WATCH: Full conversation on employability & AI with CEA V Anantha Nageswaran at AI Summit 2026
Experts discuss the urgent need for India to adapt education systems and workforce strategies to harness AI's potential while mitigating job displacement risks.
53m·Guest Multiple panelists including Vinit Na, Sanjiv Bchandani, Satish Sitha Ramay Rama, Smitha Prakash, and Anurag Mel·Host Shashi Shakar·
The Three Crisis Gaps in AI Adoption
The panel identifies three critical gaps hindering effective AI adoption in India: educational institutions resisting AI tools while students use them superficially, undefined industry expectations for AI skills, and severe accessibility disparities between tier 1 and tier 3 institutions.
Educational institutions are policing AI use while students adopt it superficially without depth
- Institutions focus on restricting AI rather than integrating it pedagogically
- Students use AI tools without institutional support, leading to shallow understanding
- This creates a capability gap where neither side achieves meaningful AI proficiency
Quote
00:02:13“Educational institutions continue to be very circumspect. They are more about policing and putting restrictions on use of AI versus students who are going ahead and using AI extensively in their day-to-day work.” — Opening Speaker
Quote
00:02:30“Because the students are not getting the support of the educational institutions, they are doing it at a superficial level. Their AI capability is not very in-depth.” — Opening Speaker
Industry demands AI skills but hasn't defined specific competency requirements
- Companies want AI-skilled hires but lack clear definitions of needed skills
- Creates mismatch between graduate capabilities and employer expectations
- Compounded by experienced workers lacking AI knowledge
Quote
00:02:47“Industry wants to now employ people with AI skills but what specific AI skills in which domain they have not defined.” — Opening Speaker
Quote
00:02:58“There is again a big expectations mismatch between what these fresh employees coming in are looking for and what the industry looks for.” — Opening Speaker
70-point digital access gap exists between tier 1 and tier 3 institutions
- 95% of tier 1 students have laptop access vs 25% in tier 3
- High-end AI models remain behind paywalls for most students
- Bandwidth costs make extensive AI usage prohibitive
Quote
00:03:33“In tier 1 institutions 95% students have access to a laptop but in tier three it drops down to 25%. So there is a 70 point gap.” — Opening Speaker
Quote
00:03:43“They don't have access to high-end models because models are expensive and behind dollar paywalls.” — Opening Speaker
AI as India's Demographic Stress Test
The Chief Economic Adviser frames AI adoption as a critical stress test for India's ability to capitalize on its demographic dividend, requiring urgent reforms across education, skilling, and labor-intensive sectors.
India needs 8M new jobs annually to avoid social instability
- Current formal skill training covers only small portion of workforce
- AI displacement could outpace reskilling efforts
- Requires coordinated national effort across private sector, academia and policymakers
Quote
00:07:27“India needs to create at least 8 million jobs annually. This is the scale of our employment challenge year after year.” — Anantha Nageswaran
Quote
00:07:55“If AI displaces faster than we can skill humans...we risk squandering our demographic window.” — Anantha Nageswaran
India must align technological adoption with mass employability
- Requires strengthening foundational education
- Scaling high-quality skilling programs
- Removing regulatory bottlenecks for labor-intensive sectors
- Ensuring calibrated AI deployment
Quote
00:10:22“We must act and act now. The first step begins with a reform of our education and pedagogy.” — Anantha Nageswaran
Quote
00:09:49“It will require a clear national commitment to aligning technological adoption with mass employability.” — Anantha Nageswaran
Media Industry's Existential Threat
Media professionals discuss how AI is fundamentally disrupting journalism through automated content creation, personalized anchors, and intellectual property challenges that threaten traditional revenue models.
AI-generated resumes create superficial homogeneity masking skill gaps
- Candidates use cheap AI models to create similar-sounding resumes
- Superficial AI usage fails to demonstrate real competencies
- Creates hiring inefficiencies when skills don't match claims
Quote
00:12:52“There are number of people who are applying for jobs using cheap models and they're all sounding the same.” — Smitha Prakash
Quote
00:13:06“When you actually meet with them they do not have the skill which they have said in their LinkedIn profile.” — Smitha Prakash
AI enables customizable anchor personas threatening journalism jobs
- News outlets could offer multiple AI versions of popular anchors
- Viewers may select intensity/version of AI-generated personalities
- Reduces need for human anchors while maintaining brand recognition
Quote
00:15:48“You never know that Republic has a milder version of AI tool and gets a milder version of Arnab Gowami for the 8:00 p.m. and the more excitable version at 9:00 p.m.” — Smitha Prakash
Quote
00:16:08“You can choose which version of the anchor you like...just like the news feed is coming in.” — Smitha Prakash
Big tech scraping Indian media content without compensation
- Major AI firms using Indian news content without payment
- Contrasts with compensation paid to Western media outlets
- Threatens viability of long-form journalism in India
Quote
00:16:29“All the big giants, the big fives, they are scraping content from Indian media organizations and not paying us for IPR, whereas they're paying millions abroad.” — Smitha Prakash
Quote
00:17:18“Media in its long form is going to disappear and India is going to face an existential threat as far as reporting and media organizations are concerned.” — Smitha Prakash
From Micro-Skills to Macro-Thinking
Vinit Na explains how AI is automating sub-process skills that drove industrial age employment, requiring a shift to problem-solving and imaginative capabilities that machines cannot replicate.
AI automates sub-skills that created industrial age employment
- Industrial revolution broke processes into sub-tasks employing many
- AI now automates these sub-skills at accelerating pace
- Requires shift from micro-skills to macro problem-solving abilities
Quote
00:18:00“In industrial age we broke that process into a guy who is very good with engines very good with tire very good with paints. So we dummified the skills...Now AI is automating the subskll.” — Vinit Na
Quote
00:19:35“The acceleration of automation is increased...people can do the same work faster cheaper better and therefore they are not going to depend on the human being.” — Vinit Na
Education must shift from knowledge transfer to imaginative curriculum
- Current system teaches fractionated knowledge
- Need curriculum that develops reimagining capabilities
- Example: Half-stories that students complete to build creative thinking
Quote
00:22:35“We need to introduce curriculum which is imaginative...that increases what we call the jugard thinking so that people start imagining new solutions.” — Vinit Na
Quote
00:22:27“In Sak Foundation we started what we call half stories. We tell half story and tell the children to reimagine the balance story.” — Vinit Na
India risks repeating Microsoft DOS history with LLMs
- Warns against foreign LLMs dominating with Indian data
- Draws parallel to DOS killing domestic operating systems
- Urges strategic thinking on data ownership and incentives for local LLM development
Quote
00:24:48“Microsoft came in and the DOS was pirated...All three operating systems were killed. And therefore over a period of time DOS became the operating system.” — Vinit Na
Quote
00:25:24“We need radical strategic thinking otherwise we will either give up our data...India will lose a competitive advantage.” — Vinit Na
Historical Patterns of Technological Disruption
Sanjiv Bchandani draws parallels from computer adoption in the 1980s to argue that while AI will transform jobs, historical precedent suggests net employment may not decline if India adapts proactively.
Institutions unaccountable to markets adapt slowly to new technologies
- Universities took 15 years to introduce computer courses
- Private sector pioneered computer training in early 1980s
- Similar lag expected in institutional response to AI
Quote
00:27:52“When a new technology comes in very often institutions that are not accountable to markets respond slowly.” — Sanjiv Bchandani
Quote
00:27:31“It took 5 to 10 years for people to understand computer as an employable skill. It took 15 years for Delhi University to respond.” — Sanjiv Bchandani
Technology fears often prove unfounded as productivity increases
- Bank computerization in 1985 faced union resistance
- No jobs lost despite automation fears
- Workers became more productive serving customers better
Quote
00:28:59“All India bank employees association...got very worried saying we lose jobs if you introduce computers...guess what? Nobody lost jobs.” — Sanjiv Bchandani
Quote
00:29:26“People became more productive. They serve customers better...productivity goes up and people are doing more things.” — Sanjiv Bchandani
Early tech adopters gain disproportionate career advantages
- PC proficiency created outsized value for late 1980s MBA grads
- Younger workers who learn AI tools will become organizational linchpins
- Older employees' slower adoption creates opportunities for tech-savvy staff
Quote
00:35:10“I was the only guy who knew how to use Harvard Graphics...I became the most useful guy at the ground level because I had a skill with a technology.” — Sanjiv Bchandani
Quote
00:35:51“The older people in any company will not know AI tools because they are not quick learners. If you learn them, you will get a job.” — Sanjiv Bchandani
AI as Capability Multiplier
Satish Sitha Ramay Rama reframes AI not as job replacement but as a productivity enhancer that will transform work organization, drawing parallels to digital native companies' software-centric operations.
AI should be viewed as capability multiplier not job replacer
- Enables faster, better outcomes in existing roles
- Parallel to smartphone cameras democratizing photography
- Focus should be on enhancing human decision-making
Quote
00:36:44“AI should be seen as a capability multiplier. It is not necessarily a tool to replace jobs but something that you can use to deliver faster better and incredible outcome.” — Satish Sitha Ramay Rama
Quote
00:37:35“You open your phones and take a photograph the incredible photographs have been made so simple simply because of technology. AI is one such more tool.” — Satish Sitha Ramay Rama
Future teams will comprise 3 humans managing 5 AI agents
- Agile teams will evolve to human-agent hybrids
- Humans define problems and monitor agent outputs
- Final accountability remains with human team members
Quote
00:41:30“Tomorrow there'll be three human beings and five agents...humans will be not only doing they're defining the problem but also managing monitoring what agents do.” — Satish Sitha Ramay Rama
Quote
00:41:47“Human beings are not going anywhere. Jobs are not going anywhere. It's just going to change the nature of job.” — Satish Sitha Ramay Rama
70-80% productivity gains observed in software development
- AI accelerates innovation cycles
- Enables higher quality product delivery
- Complements rather than replaces engineering talent
Quote
00:40:52“AI has generated incredible productivity. 70-80% more productivity in the last 2 to 3 years is significant.” — Satish Sitha Ramay Rama
Quote
00:41:02“You can deliver higher quality of product to your customers...you can do more innovation faster.” — Satish Sitha Ramay Rama
Healthcare's AI Leapfrog Opportunity
Anurag Mel presents healthcare as a prime sector where India can leverage AI to address access gaps while creating millions of new jobs through innovative care delivery models.
AI can help rebalance healthcare from sick-care to prevention
- Current system over-indexed on tertiary care institutions
- Need to shift care closer to communities
- AI enables cost-effective population health management
Quote
00:43:53“Healthcare is a very strong use case for AI...we often think of AI as taking away jobs. In fact, we should flip that.” — Anurag Mel
Quote
00:43:53“Healthcare is a is a very strong use case for AI...we should flip that especially in healthcare.” — Anurag Mel
India could create 150M healthcare jobs with AI enablement
- US has 15% workforce in healthcare equivalent
- Aging population increases care needs
- New roles like care navigators for chronic conditions emerging
Quote
00:44:02“In the US, 15% of the population is involved with healthcare...translate that to India, you're talking about 150 million plus jobs.” — Anurag Mel
Quote
00:44:54“Care navigator for high-risk cohorts...those jobs don't exist today. You are going to create new kind of jobs.” — Anurag Mel
India should aim to leapfrog not catch up in AI healthcare
- Opportunity to bypass legacy system constraints
- Build AI-native healthcare infrastructure
- Focus on population-scale solutions rather than incremental improvements
Quote
00:45:24“India shouldn't really be catching up with AI in healthcare...India should be leapfrogging it.” — Anurag Mel
Quote
00:46:43“We need to show them how these tools could potentially be useful for creating more productivity, more impact at lower cost.” — Anurag Mel
The Net Job Creation Paradox
Panelists debate whether AI will ultimately destroy or create more jobs, concluding that while specific roles will disappear, net employment may grow if India develops the right skills and policies.
50% of current jobs will disappear but 50% more will be created
- Automation will eliminate many existing roles
- New categories of work will emerge
- Key challenge is ensuring workforce has relevant future skills
Quote
00:51:39“50% of current jobs will go. I think we are fooling ourselves by assuming they will not go. The second is that we will have 50% more jobs than we have today.” — Vinit Na
Quote
00:52:00“The issue is the skills in which we are in are going to get obsolete and hence jobs are going to get obsolete.” — Vinit Na
Lifelong learnability becomes essential core skill
- Continuous skill adaptation required
- More valuable than any specific technical competency
- Educational institutions must prioritize learning agility
Quote
00:47:43“Lifelong learnability becomes an essential ingredient that students should have. With AI, that's far more important than ever before.” — Satish Sitha Ramay Rama
Quote
00:47:55“Things around you will continuously change and the speed is accelerating. So learnability has to be the core capability.” — Satish Sitha Ramay Rama
India must compete globally for the new 50% jobs
- Future jobs locationally fluid
- Requires developing competitive propositions
- Potential to capture disproportionate share through strategic focus
Quote
00:52:45“Whether those jobs will be in India or in US or in Vietnam nobody knows...India needs to develop that proposition so that we are competitive on a global scale.” — Vinit Na
Quote
00:53:07“This fight is going to be fought in the international space of who is going to use technology to create jobs and get a major share of the 50%.” — Vinit Na
⚙ Agent-readable JSON index — click to expand
{ "memcast_version": "0.1", "episode": { "id": "-7pEuZam0QM", "title": "WATCH: Full conversation on employability & AI with CEA V Anantha Nageswaran at AI Summit 2026", "podcast": "ANI News", "guest": "Multiple panelists including Vinit Na, Sanjiv Bchandani, Satish Sitha Ramay Rama, Smitha Prakash, and Anurag Mel", "host": "Shashi Shakar", "source_url": "https://www.youtube.com/watch?v=-7pEuZam0QM", "duration_minutes": 53 }, "concepts": [ { "id": "the-three-crisis-gaps-in-ai-adoption", "title": "The Three Crisis Gaps in AI Adoption", "tags": [ "education" ] }, { "id": "ai-as-india-s-demographic-stress-test", "title": "AI as India's Demographic Stress Test", "tags": [ "legal-reform", "employment-elasticity" ] }, { "id": "media-industry-s-existential-threat", "title": "Media Industry's Existential Threat", "tags": [ "automation" ] }, { "id": "from-micro-skills-to-macro-thinking", "title": "From Micro-Skills to Macro-Thinking", "tags": [ "skill-relevance" ] }, { "id": "historical-patterns-of-technological-disruption", "title": "Historical Patterns of Technological Disruption", "tags": [ "technology", "historical-analogy", "job-creation" ] }, { "id": "ai-as-capability-multiplier", "title": "AI as Capability Multiplier", "tags": [ "employee-productivity", "human-agency" ] }, { "id": "healthcare-s-ai-leapfrog-opportunity", "title": "Healthcare's AI Leapfrog Opportunity", "tags": [ "healthcare-innovation", "chronic-disease-prevention", "job-creation" ] }, { "id": "the-net-job-creation-paradox", "title": "The Net Job Creation Paradox", "tags": [ "global-competitiveness", "skill-relevance" ] } ] }