And so, does that create that, you know,
in more of a bifurcation that a more
polarization? How do we ensure that that
that diffusion is spread evenly? How do
we make sure that we're [clears throat]
not leaving major portions of society or
the world behind?
Because I think that's that's
[clears throat] going to be the big
issue for us going forward. Yeah, so
it's it's it's interesting, right? This
is one of those times when
uh by definition and because of the
rails that have been established, you
know, as you said, right? Which is uh
what's happened with mobile as well as
what's happened with the
uh broad, you know, essentially
connectivity.
>> Right. You have the ability
[clears throat] to sort of deliver the
tokens pretty evenly around the world.
Right. Uh a lot more so than, let's say,
uh the PC era or even the beginning of
the mobile era, right? Because it took a
long time for even the most smartphone
in particular to penetrate um all of the
world. Whereas now, it's not the case,
right? These models and their outputs
are pretty much available everywhere.
And so, the question to me is
what's the use cases that make sense,
right? So, what in fact one of the demos
I always go back to, I think this was
even in the beginning of '23, was a
rural Indian farmer was able to use a
bot built on, I think, a very early
GPT-3 or 2.5 even,
uh essentially to reason over some farm
subsidies that he had heard about in a
local language and had it even in that
very early days
uh have it even show some agentic
behavior, right? Like, go complete a
form for me. So, in some sense, it took
uh you know, it brought back agency to
someone uh who perhaps didn't have that
because the technology was so much more
accessible. So, I I do think it's in the
our hands, even in the global south, to
use it uh to create, I would say, more
of that opportunity where there isn't
one. Um but I think what the necessary
[clears throat]
conditions still are, do you have uh the
capital investment being put in?
Uh do you even have an environment for
capital? And because in an interesting
way, we are, for example, as
hyperscalers investing all over, right?
Including the global south. Uh so, as
long as there's an environment which
attracts the capital investment
>> And you see the demand.
>> And you see And then, yeah, the demand
is there.
>> Yeah. Um and so, the question is, how do
you have a set of policies that allow
for both the capital to come in, for it
to find nexus where There are certain
things, by the way, private capital can
do, certain things that public capital
only can do. For example, the grid.
Right? It's not I mean, grid in most
countries is sort of fundamentally
driven by governments.
>> And public. And so, if you
[clears throat] don't have a
sophisticated or rather, if you don't
have
a real approach to modernizing the grid,
uh that will hold things back. I mean,
there's a lot of talk about behind the
meter and so on. And yes, there's some
amount of that we can do ourselves.
>> do that in the US. Many countries can't.
Exactly. And it's not long-term
scalable, right? I mean, like, to me, a
long-term scalable solution is to have
um you know, all of these token
factories part of the real economy,
connected to the grid, connected to the
telco network, delivering
uh just like we deliver bits, you have
to deliver tokens plus bits.
Um and that's kind of what's going to
drive an at scale, whether it's in the
global south or in
uh on the developed world. So, so many
people talk about there may be an AI
bubble. I mean, the most important thing
that we see as an investor is
the the democratization of technology
and the diffusion of that technology
really does then transform the demand.
And the the companies or the countries
that diffuse it fastest are going to be
the ultimate winners, not the technology
creator.
That's that's
you know, it's it's it's
uh
the for this not to be a bubble Yep. by
definition, it requires
that the benefits of this are much more
evenly spread. I mean, I think a
telltale sign of if it's a bubble would
be if all we are talking about are the
tech firms.
Uh right? If uh all we talk about is
what's happening to the technology side,
that then that's by you know, it's just
purely supply side.
>> Right. Uh ultimately, if we are not
talking about, "Wow, here is a drug you
know, drug that was sort of uh brought
into the market that's super successful
because it was uh AI accelerated the
clinical trial." It's not even the
magical molecule, right? It's kind of
even the rest of what is
uh needed in order to make something
much more relevant, right? Um and so,
the more we [clears throat] have uh And
by the way, it's happening, right? So,
I'm not sort of saying that that's why
I'm much more confident that this is a
technology that will, in fact, build on
the rails of cloud and mobile, diffuse
faster,
>> Yep. and bend the productivity
[clears throat]
curve, and bring local surplus and
economic growth all around the world,
not just economic growth driven by
capital expenses.
Uh right? Because that's it's a narrow
point in time Right now, that's what
we're seeing more
>> That's what we're seeing in you know,
you know, in in the developed world in
particular.
Uh but remember, my capital, like that
the one thing that, you know, is
definitely is spending a lot of it in
the United States, but a 50% of it is
also all over the world.
>> Right. Um and so, interestingly enough,
it depends on
uh demand all over the world. And the
demand all over the world will only be
there if there is local surplus all over
the world. And so, that's sort of the
way I see the equation. So, let's drill
down a little more. As AI diffuses,
obviously, organizations, companies,
governments are going to have to evolve.
Now, getting into the demand side. So,
how do you think the structure of
organizations is changing in an AI
world?
Across roles, across teams, management.
I'm I'm sure um Microsoft has evolved
itself.
So, I it'd probably be good to tell the
audience how do you see this diffusion
occur in the utilization at the
corporate level or at a government level
that which ultimately then creates that
demand, which eliminates any fears and
bubbles. Yeah, now I think it it's
probably one of the the big challenges
with all of these new technologies is
when uh
work work artifact and workflow changes,
uh that means we as firms have to change
how we work. I In fact, [clears throat]
I remember meeting um
uh the CEO of Generali, you know, a few
years back, and he was describing he had
joined um
uh the firm, you know, pre-PC
[clears throat] era, and uh uh and he
was describing how, for example, they
worked with their agents in the field uh
with faxes, interoffice memos, and
uh and and suddenly the PC showed up,
and people would then put a spreadsheet
in an email and send it around, and the
entire workflow and the work process
changed. Right? So, similarly, I think
with AI, uh you are going to start
seeing uh actual change in how workflow
happens, right?
In [clears throat]
fact, for me, coming to Davos, you know,
whatever 50 bilateral meetings I have,
preparing for those
uh had a particular workflow, right?
Which is uh there used to be my field
team would prepare notes, and that would
come to my HQ, and that would get
further refined. And nothing had really
changed, right? Since I joined in '92 to
essentially even a few years back.
Whereas now, I just go to Copilot and
say, "Hey, I'm meeting Larry. Please
give me a brief." And it comes back and
gives me By the way, the one nice thing
is, it gives me a 360, right? It knows
what we're doing with you as a client,
what we're doing as a client of yours,
and everything in between
[clears throat] as an investment. It's
so, it captures even information unlike
anything else. In fact, what I do is I
take that and immediately share that
back with all my colleagues across all
the functions, right? Think about it.
It's a complete inversion of how
information is flowing in the
organization. It's not like this
classic, we have an organization, we
have departments, we have these
specializations, and the information
trickles up. No, no, no. It actually It
flattens the entire information flow.
So, once you start having that, you have
to redesign structurally. Uh so, the
current structure may not make sense.
Um because you want people to be able to
work in a way that allows them to have
this information flow freely. So, what
all this leads me to, if I have to sort
of say what's the formula, the formula I
think it starts with the mindset. So,
the mindset we as leaders should have is
we need to think about changing the work
the workflow with the technology. Then
that needs skill set. So, you can't sort
of talk about this in the abstract. You
got to use it. Like, so if I'm not using
the
>> You have to trust it.
>> You have to trust it, you have to use
it, you have to learn even how to put
the guardrails to trust it, right? So,
you can't again, you can't just be
afraid of it.
Uh it's going to it's going to be
diffused. So, the question is, as a
firm, you have to use it to learn how to
even
uh put the guardrails that allow you to
be able to trust it. So, skills, uh so,
mindset, skills. The other big
consideration um really is how do you
make sure you have the data set that
you're feeding? Like, context. Like it's
kind of like you have a new intelligence
layer, but the intelligence layer is
only as good as the context you give it.
So, people describe it even as context
engineering, but that is what firms do.
Right? If you think about what do firms
do, it's all about the tacit knowledge
we have by working as people in various
departments and moving paper and
information. So, the question is how do
you really have this AI also have that
context? So, these are sort of some of
the new things that have to percolate
throughout an organization
to take advantage. In fact, that's why I
think you're you're going to see that
challenge of why am I not seeing
immediate results in productivity?
Because you have to do the hard work. In
fact, that's why it's not going to be at
some, you know, it's going to they're
going to be firm-wide differences.
They're going to they could
[clears throat] be sector-wide
differences, but it's going to
fundamentally be because of the
leadership will in an organization.
Do you see the applications being used
across large companies and medium and
small companies or is it still the
domain of mostly the large companies at
this moment?
>> I think that what you're seeing is it's
easier the because if you have a green
sort of
you know, you if you start fresh, it's
easier to adopt these tools and you
construct your organization knowing that
these tools exist. So, I would say
>> then? It is a barbell. So, small
companies that are just starting use
that platform.
>> 100%. And I think in fact, I would say
even for large organizations, there's
[clears throat] a fundamental challenge,
right? Because unless and until your
rate of change keeps up with Right. uh
with with what is possible, uh you're
you're going to get schooled by someone
small being able to achieve scale
because of these tools. So, but I think
scale large organizations have an
inherent strength. You have the
relationships, you have the data, you
have
you have know-how, but the bottom line
is if you don't translate that with a
new production function,
uh then you really will be stuck. And
so, therefore, the change management
challenge for large organizations is
going to be bigger.
The structural challenge for small
organizations of how to overcome scale
issues are going to be harder. So, it's
sort of the two sides. In an interesting
way, it's going to be a very
competitively intense world
where neither side, like whether you're
a new entrant or an incumbent, can't
take it as like I I can just coast. What
about
country to country? Are you seeing big
differences in how the applications are
being used? Is it Is AI still the domain
of developed countries or is it becoming
rapidly a domain of all countries?
>> I I I'm seeing that two things I'd say,
Larry. As I travel around the world, the
quality
of
whether it's the know-how, the software
developers, the startups,
or even large or
large organizations, it's not that
different. It's fascinating. You can
show up in Jakarta, you can show up in
Istanbul, you can show up in Mexico
City. It's not that different than
showing up even in say Seattle or San
Francisco, right? It's not for the first
time just because access to what's
happening
uh is there. That said,
at [clears throat] scale, the commitment
to using this, the risk capital being
there, the large companies pushing it
hard. I mean, I you know, again, the US,
you know, is In fact, if I compare it,
uh take financial sector.
If in financial sector's adoption of the
cloud versus AI, night and day, right?
Because in an interesting way, it's much
faster
uh when it comes to AI versus it was
with the cloud. And cloud because for a
variety of reasons, regulatory
>> issues, too.
Until the regulators allowed banks to
bring their data off out out of campus,
that was a big issue. Yeah. So, I would
say I think [clears throat] wherever,
you know, so
in the West, in particular in the US,
uh there is clearly
a real I would say more of an energy
around it in terms of going and using
it.
Uh but it's sort of a lot more uniformly
spreading around the world than any
technology at least I've seen. Are you
Are you you mentioned [clears throat]
about power, the grid.
Is that going to be one of the
determinants of of [snorts]
the accessibility? If you do not have
cheap power,
it the demand is costly. 100%. So, if
you sort of look at the tokens per
dollar per watt, right? Which I think in
[clears throat] some sense, I would
claim that GDP growth in any place will
be directly correlated. Like you if you
sort of buy my entire argument that
look, we've got a new commodity, it it's
tokens. Right. And the job of every
economy
and every firm in the economy is to
translate these tokens into economic
growth. Then, if you have a cheaper
commodity, it's better.
Uh and so, that's sort of what why this
tokens per dollar per watt. And by the
way, there are many, many elements to
this, right? Which is it's not just um
the production side. That's why I think
even having the grid is important.
Construction costs, right? So, if you
like if you think about the total TCO,
uh everything, it's like the how are you
a cheap producer of energy? Can you
build the data centers? Uh then what's
the cost curve of the silicon in the
systems?
And by the way, look at the token
pricing, right? Token pricing basically
drops by you know, a half every 3
months. Uh I mean, this is a So, how So,
that that's why I think you can sort of
really plot how you use the tokens to
create surplus knowing that you have a
commodity that's whose prices are just
going to monotonically come down in a
pretty fast curve. We're sitting in
Europe
uh and there is a real fear
because of the Europe does not have its
own power.
It has to import mostly of its power.
Um
Do you have any messages for Europe
related to this? Yeah, I mean, I think
so, there are two sets of things, right?
One is, you know, here we are in in
Switzerland and I look at
the the pharma or the financial sector,
you know, obviously Swiss they're
they do a big job in in in this country
as in in Europe, but they're also
international brands and international
operations. So, one thing that
whenever I think about Europe is the
Europeans are producing products and
services that actually are going
everywhere in the world. And so,
therefore, uh European competitiveness
is about the competitiveness of their
output globally, not just in Europe. I
think sometimes when you come to Europe,
there's a lot of conversation about just
Europe. Uh but European economy is uh
thrives and has, you know, thrived in
the last whatever 200 years, 300 years,
the miracle of the West is fundamentally
because of what has happened in Europe
uh is because they were able to produce
things that the world needed. And so, I
would say that's number one. And in
order to do that, you again I go back to
the human capital here is just fantastic
and world-class.
Uh you have to absolutely invest in
producing uh you know, having the energy
and the tokens here, which again, you're
attracting like as I said, we are
investing and others are investing uh
the data centers here. So, the question
is what's that next generation of output
that comes from here, right? I always
think about the German Mittelstand.
Whenever I go to a jeweler or a dentist
in the United States, I'm surrounded by
German Mittelstand, right?
>> Yes, totally. Um it's just unbelievable
engineering prowess of that country.
Uh and now the question And by the way,
that's the point. They are producing
industrial products, which today are
built in into it all the intelligence as
well. That data, right? So, I know
whenever we come to Europe, everyone's
like talking about sovereignty and data
this, data that. Guess what? Europe
actually should be much more concerned
about access to their industrial
companies, their financial services
companies of data from you US and the
rest of the world. Uh as opposed to just
thinking that somehow by protecting
Europe, you're going to be competitive.
You are only going to be competitive if
the products coming out of Europe are
globally competitive.
And so, that's I think what needs to
change. I know Europe has led in
privacy, that's fantastic, has led in
many aspects of even safety around AI
and what have you, and that's a feature
that's great. But you also have to
complement it with by building locally
and then also thinking globally, what's
the contribution this continent will
make to the rest of the world, which it
has historically been a leader in.
>> A leader.
So, do you think the whole idea around
sovereignty of data, is that being
misunderstood?
I think that
when people talk about sovereignty,
first of all, it's very important,
clearly in Who owns the data? And in a
week like this, it's more important.
Uh
but that said, uh
it is
you have to kind of think about how what
is sovereignty mean? Like for example,
in the AI era, the topic that's least
talked about, but I feel will be most
talked about in in this this calendar
year will be the sovereignty of a firm.
Just imagine, if your firm,
you're not able to embed the tacit
knowledge of the firm in a set of
weights
in a model that you control,
by definition, you have no sovereignty.
That means you're leaking enterprise
value to some model company somewhere.
In fact, that it's sort of fascinating
that nobody's talking about that, right?
It's like everybody's talking about
everything else that is sort of, you
know, outside of that. Whereas the most
important thing is, it really doesn't
matter if you have In fact, the data
center where it runs is the least
important thing, quite honestly. But
like even there, first of all, the data
centers all are all over just because
speed of light is a real constraint. Uh
and so therefore, the data centers will
be spread.
>> Yes. Uh you will have digital, you'll be
able to encrypt everything, you'll be
able to have the keys with you. All of
these are much more technically solved
problems. But the one problem that will
only be solved is by you having much
more sovereignty over the, you know,
tacit knowledge uh and control over the
models, and it's not a one-way
enterprise value transfer. Um and so to
me, I think sovereignty requires real
thought on what is it.
You know, control of destiny means that
you are your ability to produce
something that is unique is preserved.
Uh David Ricardo was not wrong, there's
comparative advantage in countries. Uh
there is comparative advantage in firms.
That needs to be preserved even in the
AI era. That's what'll give you real
sovereignty. One last question, I know
we're running out of time.
Um in 5 years or 10 years, is there
going to be one dominant model that
we're all going to be using, or or and
how is Microsoft preparing for this? Are
you going to be Are we going to be using
one model for for enterprise, one model
for other other trades? You know, even
in the last, whatever, four three years,
four years that we've been at it, um the
the reality at this point is it's a
multi-model world, right? I mean, the In
fact, if you think about it,
the
in
both, there are going to be
multiple models, and the trick is really
how do you take advantage of these
multiple models,
and in fact, build your own model by
distilling these, right? Uh so think of
these models uh that you orchestrate to
build your own model, and more
importantly, you do what is described as
hard orchestration or harness
engineering. So, the IP of any
application or any firm is how do you
use all these models with context
engineering or your data? Yes. Right?
So, it's not three parts. So, can I
bring in all the models, by the way, uh
which is close source, open source,
build my own model, orchestrate them,
and feed it my data to change the
trajectory of some outcome that I care
about. That's it. That's the entire
picture. So, you can do it in like, oh,
I produce a particular product or
service. Uh first, I got to do better
better job in sales, or better job in
R&D, or better job in finance, or what
have you, and you take that outcome, and
then you say, can I use all the models,
orchestrate them, and feed it my
context, and then in as a result of it,
the reasoning traces are really leading
to some capability and models that I
control as my IP. As long as firms can
answer that question, they're going to
be getting ahead.
Ladies and Gentlemen, let's
thank Satya, my friend, Thank you.
for
>> [applause]
>> And hopefully, this is the beginning of
many great dialogue and conversations
here
at the World Economic Forum. Thank you,
everyone. Thank you.
It's getting better and better.
And interestingly enough, you look at
it, uh the software developer still is
got a lot of agency in it, right? So,
that's why I kind of still think that,
you know, going and thinking of these as
somehow living outside of the realm of
human agency is probably not the right
way to think about it. In fact, the way
to perhaps conceive it like if let's say
in early '80s, if somebody had come to
us and said,
whatever, 4 billion people are going to
wake up every morning and start typing.
You would've said, why, right? You know,
we have a like we have a typist pool
that's good enough, we don't need 4
billion people. But we That's what
happened. Like we invented this entire
class of thing called knowledge work,
where people started really using
computers uh to go amplify what we were
trying to achieve uh using software. I
think in the context of AI, that same
thing is going to happen. Um it's not
like, you know, what is hardcore coding
is going to remain hardcore coding
forever. It's just that the levels of
abstraction are going to change. Uh but
we also are going to have code as
output, just like documents. In fact,
one of Bill's things at Microsoft from
the day I joined in '92 always was,
what's the real difference between a
document, a website, and an application,
right? It's the lack of sort of software
that can transform itself. Interestingly
enough, AI finally gives us that, right?
Which is I can write a document, I can
just say, no, I don't want it as a
document, I want it as a website, it'll
just transform that document using
[clears throat] code into a website. I
say, oh, I don't like the website, I
want an app, it'll write more code to
transform it. So, that a reasoning and
capab- reasoning capabilities, that
prediction capabilities, that ability to
take action, remain long-term coherent,
is all improving. Um and our job,
though,
is to parlay this. Like take even what
you at BlackRock are doing, right? When
you're
taking something like, say, Co-pilot
plus Aladdin and bringing those things
together [clears throat]
Right. to improve the productivity in
the firm for the decisions you want to
make, right? With your data. I could
just tell you from at our firm, things
that would take 12 hours to compute now
takes minutes.
For us processing 14 trillion dollars of
other people's money with hundreds of
thousands of different um mandates, um
we could do that instantaneously. And
we, you know, that To me, if it wasn't
for the technology and AI today, we
would not be able to function to the
scale that we're operating. That's
right. And so, to me, that one firm at a
time, one country at a time, if we can
really take these tokens and bend the
curve of productivity, then there is
surplus everywhere, and that's really
the goal.
Well, surplus could be scary, too. Does
Does surplus mean
fewer workers? What do we mean by
surplus? And so, you know, the I'm going
to tie that into my second question
about AI diffusion.
>> Yeah.
To me, the the whole realization of AI
for any society,
and also for a more balanced world, is
making sure that it's diffused and
accessible and available across the
world. So, what, you know, can you
describe how this process of diffusion
across economies, across companies,
across people and countries, how does
that play out? Yeah, I think
that this is the real question, right?
Because one of the
things right now, the zeitgeist is a
little bit about the admiration for AI
in its abstract form, or
as as as technology. Uh
>> [clears throat]
>> but I think we as even a global
community um
have to get to a point where we're using
this to do something useful uh that
changes uh the outcomes of people and
communities and countries and
industries, right? Otherwise, I don't
think uh this makes much sense, right?
In fact, I would say we would quickly
lose even the social permission uh to
actually take something like uh energy,
which is a scarce resource, and use it
to generate these tokens if these tokens
are not improving health outcomes,
education outcomes, public sector
efficiency, private sector
competitiveness across all sectors,
small and large, right? And that to me
is ultimately the goal. So, therefore, I
think really diffusion is everything.
And so, the way it happens is, let's
sort of unpack this.
Uh on the supply side, what needs to
happen in each country is the tokens per
dollar per watt
have to sort of monotonically get more
efficient and better, right? So, to some
degree, even what we are trying to do
with investments the two firms are doing
around the world is to just say that
like let's make sure that the supply is
there, which is uh everything from the
chips on down ultimately to these token
factories that get deployed everywhere.
By the way, there's not one token
factory. This token factory is the first
thing that's going to be diffused all
around the world. It's just like
electricity, right? You just need a
ubiquitous grid of uh energy and tokens
that then will power the rest of the
economy, right? So, that's I think one
side of it.
Then the demand side of this is a little
bit like every firm has to start by
using it.
If I look back even, you know, when the
PCs first came out or the personal
computing era started, I loved, you
know, I think Jobs had a nice metaphor.
He called it the bicycle for the mind.
Uh Bill had a metaphor which I remember
was like information at your fingertips,
right? These two metaphors were great,
like which you know, allowed us to say,
"That's what it is. It's a tool that I
will use to get information at my
fingertips. I'll use it as a cognitive
amplifier." Now, I think that that's
what we have, but
you know, 10x, 100x, right? So, in some
sense, you as a as every knowledge
worker, you now have access to infinite
minds. That's the way I think about it,
right? So, there's a Turing Award winner
uh called Raj Reddy who had this nice
metaphor of AI and he had this long
before
uh even generative AI. He said he either
either it's a cognitive amplifier or
it's a guardian angel, right? So, if you
think of AI as that,
uh then in the global workforce, right?
When a doctor
can get to a patient, spend more time
with the patient because the AI is doing
the transcription and entering the
records in the EMR system, entering the
right billing code so that the
healthcare
uh you know, industry is better served
across the payer, the provider, and uh
and the patient ultimately, right?
That's an an outcome that I think all of
us can benefit from. So, I feel
ultimately, it's going to require real
leadership on the private sector and the
public sector to ensure the diffusion
happens. And the one thing I thing I'll
mention, Larry, is skilling.
Right? So, in some sense,
the thing that diffusion is very
strongly correlated to one thing alone,
which is how broadly are people skilled
in using this. Um and interestingly
enough, I think if mobile has taught us
one thing
is it it's actually distinct from what
happened in the PC, right?
Uh I remember even growing up in the
global south, uh there used to be a real
relationship between learning Excel
skills or Word skills and getting a job.
Um you know, right now, um
what's the model in in mobile? It's kind
of created the same opportunity, but
it's been a lot more consumption-led.
It's these creator economy and what have
you. But it's not been about sort of oh
wow, here's how you get a healthcare job
or here is how you get a finance job or
here is how you get you know, you get
ahead uh professionally.
Um
and that needs to come back, right?
People need to say, "Oh, I pick up this
AI skill and now I'm a better provider
of some product or service in the real
economy." So, it's it's very easy
[clears throat] to see how mobile and
the diffusion of mobile, how it
transformed economies, especially in the
global south.
Um how does how does this, you know, to
me, I I I just read a research report
that said
um the applications for AI so far are
heavily weighted toward those who are
educated or educated economies.
And so, does that create that, you know,
more of a bifurcation and a more
polarization? How do we ensure that that
that diffusion is spread evenly? How do
we make sure that we're not
[clears throat] leaving major portions
of society or the world behind?
Because I think that's that's going
[clears throat] to be the big issue for
us going forward. Yeah, so it's it's
it's interesting, right? This is one of
those times when
uh by definition and because of the
rails that have been established, you
know, I you said it, right? Which is
uh what's happened with mobile as well
as what's happened with the
uh bro you know, essentially
connectivity.
>> Right. You have the ability
[clears throat] to sort of deliver the
tokens pretty evenly around the world.
Right. Uh a lot more so than, let's say,
uh the PC era or even the beginning of
the mobile era, right? Because it took a
long time for even the smartphone in
particular to penetrate um all of the
world. Whereas now, it's not the case,
right? These models and their outputs
are pretty much available everywhere.
And so, the question to me is
what's the use cases that make sense,
right? So, what In fact, one of the
demos I always go back to, I think this
is even in the beginning of '23, was a
rural Indian farmer was able to use a
bot built on, I think, a very early
GPT-3 or 2.5 even,
uh essentially to reason over some farm
subsidies that he had heard about in a
local language and had it even in that
very early days
uh have it even show some agentic
behavior, right? Like go complete a form
for me. So, in some sense, it took uh
you know, it brought back agency to
someone uh who perhaps didn't have that
because the technology was so much more
accessible. So, I I do think it's in the
hands even in the global south to use it
uh to create, I would say, more of that
opportunity where there isn't one. Um
but I think what the necessary
[clears throat]
conditions still are, do you have
uh the capital investment being put in?
Uh do you even have an environment for
capital? And because in an interesting
way, we are, for example, as
hyperscalers investing all over, right?
Including the global south.
Uh so, as long as there's an environment
which attracts the capital investment
And you see the demand.
>> And you see And then yeah, the demand is
there.
>> Yeah. Um and so, the question is how do
you have a set of policies that allow
for both the capital to come in, for it
to find nexus with There are certain
things, by the way, private capital can
do, certain things that public capital
only can do. For example, the grid.
Right? It's not I mean, grid in may most
countries is sort of fundamentally
driven by governments.
>> And public.
>> And public. And so, if you don't have a
sophisticated or rather, if you don't
have a real approach to modernizing the
grid, uh that will hold things back. I
mean, there's a lot of talk about behind
the meter and so on. And yes, there's
some amount of that we can do ourselves.
>> do that in the US. Many countries can't.
Exact And it's not long-term scalable,
right? I mean, like to me, a long-term
scalable solution is to have uh you
know, all of these token factories part
of the real economy, connected to the
grid, connected to the telco network,
delivering
uh just like we delivered bits, you have
to deliver tokens plus bits. Um and
that's kind of what's going to drive an
at scale, whether it's in the global
south or in
uh on the developed world.
So, so many people talk about there may
be an AI bubble. I mean, the most
important thing that we see as an
investor is the the the democratization
of technology and the diffusion of that
technology really does then transform
the demand. And the
companies or the countries that diffuse
it fastest are going to be the ultimate
winners, not the technology creator.
That's that's
you know, it's it's it's
uh uh this for this not to be a bubble,
Yep. by definition, it requires
that the benefits of this are much more
evenly spread. I mean, I I think a
telltale sign of if it's a bubble would
be if all we're talking about are the
tech firms.
Uh right? If uh all we talk about is
what's happening to the technology side,
that then that's by you know, it's just
purely supply side.
>> Right. Uh ultimately, if we are not
talking about wow, here is a drug comp
you know, drug that was sort of uh
brought into the market that's super
successful because it was uh AI
accelerated the clinical trial. It's not
even the magical molecule, right? It's
kind of even the rest of what is uh
needed in order to make something much
more relevant, right? Um and so, the
more we have [clears throat]
uh And by the way, it's happening,
right? So, that I'm not sort of saying
that that's why I'm much more confident
that this is a technology that will in
fact build on the rails of cloud and
mobile,
diffuse faster,
>> Yep. and bend the productivity
[clears throat]
curve, and bring local surplus and
economic growth all around the world,
not just economic growth driven by
capital expenses.
Uh right? Because that's it's a narrow
point in time uh calculation.
>> Right now, that's what we're seeing more
of.
>> we're seeing in you know, in in in in in
in the developed world in particular.
Uh but remember, my capital, like that
the one thing that, you know, is
definitely we're spending a lot of it in
the United States, but 50% of it is also
all over the world.
>> Right. Um and so, interestingly enough,
it depends on
uh demand all over the world. And the
demand all over the world will only be
there if there is local surplus all over
the world. And so, that's sort of the
way I see the equation. So, let's drill
down a little more. As AI diffuses,
obviously, organizations, companies,
governments are going to have to evolve.
Now getting to the demand side. So,
how do you think the structure of
organizations is changing in an AI world
across roles, across teams, management?
I'm I'm sure um
Microsoft has evolved itself.
So, what I probably be good to tell the
audience how do you see this diffusion
occur and the utilization at the
corporate level or at a government level
that which ultimately then creates that
demand which eliminates any fears of
bubbles. Yeah, now I think it it's
probably one of the the the big
challenges with all of these new
technologies is when uh
work work artifact and workflow changes,
uh that means we as firms have to change
how we work. In fact, I remember meeting
um
uh the CEO of Generali, you know, a few
years back and he was describing he had
joined um
the firm, you know, pre-PC era
[clears throat] and uh and he was
describing how, for example, they worked
with their agents in the field with
faxes, interoffice memos and
and and suddenly the PC showed up and
people would then put a spreadsheet in
an email and send it around and the
entire workflow and the work process
changed. Right? So, similarly, I think
with AI, you are going to start seeing
actual change in how workflow happens.
Right? I mean, even
>> [clears throat]
>> in fact, for me coming to Davos, you
know, whatever 50 bilateral meetings I
have, preparing for those
had a particular workflow, right? Which
is there is to be my field team would
prepare notes and that would come to my
HQ and that would get further refined
and nothing had really changed right?
Since I joined in '92 to essentially
even a few years back. Whereas now, I
just go to Copilot and say, "Hey, I'm
meeting Larry, please give me a brief."
And it comes back and gives me By the
way, the one nice thing is it gives me a
360, right? It knows what we are doing
with you as a client, what we are doing
as a client of yours and everything in
between [clears throat] as an
investment. It's so it captures even
information unlike anything else. In
fact, what I do is I take that and
immediately share that back with all of
my colleagues across all the functions.
Right? Think about it. It's a complete
inversion of how information is flowing
in the organization. It's not like this
classic we have an organization, we have
departments, we have the specializations
and the information trickles up. No, no,
no, it actually it flattens the entire
information flow. So, once you start
having that, you have to redesign
structurally. So, the current structure
may not make sense. Um because you want
people to be able to work in a way that
allows them to have this information
flow freely. So, what all this leads me
to if I had to sort of say what's the
formula, the formula I think it starts
with the mindset. So, the mindset we as
leaders should have is we need to think
about changing the work the workflow
with the technology. Then that needs
skill set. So, you can't sort of talk
about this in the abstract. You got to
use it. Like so, if I'm not using the
You have to trust it. You have to trust
it, you have to use it, you have to
learn even how to put the guardrails to
trust it, right? So, you can't again you
can't just be afraid of it.
It's going to It's going to be diffused.
So, the question is as a firm, you have
to use it to learn how to even
put the guardrails that allow you to be
able to trust it.
So, skills, so mindset, skills. The
other big consideration
really is how do you make sure you have
the data set that you're feeding? Like
context. Like it's kind of like you have
a new intelligence layer. But the
intelligence layer is only as good as
the context you give it. So, people
describe it even as context engineering.
But that is what firms do. Right? If you
think about what do firms do, it's all
about the tacit knowledge we have by
working as people in various departments
and moving paper and information. So,
the question is how do you really have
this AI also have that context? So,
these are sort of some of the new things
that have to percolate throughout an
organization to take advantage. In fact,
that's why I think you're you're going
to see that challenge of why am I not
seeing immediate results in
productivity? Because you have to do the
hard work. In fact, that's why it's not
going to be at some, you know, it's
going to There're going to be firm-wide
differences. There are going to There
could be [clears throat] sector-wide
differences, but it's going to
fundamentally be because of the
leadership will in an organization.
Do you see the applications being used
across large companies and medium and
small companies or is it still the
domain of mostly the large companies at
this moment?
>> I think that what you're seeing is it's
easier the because if you have a green
sort of
you know, you if you start fresh it's
easier to adopt these tools and you
construct your organization knowing that
these tools exist. So, is it a barbell
then? It is a barbell. So, small
companies that are just starting use
that platform.
>> 100% and I think in fact, I would say
even for large organizations, there's
[clears throat] a fundamental challenge,
right? Because unless and until your
rate of change keeps up with Right. what
with what is possible, you're you're
going to get schooled by someone small
being able to achieve scale because of
these tools. So, but I think scale Large
organizations have an inherent strength.
You have the relationships, you have the
data, you have
you have know-how, but the bottom line
is if you don't translate that with a
new production function then you really
will be stuck. And so, therefore, the
change management challenge for large
organizations is going to be bigger.
The structural challenge for small
organizations of how to overcome scale
issues are going to be harder. So, it's
sort of the two sides. In an interesting
way, it's going to be a very
competitively intense world where
neither side, like whether you're a new
entrant or an incumbent, can't take it
as like I I can just coast. What about
country to country? Are you seeing big
differences in how the applications are
being used? Is it
Is AI still the domain of developed
countries or is it becoming rapidly a
domain of all countries?
>> I I'm seeing There are two things I'd
say, Larry. As I travel around the
world, the quality
of
whether it's the know-how, the software
developers, the startups or even large
or large organizations, it's not that
different. It's fascinating. You can
show up in Jakarta, you can show up in
Istanbul, you can show up in Mexico
City. It's not that different than
showing up even in say Seattle or San
Francisco, right? It's not for the first
time just because access to what's
happening is there. That said
at [clears throat] scale, the commitment
to using this, the risk capital being
there, the large companies pushing it
hard. I mean, I you know, again, the US,
you know, is In fact, if I compare it
take financial sector.
If in financial sector's adoption of the
cloud versus AI night and day, right?
Because in an interesting way, it's much
faster
when it comes to AI versus it was with
the cloud. And cloud because of a
variety of reasons
>> And regulatory issues, too.
Until the regulators allowed banks to
bring their data off out out of campus,
that was a big issue. Yeah. So, I would
say I think wherever, [clears throat]
you know, so
in the West, in particular in the US,
there is clearly
a real, I'd say, more of an energy
around it in terms of going and using
it. But it's sort of a lot more
uniformly spreading around the world
than any technology at least I've seen.
Are you
>> [clears throat]
>> Are you You mentioned about power, the
grid.
Is that going to be one of the
determinants of of
the accessibility? If you do not have
cheap power
if the demand is costly 100%. So, if you
sort of look at the tokens per dollar
per watt, right? Which I think in some
[clears throat] sense, I would claim
that GDP growth in any place will be
directly correlated. Like you if you
sort of buy my entire argument that
look, we've got a new commodity, it's
tokens Right. and the job of every
economy
and every firm in the economy is to
translate these tokens into economic
growth.
Then if you have a cheaper commodity,
it's better.
And so, that's sort of what why this
tokens per dollar per watt. And by the
way, there are many, many elements to
this, right? Which is it's not just the
production side. That's why I think even
having the grid is important.
Uh construction costs, right? So, if you
like if you think about the total TCO
everything, it's like how are you a
cheap producer of energy? Can you build
the data centers? Then what's the cost
curve of the silicon in the systems? And
by the way, look at the token pricing,
right? Token pricing basically drops by,
you know, a half every 3 months.
I mean, this is a So, how So, that
that's why I think you can sort of
really plot how you use the tokens to
create surplus knowing that you have a
commodity that's whose prices are just
going to monotonically come down in a
pretty fast curve. We're sitting in
Europe. And there is a real fear
because of the Europe does not have its
own power.
It has to import mostly of its power.
Um
Do you have any messages for Europe
related to this? Yeah, I mean, I think
So, there are two sets of things, right?
One is you know, here we are in in
Switzerland and I look at
the the pharma or the financial sector,
you know, obviously
they're they they do do a big job in in
in this country as in in Europe, but
they're also international brands and
international operations. So, one thing
that whenever I think about Europe is
the Europeans are producing products and
services that actually are going
everywhere in the world. And so,
therefore,
European competitiveness is about the
competitiveness of their output
globally, not just in Europe. I think
sometimes when you come to Europe,
there's a lot of conversation about just
Europe. But European economy is
thrives and has, you know, thrived in
the last whatever 200 years, 300 years.
The miracle of the West is fundamentally
because of what has happened in Europe,
is because they were able to produce
things that the world needed. And so I
would say that's number one. And in
order to do that, you again, I go back
to the human capital here is just
fantastic, it's world-class.
You have to absolutely invest in
producing,
you know, having the energy and the
tokens here, which again, you're
attracting like as I said, we are
investing and others are investing
the data centers here. So the question
is, what's that next generation of
output that comes from here, right? I
always think about the German
Mittelstand. Whenever I go to a jeweler
or a dentist in the United States, I'm
surrounded by German Mittelstand, right?
Yes. Totally. It's just unbelievable
engineering prowess of that country.
And now the question And by the way,
that's the point. They are producing
industrial products, which today are
built in into it all the intelligence as
well. That data, right? So I know
whenever we come to Europe, everyone's
like talking about sovereignty and data
this, data that. Guess what? Europe
actually should be much more concerned
about access to their industrial
companies, their financial services
companies of data from you US and the
rest of the world. As opposed to just
thinking that somehow by protecting
Europe, you're going to be competitive.
You are only going to be competitive if
the products coming out of Europe are
globally competitive.
>> Right. And so that's I think what needs
to change. And you know, Europe has led
in privacy, that's fantastic, has led in
many aspects of even safety around AI
and what have you. And that's a feature
that's great. But you also have to
complement it with by building locally
and then also thinking globally. What's
the contribution this continent will
make
to the rest of the world, which it has
historically been a leader in.
>> So do you think the whole idea around
sovereignty of data, is that being
misunderstood?
I I think that that when people talk
about sovereignty,
first of all, it's very important,
clearly Who owns the data? And in a week
like this, it's more important. Uh
but that said, uh
it is
you have to kind of think about how what
is sovereignty mean. Like for example,
in the AI era, the topic that's least
talked about, but I feel will be most
talked about in in this this calendar
year, will be the sovereignty of a firm.
Just imagine, if your firm
you're not able to embed the tacit
knowledge of the firm in a set of
weights
in a model that you control,
by definition, you have no sovereignty.
That means you're leaking enterprise
value to some model company somewhere.
In fact, that it's sort of fascinating
that nobody's talking about that, right?
It's like everybody's talking about
everything else that is sort of, you
know, outside of that. Whereas the most
important thing is, it really doesn't
matter if you have In fact, the data
center, where it runs, is the least
important thing, quite honestly. But
like even there, first of all, the data
centers all are all over just because
speed of light is a real constraint.
And so therefore, the data centers will
be spread. You will have digital You'll
be able to encrypt everything. You'll be
able to have the keys with you. All of
these are much more technically solved
problems. But the one problem that will
only be solved is by you having much
more sovereignty over the you know,
tacit knowledge and control over the
models. And it's not a one-way
enterprise value transfer. And so to me,
I think sovereignty requires real
thought on what is it?
You know, control of destiny means that
your your ability to produce something
that is unique is preserved. David
Ricardo was not wrong. There's
comparative advantage in countries.
There is comparative advantage in firms.
That needs to be preserved even in the
AI era. That's what will give you real
sovereignty. One last question. I know
we're running out of time.
Um in 5 years or 10 years, is there
going to be one dominant model that
we're all going to be using or or And
how is Microsoft preparing for this? Are
you going to be Are we going to be using
one model for for enterprise, one model
for other other trades? You know, even
in the last whatever 3 years, 4 years
that we've been at it,
the the reality at this point is it's a
multi-model world, right? I mean, the In
fact, if you think about it,
the
in
both there are going to be
multiple models.
And the trick is really how do you take
advantage of these multiple models
and in fact, build your own model by
distilling these, right? So think of
these models that you orchestrate to
build your own model. And more
importantly, you do what is described as
orchestration or harness engineering. So
the IP of any application or any firm is
how do you use all these models with
context engineering or your data? Yes.
Right? So it's that three parts. So can
I bring in all the models, by the way,
which is close source, open source,
build my own model, orchestrate them,
and feed it my data to change the
trajectory of some outcome that I care
about. That's it. That's the entire
picture. So you can do it in like, oh, I
produce a particular product or service.
First, I got to do better better job in
sales or better job in R&D or better job
in finance or what have you. And you
take that outcome, and then you say, can
I use all the models, orchestrate them,
and feed it my context? And then in as a
result of it, the reasoning traces are
really leading to some capability and
models that I control as my IP. As long
as firms can answer that question,
they're going to be getting ahead.
Ladies and gentlemen, let's
thank Satya, my friend,
>> [applause]
>> for
And hopefully this is the beginning of
many great dialogue and conversations
here
at the World Economic Forum. Thank you
everyone. Thank you.
>> Mhm.
>> Mhm.