Generative AI Will Change The Anatomy Of Tasks: Ravi Kumar S, Chief Executive Officer, Cognizant
Summary
TLDRMr. 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
- π Mr. Ravi Kumar, CEO of Cognizant, discusses the integration of AI with business strategy and its potential to shape the future of work.
- π 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.
- π Generative AI represents a significant technological discontinuity that will power economic prosperity and change job roles, skills, and occupations.
- π 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.
- π The interface for generative AI will be natural language, which will allow for rapid adoption across various sectors and regions, including rural areas.
- π 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'.
- π‘ Alan Turing's idea that machines should replace humans is a trap; instead, AI should be designed to amplify and enhance human potential.
- π 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.
- π 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.
- π οΈ As AI matures, reskilling will be crucial, moving from task automation to reorganizing businesses and embedding AI into organizational practices.
- β€οΈ 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
π 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.
π 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.
π 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.
π€ 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.
Mindmap
Keywords
π‘Artificial Intelligence (AI)
π‘Generative AI
π‘Cognizant
π‘Tech Discontinuities
π‘S-Curve
π‘Human-in-the-Loop
π‘Reskilling
π‘Friction Score
π‘Knowledge Workers
π‘Creator Economy
π‘Social Mobility
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
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