topic | Key Angle |
|---|---|
| “Will AI replace human jobs or create new ones?” | Challenge the binary: transformation, not just replacement |
| “Impact of AI on Indian IT industry” | Service vs product shift; reskilling imperative |
| “Human skills in an automated world” | Creativity, empathy, judgment—what machines can’t replicate |
| “Should there be an AI pause?” | Innovation pace vs safety trade-off; global coordination |
| “Will AI democratize or concentrate power?” | Access vs control; open source vs proprietary |
| Topic | Key Angle |
|---|---|
| “Should AI development be regulated?” | Innovation vs safety; who regulates the regulators |
| “Should AI-generated content be labeled?” | Transparency vs enforcement challenges |
| “Is autonomous vehicles’ moral dilemma solvable?” | Trolley problem in practice; liability frameworks |
| “Should India develop its own AI models or use global ones?” | Self-reliance vs efficiency; data sovereignty |
| “Should there be algorithmic transparency laws?” | Explainability vs trade secrets; public vs private |
| Topic | Key Angle |
|---|---|
| “Is AI in education an enabler or a crutch?” | Learning assistance vs dependency; critical thinking |
| “Is AI creativity genuine or mere pattern matching?” | Definition of creativity; consciousness debate |
| “The ethical implications of AI in hiring” | Bias amplification vs efficiency; accountability |
| “Deepfakes and truth in the digital age” | Misinformation crisis; detection vs creation arms race |
| “Can machines ever be truly intelligent?” | Narrow vs general AI; consciousness vs capability |
Essential AI Statistics for Essays
Adoption:
• ChatGPT: 100 million users in 2 months (fastest adoption in history)
• India AI workforce: Expected to grow 30% annually through 2030
Impact:
• WEF estimate: 85 million jobs displaced, 97 million new roles by 2025
• McKinsey: 30% of work activities automatable with current technology
India-Specific:
• IndiaAI Mission: ₹10,300 crore allocated (2024)
• Deepfake complaints: Increased 400% in 2024
• AI in hiring: 78% of top Indian companies now use AI screening
WAT Topics on Space Technology
WAT topics on space technology have gained prominence following Chandrayaan-3’s success. These topics test your ability to connect scientific achievement with broader implications.
Space Technology Topics List
| Topic | Primary Angle | Counter-Argument |
|---|---|---|
| “Is India’s space program worth the investment?” | Soft power, technology spin-offs, scientific capability | Opportunity cost vs. poverty alleviation |
| “Space exploration: National pride or global necessity?” | Climate monitoring, asteroid defense, resource scarcity | Terrestrial problems need terrestrial solutions |
| “Should space be commercialized?” | Innovation, cost reduction, accessibility | Commons vs. privatization; space debris |
| “India’s satellite diplomacy: Strategic asset?” | Regional influence, South-South cooperation | Priorities, dependency creation |
| “Space race 2.0: Cooperation or competition?” | Artemis Accords vs. separate missions | Geopolitical tensions, resource competition |
The Chandrayaan-3 Example
Avatar-2 budget: ₹2000 Cr
• Geopolitical: Soft power, diplomacy
• Scientific: Research, innovation
• Social: Inspiration, STEM education
• Chandrayaan-3: ₹615 Cr (fourth country to soft-land on Moon)
• ISRO budget 2024: ₹13,043 Cr (0.04% of total government expenditure)
• Satellites launched: 400+ foreign satellites for 34 countries (₹4000 Cr revenue)
• NAVIC: India’s own GPS covering South Asia and 1500 km beyond
• Gaganyaan: First crewed mission planned, ₹12,000 Cr investment
WAT Topics on Technology: Digital Society & Data
WAT topics on technology frequently explore the intersection of digital platforms, society, and governance. These require understanding both benefits and risks.
Digital Society Topics (15 Topics)
| Topic | Framework Approach |
|---|---|
| “Is social media a threat to democracy?” | Stakeholder: Platforms, users, governments, democracy itself |
| “Technology connects but isolates” | Paradox analysis: What it gives vs. what it takes |
| “Should social media have age restrictions?” | Problem-Solution: Harm identification, enforcement feasibility |
| “Is digital detox necessary or overblown?” | Micro-Macro: Individual vs. societal perspective |
| “Should tech platforms be responsible for user content?” | Pros-Cons: Section 230 debate, intermediary liability |
Data & Privacy Topics (10 Topics)
| Topic | Key Tension |
|---|---|
| “Is privacy dead in the digital age?” | Convenience vs. autonomy |
| “Should data be treated as a public good?” | Collective benefit vs. individual rights |
| “Is surveillance capitalism acceptable?” | Free services vs. behavioral manipulation |
| “Should individuals own their data?” | Property rights vs. network effects |
| “Is India’s data protection framework adequate?” | DPDP Act 2023: Strengths and gaps |
| “Should government have backdoor access to encrypted communications?” | Security vs. privacy; technical feasibility |
| “Is biometric data collection by private companies acceptable?” | Convenience vs. irreversibility of biometric data |
| “Should there be a ‘right to be forgotten’?” | Individual dignity vs. public interest |
| “Is the ‘nothing to hide’ argument valid?” | Privacy as default vs. surveillance normalization |
| “Should tech companies be broken up?” | Competition vs. network effects; antitrust in digital age |
Digital India Statistics
Digital Payments:
• UPI: 10+ billion transactions/month (2024)
• Digital payments: 72% of all transactions in India
• UPI P2M transactions: Growing 45% year-on-year
Digital Adoption:
• Internet users: 900+ million (2nd globally)
• Smartphone users: 750 million
• Average daily screen time: 4.5 hours
Digital Divide:
• Rural internet penetration: 38% vs urban 67%
• Gender gap in internet access: 35% difference
• Digital literacy: Only 38% of population
One of my students opened an essay on digital divide with: “My grandmother still counts cash for vegetables while my brother trades crypto worth lakhs before breakfast—this is India’s digital divide in 2025.”
That single sentence did more than any statistic could. It made the abstract concrete. It showed lived experience. It revealed awareness without lecturing.
If you can connect a technology topic to something you’ve actually observed—in your family, your workplace, your hometown—use it. Personal specificity beats abstract argumentation every time.
WAT Topics on Ethics in Technology and AI
WAT topics on ethics in technology and AI are especially common at XLRI and SPJIMR, but increasingly appear at IIM Bangalore and IIM Calcutta. These test moral reasoning, not just knowledge.
AI Ethics Topics
| Topic | Core Ethical Tension | Stakeholders to Consider |
|---|---|---|
| “The ethical implications of AI in hiring” | Efficiency vs. fairness; bias amplification | Employers, candidates, marginalized groups |
| “Is it ethical to profit from addiction (social media)?” | Business model vs. user wellbeing | Platforms, users, advertisers, society |
| “Should AI weapons be banned?” | Military advantage vs. accountability | Nations, soldiers, civilians |
| “Is planned obsolescence ethical?” | Business sustainability vs. waste | Companies, consumers, environment |
| “Should AI have rights?” | Consciousness, personhood, responsibility | AI systems, developers, society |
Technology Ethics Beyond AI
| Topic | Ethical Framework to Apply |
|---|---|
| “Is online anonymity more harmful than helpful?” | Consequentialist: Net effect on discourse and safety |
| “Should genetic editing be allowed?” | Deontological: Human dignity, slippery slope |
| “Is facial recognition by governments acceptable?” | Rights-based: Privacy, surveillance, consent |
| “Should tech companies sell to authoritarian regimes?” | Virtue ethics: Corporate responsibility, complicity |
| “Is digital immortality (uploading consciousness) desirable?” | Existential: Identity, mortality, human experience |
XLRI Ethics Approach
XLRI is a Jesuit institution with values-based selection. For technology ethics topics:
Do:
• Show genuine concern for social impact
• Balance profit and purpose thoughtfully
• Reference Indian ethical frameworks, not just Western
• Consider marginalized stakeholders explicitly
Don’t:
• Take pure capitalist positions (“profit is the only duty”)
• Take pure idealist positions (“ban all technology”)
• Ignore the tension between business and ethics
Recent XLRI topics:
• “The ethical implications of AI in hiring” (2024)
• “Is profit compatible with purpose?” (2024)
• “Can business be a force for good?” (2025)
Weak conclusion: “Companies should be more ethical in their AI practices.”
(No verb. What should companies actually DO?)
Strong conclusion: “Companies must audit algorithms for bias, disclose AI usage to candidates, and appoint ethics officers who report directly to the board—not HR.”
(Multiple verbs. Specific actors. Concrete actions.)
Ethics isn’t about stating values. It’s about showing WHO does WHAT and HOW. That’s what transforms a 6/10 essay into an 8/10 essay.
Recent WAT Topics on Technology and AI
These are recent WAT topics on technology and AI that have actually appeared at IIMs and top B-schools in 2024-25:
Verified Actual Topics (2024-25)
| School | Actual Topic | Year |
|---|---|---|
| IIM Bangalore | “Is social media a threat to democracy?” | 2024 |
| IIM Calcutta | “Technology connects but isolates” | 2024 |
| IIM Indore | “Impact of AI on Indian IT industry” | 2024 |
| IIM Indore | “Electric vehicles in India: Reality check” | 2024 |
| XLRI | “The ethical implications of AI in hiring” | 2025 |
Predicted Hot Topics for 2025-26
• Deepfakes and electoral integrity
• AI in judiciary: Promise or peril?
• LLMs in education: Tool or crutch?
• Digital addiction as public health crisis
• Online polarization and democracy
• Creator economy: Employment or exploitation?
• Quantum computing threat to encryption
• Biometric data in private hands
• India’s semiconductor ambitions
Key shift in 2024-25: Technology topics are becoming less about “Is technology good or bad?” and more about “How should we govern technology?”
This means essays need to show policy awareness, not just technological understanding. Know the key debates: EU AI Act, India’s DPDP Act, Section 230, Artemis Accords, AI safety research.
GD Topics on Technology: Complete List
GD topics on technology follow similar themes to WAT but require different preparation—you need entry points, not just arguments.
Technology GD Topics by Category
- AI will create more jobs than it destroys—agree or disagree?
- Should AI development be paused until regulation catches up?
- Is ChatGPT a threat to education or an educational tool?
- Will India benefit or suffer from AI revolution?
- Human creativity vs machine efficiency: What’s more valuable?
- Should AI be granted legal personhood?
- Automation of white-collar jobs: Are engineers next?
- India’s AI strategy: Following or leading?
- AI in healthcare: Promise or overreach?
- The future of work: Human-AI collaboration
- Social media: Net positive or negative for society?
- Should parents limit children’s screen time?
- Is digital addiction a real medical condition?
- Remote work: Here to stay or pandemic anomaly?
- Online education vs traditional classrooms
- The attention economy: Who benefits?
- Digital divide: Is India bridging or widening it?
- Cryptocurrency: Future of money or speculative bubble?
- The metaverse: Revolution or hype?
- Influencer marketing: Authentic or manipulative?
- Should tech giants be broken up?
- Data localization: Security or protectionism?
- Net neutrality: Should it be mandatory?
- Government surveillance vs citizen privacy
- Should social media platforms be regulated like media companies?
- India’s semiconductor mission: Realistic or aspirational?
- Should there be a global AI treaty?
- 5G deployment: Speed vs security concerns
- Digital public infrastructure: India’s competitive advantage?
- Should platforms be liable for user content?
Technology GD Topics: Entry Point Strategy
- “Let me reframe this: it’s not AI vs jobs, it’s which jobs and when”
- “Building on what Priya said, the Indian context is different because…”
- “I want to challenge the premise—is this actually an either/or?”
- “Let’s look at this through three lenses: individual, corporate, societal”
- “Quick fact to ground us: UPI processes 10 billion transactions monthly”
- “I think technology is a double-edged sword” (cliché)
- “According to the definition of AI…” (boring)
- “In my personal opinion…” (unnecessary)
- Interrupting without acknowledging previous speaker
- Repeating a point already made by someone else
GD Topics on AI and Technology
Here are specific GD topics on AI and Technology with strategic approaches for group discussion format:
Top 15 AI-Specific GD Topics
| Topic | Opening Gambit | Differentiation Point |
|---|---|---|
| “AI in hiring: Efficient or discriminatory?” | Start with Amazon’s failed AI recruiter case | Bias amplification vs. human bias—which is worse? |
| “Should AI art be protected by copyright?” | Recent US Copyright Office ruling | Training data compensation; derivative work |
| “ChatGPT in education: Cheat or tool?” | Historical parallel: calculators in exams | What skills should education develop? |
| “AI replacing doctors: Dream or nightmare?” | Diagnostic accuracy stats (AI vs human) | Empathy, liability, patient trust |
| “Should AI decisions be explainable?” | Black box problem in simple terms | Accountability vs. competitive advantage |
GD vs WAT: Same Topic, Different Approach
| Aspect | GD Approach | WAT Approach |
|---|---|---|
| Content Depth | Multiple short points; build on others | One sustained argument with depth |
| Examples | Brief mentions; 1-2 sentences | Developed examples; 3-4 sentences |
| Counter-Arguments | Acknowledge others’ points; pivot | Explicitly state and rebut |
| Structure | Flexible; adapt to flow | Fixed; intro-body-counter-conclusion |
| Recovery | Can recover from weak start | First impression is permanent |
GD = Points/entries. You need 4-5 strong points you can deploy when there’s an opening. Each point should be 15-20 seconds maximum. Build on others, add a fresh angle, and be ready to pivot.
WAT = Sustained argument. One thesis, developed over 250 words. Every sentence supports your central claim. You control the structure.
Prepare your PESTLE analysis for any technology topic. In GD, you might only use Economic + Social. In WAT, you might develop all relevant angles into a coherent argument.
The IMPACT Framework for Tech Essays
Use this framework specifically for technology WAT topics:
IMPACT: Technology Essay Framework
“ChatGPT represents a breakthrough in large language models—not because AI is new, but because its accessibility is.”
“AI hiring tools help employers (efficiency) but may harm candidates (bias)—and neither controls the algorithm’s training data.”
“India’s DPDP Act 2023 addresses data protection but lacks specific AI provisions—a gap that needs addressing.”
“We can ban AI in hiring (lose efficiency), regulate it (implementation challenge), or audit it (ongoing cost)—each has trade-offs.”
“Companies must audit, regulators must mandate, and workers must upskill—no single actor can solve this alone.”
“In 2 years: disruption. In 10 years: adaptation. In 20 years: integration. The question isn’t if, but how we manage the transition.”
Applying IMPACT: Quick Example
I: AI automates tasks, not jobs—most jobs are bundles of tasks
M: Workers (threat), employers (opportunity), society (transition cost)
P: Reskilling programs, social safety nets, AI disclosure requirements
A: Ban (impossible), ignore (dangerous), manage (realistic)
C: Government must fund reskilling, companies must retrain before replacing, workers must adapt continuously
T: Short-term pain, medium-term adaptation, long-term productivity gains
Sample Responses That Scored 8+
Here are annotated sample responses for technology topics:
Sample 1: “Technology connects but isolates” (IIM-C Style)
“My grandmother still counts cash for vegetables while my brother trades crypto worth lakhs before breakfast—this is India’s digital divide in 2025.” [HOOK: Personal, vivid, immediate—evaluator wants to read more]
The paradox of connection-through-isolation isn’t a bug in technology—it’s a feature we designed. [THESIS: Clear position, challenges the framing]
Consider Jio’s revolution: 500 million Indians gained internet access in five years. A farmer in Gorakhpur can video-call his son in Bangalore daily—a connection impossible a decade ago. Yet the same farmer spends those calls watching his son scroll through Instagram, physically present but mentally absent. [ARGUMENT 1 + EXAMPLE: Specific, Indian, balanced]
The isolation isn’t caused by technology but by how we’ve designed its incentives. Social media profits from engagement, not wellbeing. Infinite scrolling exploits psychology for quarterly earnings. [COUNTER ACKNOWLEDGED: Not blaming technology itself]
The solution isn’t disconnection but redesign. Platforms must prioritize time well spent over time spent. Parents must model boundaries, not just mandate them. Schools must teach digital citizenship alongside coding. [VERB TEST: Multiple specific actions with actors]
Technology is a mirror, not a monster. What we see in it—connection or isolation—depends entirely on what we choose to reflect. [CONCLUSION: Memorable, ties to opening’s duality]
Sample 2: “Should AI development be regulated?” (IIM-B Style)
ChatGPT reached 100 million users in two months. The nuclear bomb took years to develop but only seconds to deploy. Speed of capability without speed of wisdom is the defining challenge of our age. [HOOK: Startling comparison, establishes stakes]
The question isn’t whether AI should be regulated—it’s how, by whom, and at what cost. [THESIS: Reframes the binary question]
The EU’s AI Act classifies systems by risk level—a sensible start. High-risk applications (hiring, lending, healthcare) face strict requirements; low-risk (spam filters) face minimal oversight. This graduated approach balances innovation with protection. [ARGUMENT 1: Policy awareness, specific example]
India faces a unique challenge. We’re simultaneously an AI developer (startups) and consumer (population). Overregulation kills innovation—ask why India has no AI giant despite its tech talent. Underregulation risks becoming a testing ground for others’ technologies. [INDIAN CONTEXT: Specific, shows complexity]
Critics argue regulation slows progress. But unregulated progress gave us social media platforms that erode democracy and AI systems that amplify hiring bias. Speed without direction isn’t progress—it’s drift. [COUNTER + REBUTTAL: Acknowledges, then refutes]
India should establish an AI regulatory sandbox—test frameworks on limited deployment before national rollout. MEITY must collaborate with IITs, not just MNCs. Industry must fund safety research, not just capability research. Citizens must be consulted, not just informed. [VERB TEST: Specific actors, specific actions]
Regulation isn’t the opposite of innovation—it’s innovation’s guardrails. [CONCLUSION: Reframes, memorable]
Sample 3: “Impact of AI on Indian IT industry” (IIM-I Style—10 min)
“Six months ago, I lost my job to an AI tool. Today, I train that same tool.” This isn’t fiction—it’s the reality facing millions of Indian IT workers. [HOOK: Borrowed from successful opener, immediate]
India’s $250 billion IT industry faces transformation, not extinction. [THESIS: Clear, nuanced]
The threat is real: routine coding, testing, and support tasks are increasingly automated. TCS and Infosys already report 15-20% productivity gains from AI—gains that translate to fewer entry-level hires. [THREAT: Specific data]
But opportunity exists: India can shift from IT services to AI services. We have the talent, the English proficiency, and the cost advantage. What we lack is urgency. [OPPORTUNITY: Balanced]
Companies must reskill before they replace. Government must reform education for AI-era skills. Workers must embrace continuous learning or face obsolescence. [VERB TEST: Fast, punchy, actionable]
The question isn’t whether AI changes Indian IT—it’s whether we shape that change or suffer it. [CONCLUSION: Forward-looking]
-
1Challenge false dichotomies in technology topics“AI replaces vs creates jobs” is a false binary. The sophisticated answer addresses transformation, transition, and policy simultaneously. Evaluators reward nuanced thinking over extreme positions.
-
2Use the IMPACT framework for structured analysisInnovation context, Multiple stakeholders, Policy dimension, Alternatives, Concrete recommendations, Temporal perspective—this ensures you cover essential angles without missing key points.
-
3Personal observation beats generic statistics“My grandmother counts cash while my brother trades crypto” is more memorable than any statistic. Connect technology topics to something you’ve actually observed. Specificity wins.
-
4Apply the Verb Test to all recommendations“Companies should be ethical” is weak. “Companies must audit algorithms, regulators must mandate disclosure, and workers must upskill” has verbs, actors, and actions. That’s what scores 8+.
-
5Know the policy landscape, not just the technologyTopics are shifting from “Is technology good?” to “How should we govern technology?” Know key frameworks: EU AI Act, DPDP Act 2023, data localization debates. Policy awareness signals sophistication.
-
6Master 15-20 statistics, not 50 vague onesCreate topic clusters: Digital India (UPI, digital payments %), AI adoption (ChatGPT users), Space (Chandrayaan cost comparison), Ethics (deepfake increase). One specific statistic used well beats five approximate ones.