- 5 hours ago
At the India Today AI Summit 2026, leaders said AI is reshaping jobs, not ending them. Routine tasks will shift to machines, while people who adapt, reskill and use AI smartly will stay relevant in the future of work.
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00:00is session ko is satr ka joh topic hai joh humnne deya tha
00:05ki is ai displacing more jobs than creating
00:09mujhe lagta hai kiunki hamarai sare guests ko dillii ke traffic se jujna pada hai
00:12mujhe lagta hai traffic control ka to ai ke paas baiter vikalp hooga
00:19ek ek karke mein ishi ek sawal se sabke saad churuaat karna chahathi ho
00:23aur anggrezhi hindi joh bhi mixed hum bachit yaa pa rakhye
00:28ki important cheez hai ki hamarai message saamne jahe
00:30ab pehli cheez ye hai ki bhohut discussion ho raha hai ki naukri
00:35chali jahegi naukri chali jahegi sab kuch eek computer baitha hua
00:38woh sara kuch control kar dega kya
00:42ye job loss real hai
00:45ya keval
00:46joh naukri hai uska tariqa badal raha hai
00:49woh transform ho raha hai
00:51kya sachmuch me ye job loss aapne dekha hai ab tak
00:55ki iska koi straight forward answer naihi hai
00:58agar ham isko eke silo me divide kar dhenge
01:00kya job loss ho raha hai
01:01sab kuch khatam ho gaya
01:02pori dunia khatam ho gaya
01:03woh bhi naihi ho raha hai
01:04ya ham ye bolne ke bade ek idealist word
01:06mein rekhi hai kuch naihi ho raha hai
01:08woh bhi galat ho ga
01:10ho kya raha hai ki kai sare aise tasks
01:13pahle kya hota ta automation aapko aise task
01:15joh workflow automation structure ho jate
01:18hai hai hai hai hai hai hai hai hai
01:19the nature of the technology is ki
01:21aap machine me coding naihi karte ho
01:23machine me unlimited data dalte ho
01:25machine aapne aapko intelligent bana leti
01:27and then it starts answering
01:27to naturally when you have such a large
01:30capability joh machine kar rahi hai
01:32to the the the impact of ai is far wide spread
01:36but then joh regular automation ka tha
01:38to that way jobs pe aise job
01:41joh kabhi sochi bhi nahi thi
01:42ke impact ho sakin technology se
01:43for sure impact are raha hai
01:44but whether is come to job loss
01:46hai no job loss nahi hai
01:47iska matlab ye hai
01:48ke shayad optimizations ho raha hai
01:51tha
01:51jayse sabse jada low hanging fruit
01:52for example hai ke chalo
01:54humare call center ki job job thi
01:55chat job actually
01:56these are not like faq type of a chat
01:58board these are human intelligent chat
02:00boards hai
02:00ya softer coding
02:02jih sari low hanging fruit hai
02:03ap ai ki term se bolou
02:04ke pura pura coding ho jayega
02:05to kal ko aapko aapko aapko
02:07aapko pačaas loog lagtay thae
02:08to pačaas ki beja
02:09shah aapko das loog lagtenghe
02:10kyunki woh log oversee karenghe
02:12the human element the gut element
02:13aek intelligence element joh hai
02:15woh hamisha rahe ga
02:16lekin joh regular cognitive work hai
02:18joh kia ja saktay
02:20machine se machine se ho ne lagt jayega
02:21pura pura
02:21so that is one part ke
02:23bohut sare task automate ho jayega
02:26puri puri job loss nahi ho
02:27ghi lekin kai sa task automate ho jayega
02:29or uske karan kahi nah kahi
02:30aek lesser number of jobs
02:32ho ne lagt jayega
02:33that is one aspect of that
02:34but agar mein dousri tarav se dekhe
02:37aaj ki date mein
02:39ai ko
02:40agar mein multiple steps pe dekho
02:42i work in infrastructure space
02:44i am looking out for
02:45hundreds and hundreds of engineers
02:47right from ke meri data center
02:50kaise banen ga
02:50right
02:51aapko aaj ki date mein india ki
02:53puri data center market
02:545-6 guna ho chukhi
02:55i am going to
02:57i mean as an industry
02:58we are going to grow
02:59at least 10 times
03:00even then industry ki
03:02compute ki demand khatam ne hogi
03:03ai ko run karne ke liye
03:04kyunki aap
03:05aek upi tha jis nne
03:07puri da humari life ko change kar diya
03:08ai will bring 50 upi moments
03:11in agriculture in health care
03:13in education in climate in banking in finance in entertainment everything will be impacted
03:18jib wu sara sara aayega
03:20uske liye
03:21sabse fundamental layer
03:22pe joh digital factories
03:23banengi
03:23ai factories
03:24banengi
03:24korn banayega
03:25unko banane ke liye data center
03:27lagengue
03:27log lagengue
03:28pura underline
03:29joh power ka
03:29cooling ka
03:30electricity ka
03:31joh automation ka
03:33ecosystem
03:33ha
03:34uske anadar
03:35wu sari companies
03:35mein log lagengue
03:36sab ko banana
03:37paadega
03:37uske oopar
03:38aapka
03:38technology
03:39leye ra ghi
03:39joh yeh bolta hai
03:40machine ko train karna hai
03:41korn karega
03:42enterprises ko
03:43aaj ko samaj nia ra
03:44mire pa data ta bhoot hai
03:45lekin
03:45mei ai ko use
03:45kaise karu
03:46korn karega
03:47engineers hi karengue
03:48the people who are able to understand business problem
03:51understand ke business ke waast kya data hai
03:53us data ko use karke
03:54ai ko use karke
03:55kaise
03:55usko productive use case
03:56mei daala jaye
03:57yeh sab chijay aasi hai
03:58joh ultimate
03:58loghi karne wale hai
04:00machine still aapke control
04:01mei rahe ghi
04:01so kuch chijay
04:03yes
04:03khatam ho jayenge
04:04automate ho jayenge
04:05log kam ho jayenge
04:05kahi chigay peh ai actually
04:07nahi nahi job create karega
04:08net impact kya ho ga
04:09we are all here to see
04:11to amrit achari ji
04:13kya ham yeh keh sakta hai
04:14ki
04:15more of a job transformation
04:17than job loss
04:20dekhi
04:20if you look at any study
04:21globally
04:23they will all say ki
04:24haan
04:24we will have some job loss
04:25but we will also have job creation
04:27and the net impact
04:27I think will be positive
04:29there will be more jobs
04:30that will be created
04:30than jobs that will get impacted
04:32you take history
04:35AI is of course
04:36very powerful trend
04:37but internet was one such trend
04:40they have all expanded
04:42the size of the economy
04:43right
04:43so I think
04:44we should all believe in that
04:45ki economy size
04:47badhega
04:48and economy size badhega
04:49that more jobs
04:50will get created
04:51and that is a natural flow
04:52and that is what I believe
04:54but I completely agree
04:55with what sir said
04:56ki
04:56the nature of jobs
04:58may change
04:58a job is nothing
05:00but a combination of tasks
05:01it may be 5 tasks
05:0210 tasks
05:0320 tasks
05:03and out of 20 tasks
05:05thus may get automated
05:06because of AI
05:07now that creates bandwidth
05:09for that person
05:10to do 10 more things
05:10which they had never done before
05:12right
05:12and we are seeing that
05:14in a very direct way
05:15in software engineering
05:16one of the last things
05:18we imagine
05:19which will get automated
05:19but we employ
05:21like many software engineers
05:23in the company
05:23it's not like
05:24we have to let people go
05:25they are producing more code
05:27in a short span of time
05:29than they could
05:30in before AI
05:31right
05:32and we take that example
05:34anywhere
05:34I think
05:35that will largely
05:36be the trend
05:39and more and more jobs
05:41will get created
05:41we are also seeing
05:42the similar phenomena
05:43like
05:43there is high demand
05:45for electrical engineers
05:46mechanical engineers
05:48people who know
05:49how to use their hands
05:49you know
05:50so these are
05:50things which will get
05:51augmented more and more
05:52with AI
05:59so here is what I would say
06:02hype and fear
06:03have got nothing to do
06:04with stats
06:05and I completely agree
06:07with the viewpoint
06:08there is a lot more
06:09anxiety
06:10because we personalize
06:13those losses
06:14when we actually take a look
06:15at some of our colleagues
06:17other professionals
06:18what we read
06:19in the media
06:20we essentially develop
06:22that fear factor
06:23the reality actually
06:24could not be more different
06:26so let me actually
06:27kind of make this
06:28very practical
06:29and a bit stat oriented
06:30if you take the
06:32World Economic Forum
06:33and LinkedIn
06:34together
06:34they have estimated
06:36that in the past
06:37two years
06:391.3 million
06:42net new AI jobs
06:44were added
06:44what was those jobs in
06:46prompt engineering
06:47AI engineering
06:49data annotators
06:51and if you get
06:53into specific industries
06:54healthcare
06:55medical AI validators
06:58transportation
06:59autonomous vehicle monitors
07:02energy
07:03smart grid managers
07:05these are jobs
07:07that never existed
07:08they now actually exist
07:09but
07:10we don't report on them
07:12we don't talk about them
07:14we don't pay attention
07:15those are net new job creation
07:19second
07:21Sunil kind of very rightfully
07:23mentioned the fact
07:24that
07:25there is
07:26a preponderance
07:27of AI data centers
07:29that are being built
07:29we marvel at it
07:31we talk about it
07:33in the sense of
07:34a new gigawatt data center
07:36Sunil can even comment
07:38on
07:38the number of GPUs
07:40that Yota actually has
07:44let's actually pause
07:45for a minute
07:46what does that mean
07:48it is okay to marvel
07:51at the fact
07:51that a new gigawatt data center
07:53is actually
07:54being stood up
07:56what goes into the data center
07:58it's not the chips
07:59or not only the chips
08:01it's steel
08:03aluminum
08:05that has to be manufactured
08:06it's PVC pipes
08:09for coolants
08:10that have to be manufactured
08:11it's cabling
08:12that has to be manufactured
08:14it's new power units
08:16that have to be manufactured
08:17there's new basically
08:19upgrades that have to be done
08:20to the grid system
08:21for which you need technicians
08:23there's more energy sources
08:25and energy mix
08:26that is required
08:27for which jobs are created
08:29for every single
08:32call center job
08:34that could perhaps
08:35have been displaced
08:37displaced
08:37because of a virtual agent
08:39there is perhaps
08:41a hundred
08:42X more jobs
08:43that are actually created
08:44because that virtual agent
08:46has to be run
08:47on a data center
08:48that has to be constructed
08:49for which manufacturing
08:50has to be done
08:51and not only
08:52kind of manufacturing
08:53has to be done
08:54but the energy systems
08:55have to be upgraded
08:56and now
08:57as per the last budget
08:59that was introduced
09:00by the government
09:01they also talked about
09:02critical mining corridors
09:04that have to be established
09:05you take the compounding
09:07effect of it
09:08there's a lot many more
09:09net jobs
09:10that are actually created
09:12than those that are lost
09:13the trick
09:14is not job losses
09:15it's job reskilling
09:18reskilling
09:18to create
09:19not necessarily
09:20a blue collar workforce
09:22or a white collar workforce
09:24but what I would kind of say
09:26a new collar workforce
09:27wow
09:29that's a good term
09:31Reju would you agree
09:34yeah I mean largely
09:35I think agree
09:36I mean firstly
09:38AI I think
09:38targets or affects
09:40more of the services
09:41or the intangible components
09:43goods as sir said
09:44you know
09:44I think
09:44will be less affected
09:46or will be affected later
09:47and I think
09:48as regards to
09:50the way in which
09:52job change
09:53the way it is changing
09:54I would like to give
09:55an example
09:56of customer support
09:57you know
09:57something that we
09:58deal with
09:59so we've tried
10:00to automate
10:00customer support
10:01but what will happen
10:03is
10:03we are maybe
10:04currently at 50-60%
10:06automation of
10:07you know
10:07all the queries
10:08that come in
10:08now there is a bunch
10:10of people
10:10who will
10:11you know
10:11who will kind of
10:12use AI
10:13to make that
10:14take that
10:1550-60%
10:16up to 80-90%
10:17but then you'll still
10:18be left with
10:19you know
10:1920%
10:20of the queries
10:21which are the really
10:22complex cases
10:23that you know
10:23AI can't
10:24you know
10:24touch
10:24so you need
10:25those subject matter
10:25experts
10:26you know
10:27that will work
10:28on those
10:2810-20%
10:29of the tickets
10:30and I think
10:30that's going
10:30to be the trend
10:31for a lot
10:31of the existing
10:32jobs
10:33as to how
10:33they will change
10:34and then of course
10:35there will be
10:35new kinds of
10:36jobs
10:36you know
10:37that we are
10:37discussing
10:37I think
10:40I think
10:40I think
10:41we have
10:41seen
10:41our
10:42thought
10:43of the
10:44AI
10:44as we
10:47see
10:47the robot
10:47humanoid
11:14and I think the real conversation, I would say,
11:18is not job losses.
11:19The real conversation is, if we are trying to resist AI
11:24and not follow the path and trying to skill ourselves,
11:27and by the way, there can always be some part of the organization
11:34which will be coding it, fine-tuning it,
11:37creating your own model, which will be put to use.
11:40But every single person in the organization
11:42will have to be illiterate to how to use AI.
11:46Because if you are not doing it, it's a very cliche statement
11:48that AI will not take your job,
11:51a person equipped with AI will take a job
11:53of a person who is not equipped with AI.
11:55So, without doing it,
11:57you will be equipped with AI
12:00and equipped with your productivity.
12:03I'll give a simple example.
12:05In our organization, there are certain low-hanging fruits.
12:08Today's rate, my marketing team,
12:10they are doing tens of things,
12:13you know, some physical, like event organizations,
12:15but lots of things which are digital,
12:17collaterals, content, social posts.
12:20Now, because of AI coming in,
12:22a lot of the stuff we are able to do,
12:23just like ChatGPT prompted.
12:25But because we are able to do everything,
12:27we are able to create a lot of creative,
12:28does it mean that I'm doing the size of my marketing team?
12:31No.
12:32Possibly, I've increased the size of the team.
12:33Why?
12:34But now, the marketing team,
12:36who was doing X amount of work,
12:38what are we doing now in our mind?
12:39What are we doing now?
12:39This work will be done by machine.
12:40I'll do what else I'll do.
12:42I'll get more customers to meet with more,
12:44I'll do more events.
12:45Basically, the physical part,
12:47till the time your today's,
12:49I would say, logical AI or the agentic AI
12:52also start getting into the domain of physical AI,
12:55that tomorrow human-hood reverts,
12:57that will also be our Mali, technician, plumber,
12:59that will also be doing all the work.
13:01Possibly, you'll have to see that
13:02what will cost economics and robots produce?
13:05Possibly, we'll still feel our people,
13:07that will be a very good job.
13:08Why do I have to take automation?
13:09Even then, that question will be there.
13:10But what I'm saying is,
13:12AI will increase productivity from the AI.
13:15Overall, how much you can do the work,
13:17in companies, maybe you can create more revenue,
13:20new product lines, new businesses,
13:22you can do the business in that direction,
13:24thinking, no, no, I'll reduce the cost,
13:25and the logo will reduce the cost.
13:27That is, I think, the impact will be there,
13:29but that is the most fundamental requirement.
13:30And which I see day in and day out in my own organization.
13:34I can see the people,
13:36youngsters in my organization,
13:38who are older people,
13:39who are like us,
13:40who are resisting.
13:42Because we have to learn,
13:43learn,
13:44we have to debate,
13:45we have to do what we have to do,
13:46what we have to do,
13:46Is it not?
13:48Youngsters don't think all this in mind.
13:50That starts from a moment.
13:51My entire AI department in my company
13:54is run by youngsters who are like
13:55two years, three years old.
13:56And their salary levels are already
13:58two times, three times higher
13:59than the people who are nodding with the AI.
14:01So I think, instead of resisting,
14:03we adopt AI,
14:05increase our productivity,
14:06job loss not.
14:07I think,
14:08I think,
14:08I think,
14:09that's the only way to do it.
14:16So,
14:17that's the thing.
14:42I think one of the good things about the AI wave is it's quite democratic.
14:49It's not that hard and and I see that in my own job like part of my job is you
15:00know when
15:00we when we do something different we have to update our board we have to write these elaborate
15:05notes and I'm able to do that usually as to have a chief of staff he used to write those
15:12notes I used to edit and now I'm able to get a v0 version which is ten times better than
15:17what my chief of staff would have written and then we're able to kind of fine-tune it
15:23and edit it and and the AI is able to tell you things which you're not even thought about
15:29it it has as humans you have a lot of blind spots you think okay I know these ten things
15:34I don't know these other ten things but a good AI if you ask the question well it can answer
15:40the question in a way which is very very comprehensive right and and though I'm a you know tech entrepreneur
15:49I feel like if I could learn this anyone can learn this you know it's it's not that not
15:55that difficult and in fact the first person who's been after me was my wife she has been
16:00the I think she was one of the first users of chat GPT pro in India you know she's been
16:04after me two years ki you know learn this learn this learn this and I was delaying I was resisting
16:09actually yeah I was saying our manufacturing focus company hey will be the last thing that
16:14will touch my business but the moment I embraced it my productivity gains have been dramatic and
16:20I cannot imagine a world with without using it now right and and I would encourage everyone
16:25to do the same it's very simple and user-friendly tools and and this fear ki you know a new
16:32machine signal that I think is true for any job in any profession I think AI sort of exposes it
16:38in
16:38a very it keeps the spotlight on you the same is true for any company lot of companies are sitting
16:44on
16:44so much data AI can contextualize the data and make it more in a can enable decision making which you
16:51had never even thought about before so you know I think there's a lot of power in in in embracing
16:57it
16:58rather than resisting it yeah yeah I see what I'm going to resist karna chowdna hooga
17:02me personally speaking shaih maybe resist karthi mujhe lagta over dependence ho
17:07jayega lekin shaih job me will help kare uh humari in fact uh hum day India today group
17:13pehla group tha jis naik ai news anchor uh co studio bay lekar a fir uh humari anchors ki apne
17:21twins are humari ah humari twin say ai parcharine humari aur meri jo twin hai unse mein meri digital twin
17:32Shweta Singh Singh wants to ask a question in this session. If he is ready for this, then I want
17:39to give me just a cue from there. Are we ready? Yes, okay. Please.
17:47Hello. I'm Shweta Singh's digital agent. And I want to ask you all, what advice you will do to the
17:53young people? What do they want to learn so that they stay relevant in an AI-driven economy?
18:00Do they stay relevant in an AI-driven economy?
18:21Okay. So let's do this quick exercise to kind of maybe get to your question of what skill set
18:30youngsters should be developing. Maybe through a quick show of hands, how many of you have teenager children?
18:39How many of those teenager children do not use a smartphone?
18:45Okay. Fast forward five years. I'm going to ask the same question. How many of you kind of have teenagers?
18:50And how many of those teenagers do not use AI? It is inevitable.
18:55Every technology curve is inevitably going to be used by the next half a generation, not even the full generation.
19:06So if it is inevitable, what are the skill sets that are important?
19:11We can write a whole book. And frankly, you can prompt with whichever chat chat, chat what you kind of
19:17fancy, what skill sets are important?
19:21Maybe I'll do this. I'll articulate two skill sets that are more important than anything, anything that essentially a chat
19:28bot or a model basically kind of infers and gives you a response on.
19:32First skill set, curiosity.
19:36Second skill set, adaptability.
19:39If we are curious, curiosity leads to learning. Learning encourages us to be adaptable.
19:47We can pivot. We can reskill. We can take on essentially anything that we want to.
19:54You can have a digital twin. Good luck that digital twin expressing creative ideas.
20:00Good luck that digital twin developing relationships in the broader community.
20:07Good luck that digital twin actually kind of understanding context beyond what he or she can regurgitate based on its
20:18pre-training.
20:19Those are very human intuitive traits, experiences, judgment, relationships, understanding, context.
20:31That is what we actually have to focus on.
20:33That is not something that is easily replicable.
20:36Maybe at some point of time, we're not there as yet.
20:39So nothing to fear about your job and kind of what you do on a day to day basis.
20:43No, I just got a bright idea today that probably I sell my digital twin's rights to the company and
20:50sit in Goa and enjoy my holiday.
20:53But, what is the responsibility of a company that they will reskill their employees?
21:02Right. I think what we do is,
21:06I think what we do is we set a high bar of expectations in terms of outcomes.
21:13Right. I think for us, it is not that you do it with AI, but you do something that is
21:1910x better than how we are doing it today.
21:21Right. We tie it to outcomes and then let people figure out, you know, what to do.
21:25Like for instance, for again, going back to customer support, you know, we want 90% of our queries and
21:30tickets to be resolved in 10 minutes.
21:32Right. Like last year, that was 24 hours.
21:34We want, we are a payments company, so we onboard businesses.
21:37So we want onboarding to be automated again, you know, instant, right.
21:40If you do it manually, it's going to take time.
21:43So that's the kind of high bar we set.
21:45Like a landing page should be up in 10 minutes or, you know, instantly.
21:48So those kind of high bars is what we set and then people figure out, you know, and upscale themselves.
21:53Right. So people need to have a great idea of how to do their job better.
21:57You know, like they need to have that vision yardstick and then adapt themselves accordingly.
22:01I think that.
22:02I think that because the digital payments of the business, that's the biggest example of this case.
22:08Everything is digital is done, but banks are still doing this today.
22:11Internet banking people have stopped themselves.
22:15But today it is true.
22:16You can travel just via mobile phones.
22:20Actually, what happens is that many of the news from different places come from this place.
22:39I would say information sharing has become so much hype, so this is more of a highlight.
22:50When you are talking about something more and more and more and more,
22:53you can see you in one direction, you have become a fierce icon, you have to make more and more.
23:02Even without looking at the data, I can safely say that you have 10 years old,
23:06do not have job losses before the AI?
23:09Normally there are job losses, but not because the employees,
23:13the employees that were doing everything with your productive employees,
23:15suddenly they told them to go away from tomorrow
23:17across organizations, there is also in Indian culture,
23:19But in US culture, the capitalist economy is very regular in every year that you have a bottom 3-4
23:25-5% of optimizing your project or improve your P&L or people were not performing well.
23:32So this is something which is going to be there but that number will not come.
23:38Or that number will be popularized that how many companies are recruiting these companies at staggering salaries because somewhere these
23:44companies are running the race of building the best possible AI, the AGI and all that stuff.
23:49So hiring, I mean job losses are happening, if at all we say AI is happening with it, maybe AI
23:55is happening with it, which is not happening with it.
24:00So I think both things are going to be there.
24:02What kind of job loss will be and what kind of new job date will be different.
24:07Which sector is the most prevalent?
24:10Look at this time there are some things that are very low hanging.
24:15BPO sector, call center sector.
24:18Right?
24:18That is a very low hanging.
24:20That is a lot of work that people are doing.
24:21That there are some information that has been asked for the customer's query.
24:25Now the machine is not only automating it, it also can try to act like a human, try to talk
24:30like a human as much as possible and can answer that question.
24:32So the person who asked the person will also know that it is a machine and the human is not
24:36talking about it.
24:37But I am happy that someone is talking to me and whatever I am asking you, they are not doing
24:41press 1, press 2, press 3.
24:42Whatever I ask the question, they will understand me and answer them in contact.
24:46So people are okay with that.
24:47The other thing is software coding.
24:49For sure, the machine is creating a software itself.
24:52So that's why you don't have to do coding.
24:54So people who were coders have to elevate me.
24:58Instead of coding, I am going to understand the business problem.
25:00The business analyst is the person that I talk about.
25:03I understand the business of the business contact.
25:05I understand the data.
25:06I understand the data.
25:08I understand the data.
25:09I relate them to the business.
25:11I understand the business that I have to solve this problem.
25:12I use this data.
25:13I will make this model, this engine, which I will make this ER plugin.
25:17So one way, you will have to do your cognitive level,
25:21the higher level of things.
25:23You will have to do the regular routine things.
25:25You will have to do the machine.
25:26For sure, there will be an impact on there.
25:28But again, the point will come down to,
25:30how to go to the higher level of work,
25:34where I leave the routine work on AI and I will do the work of thinking.
25:38Like Nitin has said,
25:40some of the things that people are talking about AGI,
25:44the whole silicon valley is put on it.
25:46But when it comes, we will see.
25:48But there are some things that are essential human.
25:51You have shown our digital twin.
25:53Were we able to, we were doing wow on that.
25:56Wow.
25:57But were we relating to that twin the way we are relating to you?
26:00No.
26:01The human emotions, the connectedness,
26:03the cultural one,
26:04the one we talk about,
26:06we talk about body language,
26:08we don't do that.
26:09So that human element,
26:11the human-in-the-loop element
26:12is always going to be alive.
26:14So what would you have to do with advice?
26:16I mean,
26:19don't be rigid in AI,
26:20don't be rigid for AI,
26:21all these things are okay.
26:22But where will a normal employee start from
26:27to understand that my job is secure?
26:32I think job security…
26:33What is AI?
26:34Writing a set of prompts?
26:35What is AI?
26:36I mean,
26:38generally I am an optimist,
26:39but I would also,
26:40I will talk about the counter view.
26:42AI is also scary in the sense that
26:43the pace at which change is happening
26:45is very, very fast.
26:46Right?
26:46And we are thinking that
26:48in one month,
26:50I will learn this.
26:51And it's very possible that
26:52after that end of the one month,
26:55that learning may be redundant,
26:56because you know,
26:57Anthropic is a new plugin.
26:59Right?
27:00And so the only constant is change.
27:03I think that is very much applicable
27:05to our times,
27:05and especially to younger people.
27:07I think we have to be agile,
27:09we have to be fast,
27:10we have to be responsive.
27:12And we have to be to an extent ahead,
27:15which is very, very difficult.
27:16Right?
27:17And,
27:18but I feel like,
27:20I have to do it.
27:21I am sure all of,
27:22everyone who is in a leadership position,
27:23they have to constantly think about it.
27:25And that same thing applies to everyone
27:28across the organization.
27:29Right?
27:30Look around the corner a little bit.
27:32What part of my job is automatable?
27:34Think ahead of that.
27:35And then,
27:37maybe be proactive also.
27:38You can go over to your manager and say,
27:40look,
27:40I've automated my job,
27:41can I do something else?
27:42You know?
27:43And you know,
27:43that attitude will take you a long way.
27:47I should comment on kind of like,
27:48the point that you made.
27:50Going to kind of manager,
27:51can I do something different?
27:52So here's a very concrete example.
27:54Reskilling,
27:55asking,
27:56changing kind of your profile.
27:58You take a country like Japan.
28:00I think everybody kind of knows
28:02the basic demographic challenges
28:04that they've been having in the labor shortage.
28:06It's been kind of a story for two decades.
28:08A decade back,
28:09they started deploying these robots in stores.
28:12Not in the aisles,
28:13but essentially off hours and behind,
28:16so that some of the tasks,
28:18like lifting the pallet,
28:19could be done by a robot.
28:20Shelving could be done by a robot.
28:22And some of the stocking could be done by a robot.
28:25Five years back,
28:26how were those robots actually kind of operated?
28:29They were operated by a single human operator,
28:33putting on a headset,
28:34using a joystick,
28:35and controlling the robot.
28:37Tele operations.
28:38Move the joystick so that the robot could pick up
28:40kind of its arm,
28:42and consequently stalk an item.
28:45What is happening today?
28:47There are call centers in Philippines.
28:50Virtual agents have been deployed.
28:52Those jobs have been displaced
28:55of the actual call center.
28:57But has that person become redundant?
29:00Absolutely not.
29:01You know what's happening with those individuals
29:03who used to work in the call centers in Philippines?
29:05They've all been rescaled
29:07to train the models that teach the robots.
29:11So those former call center employees
29:13are now starting to train the models,
29:15and those models are then teaching the robots
29:18in a simulated environment
29:20so that you do not have a human operator
29:23that has a one-to-one connection
29:24with a headset and a joystick.
29:26You actually have a whole army
29:27of former call center employees
29:29in Philippines training the model
29:32to teach the robot.
29:33That's basically job creation,
29:35job rescaling,
29:37and job transformation.
29:38So if I ask you a percentage of jobs,
29:41that there is no one hundred percent
29:44that doesn't happen.
29:45Anything is a percent.
29:46How much is the cost?
29:48How much is the cost?
29:49How much is the cost?
29:51I think I would say 100% of the cost.
29:5399%
29:54Look,
29:55those who can change the world
29:57who are young
29:57and have an advantage for India
29:59for them it is an opportunity.
30:00I think it's a great time to be an entrepreneur
30:02and think like,
30:03what new things can I do?
30:05What can I do better?
30:06So,
30:07population ke liye,
30:08it's I think an opportunity
30:09and given that
30:11ab dekhiye jab
30:12mobile ya internet age tha,
30:13we did not have,
30:14you know, phones,
30:15we did not have internet computers.
30:16Today,
30:17everyone has access to AI
30:18and you know,
30:19India is the second largest consumer
30:20of all the LLM,
30:22you know,
30:22open AI and etc.
30:24So,
30:24we have the opportunity,
30:25we have the skills,
30:26we have the manpower,
30:26so I'm sure we'll do really well,
30:28you know, here,
30:28as a young population.
30:29So,
30:30our panel
30:31is very optimistic
30:31that the job
30:33can be changed
30:34in its way,
30:36it can be transformed,
30:37but the job will not go,
30:38it will be created.
30:39Thank you so much.
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