Generative AI Will Change The Anatomy Of Tasks: Ravi Kumar S, Chief Executive Officer, Cognizant

Summary

Mr. Ravi Kumar, CEO of Cognizant, discusses the transformative impact of generative AI on the future of work. He emphasizes its potential to create a 'creator economy,' democratize expertise, and enhance human potential rather than replace it. The talk highlights AI's jagged frontier, where tasks within jobs will be disrupted, necessitating a human-in-the-loop approach. The study by Cognizant and Oxford Economics reveals AI's significant disruption across various jobs, with a focus on reskilling and responsible AI integration to foster social mobility.

Takeaways

• 🌟 Mr. Ravi Kumar, CEO of Cognizant, discusses the integration of AI with business strategy and its potential to shape the future of work.
• 📈 Cognizant is a Fortune 500 company with $20 billion in revenue and 70% of its workforce in India, making it a significant tech employer in the country.
• 🚀 Generative AI represents a significant technological discontinuity that will power economic prosperity and change job roles, skills, and occupations.
• 🔁 Historical tech disruptions like microprocessors and the internet followed an S-curve of slow start, acceleration, and plateau, but generative AI is expected to have a steeper curve due to its rapid diffusion.
• 🌐 The interface for generative AI will be natural language, which will allow for rapid adoption across various sectors and regions, including rural areas.
• 📊 AI's impact on tasks within jobs will be jagged, with some tasks being highly efficient for AI and others requiring human involvement, emphasizing the need for a 'human in the loop'.
• 💡 Alan Turing's idea that machines should replace humans is a trap; instead, AI should be designed to amplify and enhance human potential.
• 🔍 A study by Cognizant and Oxford Economics analyzed the exposure of 1,000 occupations to AI, revealing that 90% of jobs will be disrupted to some extent by 2032.
• 📉 Generative AI is a leveler, benefiting less productive workers more significantly than the highly productive, with the bottom 50th percentile gaining 43% in productivity compared to 17.7% for the top 50th percentile.
• 🛠️ As AI matures, reskilling will be crucial, moving from task automation to reorganizing businesses and embedding AI into organizational practices.
• ❤️ The essence of AI is to amplify human efforts, not replace them, as exemplified by the preference for human-to-human interaction in sports like cricket.

Q & A

What is the main topic of Mr. Ravi Kumar's speech?

Mr. Ravi Kumar's speech is focused on the impact of generative AI on the future of work and its integration with human efforts.

What is Cognizant, and what is its significance in India?

Cognizant is a Fortune 500 company with approximately $20 billion in revenues and 360,000 employees globally, of which 260,000 are based in India, making it the second largest tech services employer in the country.

What does Mr. Kumar suggest about the nature of the generative AI technology?

Mr. Kumar suggests that generative AI is a general-purpose technology that will power economic prosperity, change job anatomy, skills, tasks, and occupations, and potentially create upward social mobility.

How does Mr. Kumar describe the S-curve of technological discontinuities?

Mr. Kumar describes the S-curve of technological discontinuities as starting slow, then accelerating, and finally plateauing. He predicts that generative AI will follow a steeper S-curve due to its rapid diffusion.

What is the 'Jagged Frontier of AI capabilities' that Mr. Kumar refers to?

The 'Jagged Frontier of AI capabilities' refers to the uneven impact of AI on tasks within jobs, where AI will be highly efficient for some tasks but not for others, necessitating a human in the loop.

What was Alan Turing's perspective on machines, and how does Mr. Kumar view it?

Alan Turing spoke about machines being more efficient than humans to replace them. Mr. Kumar views this as a trap, arguing that machines and computers should be built to amplify human potential, not replace humans.

What did the study by Cognizant and Oxford Economics reveal about AI's impact on jobs?

The study revealed that AI will impact a trillion dollars by 2032, with 90% of jobs being disrupted to some extent and only 10% remaining unaffected.

How does Mr. Kumar describe the impact of generative AI on different types of workers?

Mr. Kumar describes generative AI as a leveler, impacting more productive workers but providing greater benefits to the less productive workers, potentially reducing entry barriers for specialized jobs.

What is the significance of the 'human in the loop' concept in the context of AI and jobs?

The 'human in the loop' concept signifies that even as AI takes over certain tasks, humans remain essential for overseeing and contributing to the process, ensuring that AI amplifies rather than replaces human work.

What does Mr. Kumar suggest about the future transition from an information economy to a creator economy?

Mr. Kumar suggests that the future will see a transition from an information economy to a creator economy, where AI provides expertise on demand, enhancing individual capabilities and potentially reducing the need for specialized skills to enter certain jobs.

What role does Mr. Kumar emphasize for reskilling in the context of AI's impact on jobs?

Mr. Kumar emphasizes that reskilling will become very important as AI evolves and impacts jobs, necessitating a shift from task automation to reorganizing businesses and processes, and embedding AI deeply into organizational operations.

How does Mr. Kumar conclude his speech on the role of AI in the future of work?

Mr. Kumar concludes by emphasizing that AI will always be a tool to amplify human potential, using the analogy of cricket to illustrate that humans will always care for humans and machines will serve to enhance human capabilities.

Outlines

00:00

🌟 Introduction to Generative AI and Its Impact on Business Strategy

Mr. Ravi Kumar, CEO of Cognizant, is welcomed on stage to discuss the integration of generative AI into business strategy. He emphasizes the importance of AI in shaping the future of work and its potential to create a more innovative and economically prosperous society. The speaker provides a brief overview of Cognizant, a Fortune 500 company with a significant presence in India, and hints at the transformative power of generative AI as a general-purpose technology that will redefine job roles, skills, and occupations.

05:01

🚀 The Rapid Diffusion and Disruptive Nature of Generative AI

The speaker explains the rapid diffusion of generative AI, highlighting its unique characteristic of understanding humans through natural language interfaces. This feature is expected to accelerate the adoption of AI across various sectors, including rural economies. The discussion then shifts to the jagged frontier of AI capabilities, suggesting that AI will have a variable impact on different tasks within jobs, necessitating a 'human in the loop' approach to ensure efficiency and precision. The speaker also references a study by Cognizant and Oxford Economics, which analyzed the exposure and friction scores of various occupations to AI, indicating a significant disruption in job tasks and the need for reskilling.

10:01

📊 Economic Impact and the Disruptive Curve of Generative AI

This paragraph delves into the economic impact of generative AI, projecting a trillion-dollar influence on the US economy by 2032. The speaker discusses the S-curve of technological adoption, suggesting that generative AI will follow a steeper curve due to its ability to quickly integrate into various tasks. The analysis includes a bubble chart representing the exposure and friction scores of different jobs, indicating varying levels of disruption. Generative AI is also presented as an equalizer, benefiting less productive workers more significantly and potentially reducing entry barriers for specialized jobs.

15:03

🤝 The Human-Centric Approach to AI Integration and Future Outlook

In the concluding remarks, Mr. Kumar emphasizes the importance of a human-centric approach to AI, using the analogy of cricket to illustrate that machines are tools to amplify human potential rather than replace humans. He stresses the need for responsible navigation of AI to avoid the trap of machine efficiency over human augmentation. The speaker also touches on the importance of reskilling, the evolution of businesses, and the significance of safety, trust, and equity in the integration of AI. The future of work is envisioned as a creator economy, where AI serves as a powerful tool to enhance human capabilities and create upward social mobility.

Keywords

💡Artificial Intelligence (AI)

Artificial Intelligence refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. In the context of the video, AI is the driving force behind generative AI, which is shaping the future of work by seamlessly integrating with human efforts. The script mentions AI's role in creating a 'creator economy' and its potential to amplify human potential rather than replace humans.

💡Generative AI

Generative AI is a subset of AI that focuses on creating new content, such as text, images, or music, that is novel and not simply a replication of existing data. The video discusses generative AI as a general-purpose technology that will diffuse rapidly due to its natural language interface, leading to a steep 'S curve' of adoption and integration into various tasks and jobs.

💡Cognizant

Cognizant is a Fortune 500 company mentioned in the script, specializing in providing IT services and consulting. The company is highlighted as an example of a large tech services employer in India, emphasizing the importance of AI in the tech industry and its workforce, which is a significant part of Cognizant's global employee base.

💡Tech Discontinuities

Tech discontinuities refer to significant shifts or breakthroughs in technology that disrupt the status quo and lead to new ways of doing things. The script discusses past tech discontinuities like microprocessors and the internet, and how generative AI represents the next big one, with the potential to change job roles, skills, and create social mobility.

💡S-Curve

The S-Curve is a model that describes the typical growth pattern of a technology or product, starting with a slow take-up, accelerating as it gains acceptance, and then plateauing as it reaches market saturation. In the video, the S-Curve is used to illustrate the expected rapid adoption of generative AI, which is predicted to have a steeper curve due to its fast diffusion.

💡Human-in-the-Loop

Human-in-the-Loop is a concept where humans are actively involved in the AI decision-making process, ensuring that AI systems are supervised and guided by human judgment. The script emphasizes the importance of keeping humans in the loop to avoid the 'Puring Trap' and to ensure that AI augments rather than replaces human capabilities.

💡Reskilling

Reskilling refers to the process of learning new skills or improving existing ones to stay relevant in a changing job market. The video discusses the importance of reskilling as AI continues to evolve and impact jobs, necessitating a shift in the workforce's skill set to adapt to new technologies.

💡Friction Score

In the context of the video, the friction score is a metric used to measure the ease or difficulty of reskilling workers for tasks that may become automated due to AI. Lower friction scores indicate tasks that can be more easily adapted to, while higher scores suggest greater challenges in reskilling and potential job disruption.

💡Knowledge Workers

Knowledge workers are individuals whose primary job involves creating, manipulating, or disseminating information and knowledge. The script points out that generative AI is likely to disrupt knowledge workers more than blue-collar workers, indicating a significant shift in the impact of technological advancements on different types of jobs.

💡Creator Economy

The creator economy refers to a socio-economic system where individuals create content or provide services based on their skills and expertise. The video suggests that generative AI will transition us from an information economy to a creator economy by providing expertise on demand and lowering entry barriers for specialized jobs.

💡Social Mobility

Social mobility refers to the ability of individuals to move up or down in social status, typically in relation to their occupation and income. The script mentions that generative AI has the potential to create upward social mobility by providing access to jobs and opportunities that were previously unattainable.

Highlights

Ravi Kumar, CEO of Cognizant, discusses the integration of AI with business strategy.

Cognizant is a Fortune 500 company with a significant presence in India, employing 70% of its workforce there.

Generative AI is a general-purpose technology that will power economic prosperity and change job anatomy.

Tech discontinuities follow an S-curve, with generative AI expected to have a steeper curve due to rapid diffusion.

Generative AI is unique as it's the first technology where computers aim to understand humans through natural language.

AI's impact on tasks within jobs will be jagged, requiring a human in the loop for efficiency.

Alan Turing's idea that machines should replace humans is a trap; AI should amplify human potential instead.

A study by Cognizant and Oxford Economics analyzed the AI exposure and friction scores for thousands of occupations.

Generative AI will disrupt white-collar workers more than blue-collar workers, affecting knowledge workers significantly.

Generative AI acts as an equalizer, benefiting less productive workers more and leveling the playing field.

Expertise will be readily available through AI, reducing entry barriers for specialized jobs.

The transition from an information economy to a creator economy is facilitated by AI's ability to provide expertise on demand.

Generative AI will create upward social mobility by providing access to jobs previously out of reach.

Reskilling becomes crucial as generative AI evolves and integrates deeper into organizational processes.

Safe, trustworthy, and equitable AI is essential to avoid the trap of replacing humans with machines.

In the context of sports like cricket, machines are used to amplify human performance, not replace it.

AI should always be a tool to enhance human potential, reflecting the future of work and jobs.

Transcripts

we now turning our attention to

scripting tomorrow with artificial

intelligence exploring the dynamic

interplay of Technology Ai and business

in shaping an Innovative future

absolutely and for this I'm pleased to

invite and introduce on stage Mr Ravi

Kumar he is the CEO of cognizant and

expert of course in melding AI with

business strategy Mr Kumar welcome on

stage you will be enlightening us about

generative AI SP to shape the future of

work and its seamless integration with

human efforts thank you so

much thank you everyone uh thank you for

the opportunity to talk to all of you uh

always

uh always love coming to

India the energy the

enthusiasm um and the vibrancy just kind

of rubs off as you uh get to India so

the first uh thing I would do I have 15

minutes uh to talk about uh generative

AI I know I'm not the first Speaker

speaking on generative AI in the last

one year I'm sure you've heard many of

many of uh the speakers across the world

talking about it I'll pivot it in a

direction and so that you get some

takeaways from today um what I'm going

to do uh talk a little bit about um G of

AI but before that I'll introduce uh

cognizant cognizant is a Fortune

500 uh roughly $20 billion of revenues

uh 360,000 employees

globally 260,000 of them actually are

based in India so 70% of our Workforce

is in India we the second largest tech

services employer in India so pretty big

in India the heart of the companies in

India tech services companies pivot

on technology dis continuities which U

power human capital

needs and U the generative AI

discontinuity which is going to be the

next big one is very different from the

past but it is going to actually power

economic Prosperity is going to change

the anotomy of jobs

skills uh tasks

occupations uh it's probably going to

create upward social Mobility so we we

kind of going to Pivot a little bit

about uh about that as I speak and

before I do that what I'm going to do is

um talk a little bit about uh what

happened in Tech discontinuities of the

last 40 or 50 years if you go back to

microprocessors in the '

70s um and they all go through an

scurve um the microprocessors in the'

70s it took almost uh 20 years for

personal computers to come in uh and

that was a slow

start most tech discontinuities are

general purpose Technologies general

purpose Technologies spawn Downstream

Innovation uh they are very pervasive

and they improve over time that's what

general purpose Technologies are all

about generative AI is also a general

purpose technology but it's very

different from the past if you go back

to the

internet the internet started way back

in the 80s

but the downstream Innovation which is

on search engines actually kicked off in

the '90s and actually none of us

actually remember the most popular

search engine in the '90s I'm quite sure

many of us don't remember that alter

Vista was the most popular search engine

in the '90s

uh none of us remember because we all

live in a era where the further

Downstream Innovation which came from

Google in 20 in

1998 uh was the one which actually

powered the search engine story if you

go back to the mobile Revolution very

similar the mobile Revolution started in

the ' 7s if you if you really look at it

but

smartphones really came became very

popular in

2001 and in some ways um you know when

the iPhone the first iPhone version kind

of got released that's the time uh it's

almost 35 years since the mobile re

ution started that's the time

actually the the the information age

kind of uh got created so if you look at

Tech discontinuities of the past they

went through this S curve there were it

was a slow startat then it actually

accelerated and then it

plateaued generative AI is going to be a

much steeper S curve it's going to be a

much steeper S curve and why would why

would it be a much steeper S curve it

would be a much steeper S curve

because it kind of actually diffuses

very fast why does it diffuse very fast

if you go back to the 70 years of

computing history you will realize that

almost in every change in Computing

history you would notice that U you know

humans wanted to understand

computers this is the first time

computers would like to understand

humans and the interface is going to be

natural language and if the interface is

natural language it's going to diffuse

really fast just

imagine technology built in the Silicon

Valley in um in genitive AI will diffuse

to a farmer in rural India at rapid

Pace a farmer in rural India who is

actually going to speak in a local

dialect which would access

computers and create in some ways a

Creator economy in that rural uh economy

and that is the pace at which it will it

will move and therefore this S curve is

much much steeper it'll be a slow start

a short Runway and then it'll take off

and it'll accelerate much faster than

the past S curves we've actually seen in

in the

past so what I'm going to talk a little

bit about is the jagged Frontier of AI

capabilities what I mean by that if the

blue line is actually a

workflow most times a discontinuity of

this kind will actually impact tasks it

doesn't as much impact jobs it doesn't

actually impact occupations these tasks

are on the blue curve but AI has the

capability to sharply fall

off and actually take off again and

sharply fall off what that means is for

some tasks AI will be very efficient and

for some tasks it's not going to be as

efficient so you need a human in the

loop so in some ways it's going to be

very Jagged and that's why you know jobs

are not going to get disrupted

immediately but tasks within jobs are

going to get disrupted and what's really

going to happen is you need a human in

the loop you know there was a scientist

in the 50s called Alan puring who had

spoke about how machines should be more

efficient than humans which can replace

humans and that's a trap it's a trap

because M you know computers and

machines should not be built to replace

humans they should be built to amplify

human potential this should be built to

agument and enhance human potential so I

actually believe that as as you go

through this curve and as technology

improves these curves are going to look

different but you always need a human in

the

loop you know some task for example if

you want to run an ad campaign and

brainstorm on it AI will do it very well

but if you want to point to data or if

you want to do say for example a very

precision based task you need humans in

the loop and therefore I think it's

going to be a curve which is always

going to have humans in the

loop you know cognizant and Oxford

economics ran a study for 18,000 ta

a thousand

occupations and what we really did in

that process is to understand every job

and every occupation and what the tasks

in that occupation have an exposure to

AI we took each job we cut it down to

tasks we looked at the significance of

those tasks some tasks are more

important some tasks are less important

based on the importance of the task we

we we created a weighted average and

then what we really did was we looked at

the exposure score for every

task we also we also calculated

something called the friction score

which is about

identifying tasks which get automated

and can you actually res

skill the the people who are working on

this tasks if you can rescale the

friction scores are lower if you

actually cannot

rescale your the the friction scores are

going to be very high so some jobs which

have tasks where the friction scores are

very high you need to actually put a lot

of effort to rescale and some task you

have to put lesser effort to rescale

this is also one of the few

discontinuities which have happened

which is going to disrupt a white collar

worker more than a blue collar worker

it's going to disrupt knowledge workers

much more than uh much more than blue

collar

workers so what we did from there uh is

um we we found out we actually found out

uh what is the impact it does in the US

economy it impacted a trillion dollars

by 2032 because this is a general

purpose technology it'll actually spawn

Downstream Innovation it'll improve over

time so over a period of time the

exposure scores go up 90% of the jobs

get disrupted only 10% of the jobs don't

get disrupted 9 % of the jobs have an

exposure score of more than

10% 52% of the jobs actually have an

exposure score of

25% what that means is 25% of the jobs

will actually go through A disruption

the Tas in the jobs will go through A

disruption so we we created a bubble

chart of exposure scores and friction

scores for all professions all jobs and

we actually identified the tasks in

those jobs which have an exposure to AI

it kind of

expands from the year we are in today

all the way to

2032 where uh you know the disruption

will continue on AI some will get

disrupted more some will get disrupted

less some already have a level of

disruption today which is very high so

that's uh that's how we kind of looked

at the impact of occupations and impact

of jobs and the tasks underneath

it so the next uh big difference

is generative AI is going to be a

equalizer it's some it's some kind of a

leveler it's

interesting every technology which which

has come so

far has always impacted the less

productive

workers this is a technology which will

impact the more productive workers

however the less productive workers will

actually get get the most benefit out of

this so it's some kind of a leveler the

less productive workers will get more

benefit out of it the more productive

workers will get less benefit out of it

we did a study and we found out that the

bottom 50 percentile get affected by 43%

so you get much higher productivity

using this the upper 50 percentile only

gets 177%

benefit and what that means is it's kind

of going to be a leveler of SS

what it also does is it's going to hand

over expertise on your

fingertips if you have expertise on your

fingertips the entry barriers for

specialized jobs is going to go

down if the entry barriers for

specialized jobs will go down you can

actually do a breadth of

capability using AI you know enhancing

your skill

but you could potentially have a

capability which is not necessary for

that particular job as an example if

you're an equity research

analyst analytics and mathematical

skills are very important you don't need

them to enter that job because you could

actually have expertise of mathematics

coming from an AI algorithm on your

fingertips so we going to transition

from an information information economy

to a Creator economy where you can

actually have that expertise on your

hands so that's the kind of change we're

going to see as we go forward in uh in

the space so it is it is also going to

create upward social Mobility because as

you actually use this technology in a

more mature way you're going to you're

going to access jobs which you did not

have access to and therefore therefore

create that uh create that um uh

accessibility for for

jobs so what

next so as we go forward in this

journey reskilling is going to become

very important some of the panelists

spoke about it

before as evolution of this technology

happens you're going to Mo move from

task

automation to reorganizing businesses

reorganizing process and then it's going

to be deeply embedded into

organizational

muscle safy

trust and Equity will make it very

responsible if you don't want to fall

into the puring Trap as I spoke

about you will have to responsibly

navigate it responsibly navigating it

means you don't replace the humans in

the in the loop but you enhance human

potential by doing this and and

finally what I want to say is humans

care for

humans you know I'm in India I'm going

to take an example of cricket to wrap up

my conversation you're never going to

see a machine bowling in cricket to a

human batting and you'll never be

excited to see that you'll always use a

machine to amplify the human you'll

always use it to practice yourself

you'll always want a human to bow to a

bad to a to a batter who's also a human

so humans will care for humans the

context of machines is always going to

be in the context of humans so AI will

always be a powerful tool to amplify

human potential and that's the power of

this new discontinuity we're going to

see in the future of work and future of

jobs thank you

again thank you so very much Mr Ravi

Kumar for giving us that deep insight

into generative Ai and the kind of power

that it has to shape the future for work