And in a year of
tremendous change,
one thing captured our
attention above all else--
- AI, just the
boom of interest.
- The talk of
the town is AI.
- Artificial
intelligence is
poised to shape the world
around us for decades.
- Now, that's all
good and fine,
but let's not lose sight
of the real bottom line--
- We're bringing
the human touch
to every interaction
with our customers.
- When it comes to
customers and trust,
there can be
nothing artificial
- It's all about CRM,
AI, data, and trust,
and the power
that that brings.
- You see, this isn't
just a technological
No, this is a
trust revolution.
- Salesforce is a huge
trusted advisor when
it comes to embracing AI.
- AI has amazing
potential,
but you've got to
have really good data.
- Data Cloud allows us to
integrate that innovation
and deliver it at scale,
securely, and reliably.
- Working with
Salesforce, we're
creating these
magical connections
and personalized
experiences in a way
that nobody's
ever seen before.
- The Einstein
1 Platform, it's
the trusted and secure way
to put your data to work.
This is a once
in a lifetime
opportunity to lift
human potential.
- What the Einstein
1 Platform does
is collaborate actually
with the advisor.
- It'll take
their keywords
and will automatically
give me service replies
It's like a helping hand.
- It's improving
the team as well.
Everyone's
performance is raised.
- Yeah, it's all
of us or bust.
So no one gets
left in the dust.
- It's a turbocharger
for our business.
It's going to make
us more efficient.
Because AI is
there helping
us augment the
team, we can
transform how
we do business
and be more productive
than ever before.
- Because it
always comes down
to this timeless refrain--
business is the greatest
platform for change.
- We're in one of
the greatest moments
Trailblazers, trusted
AI, working together,
we are going to
get it right.
- We've been able to
drive a 40% increase
- Three times the output
that we have in the past.
- We delivered the highest
revenue ever, double
- Core values, true north.
- Wow, shares
in the green.
- Incredible cash
flow numbers.
- A lot of
margin expansion.
- Salesforce is going
to have a dynamite 2024.
- Thank you for everything
and all that's to come.
Please welcome co-founder
Salesforce and CTO
Welcome to the New
York World Tour.
Welcome to the
AI Enterprise,
where customer data
is the new gold.
The world is
going incredibly
We all know
that, and we're
going to give a great
show today and show you
how Salesforce is going
to bring all you forward
But as we always
do, what do we
do first in every
one of our shows?
We want to thank each
and every one of you.
Thank you to all
of our MVPs--
[AUDIO FEEDBACK]
--and Trailblazers.
Yep, and the golden
hoodies over there.
Thank you to
our nonprofits.
Do we have any
nonprofits in the room?
Shout out to
the nonprofits.
Thank you to all
of our employees,
all of the SI partners,
the ISV partners.
All of you together have
joined us over the past 25
years to create something
very, very special.
And we couldn't have
done it without you,
We have an incredible
world tour today here
We're going to go through
a whole bunch of customer
stories throughout
the day today.
In this keynote, we're
going to really highlight
an incredible story of a
company called Turtle Bay.
There are a ton of
things to do here today,
not just this keynote,
100 sessions, 20 demos,
If you can't figure it
out, go to that QR code
and use the mobile
app, the events app,
to figure out, what
are you going to do?
Because you
can't do it all.
And what's most
important to you?
It's a unique
experience for each
So together, we're really
proud over the past 25
years of where
we have gone.
And we are at $38
billion projected revenue
We're very proud of that.
But I think what we're
more proud about is
That is the model
that we've always
had as a company since I
met Marc Benioff actually
And together
with you, we have
become one of the most
innovative companies.
Together with you,
we have given back
one of the top 100
companies that care.
And together
with you, we have
been a very ethical
company, world's most
And really, why did
that all happen?
Well, it happened
because of values.
And I think the best
companies in the world
And Salesforce has
always led by our values.
Value of trust-- when
we started the company,
Would you trust a credit
card on the internet?
Would you trust
your customer list
People were like, no way.
I will never put
my customer list
But it's also about data.
And we're going
to talk a lot
And your data is
not our product.
That's also part of trust.
But it's also the values
of customer success.
We want to make you
successful before we
Before we talk about all
the innovation today,
we want to make
you successful.
It's about equality, and
it's about sustainability.
It's about those core
set of values that guide
And those values also
came out of something
that we created when
we started the company.
We created something we
called the 111 model.
The 111 model, when
we were three people
in an apartment
in San Francisco,
But look what we
have done today.
It's about 1%
of our equity.
We've given over
$700 million
out in 25 years in
all-time giving.
Three people in
an apartment,
75,000 to 80,000-- I
don't even know how many
A lot of employees
around the world
have given 8.7
million hours back.
We give nine days a year.
We tell our employees,
go give back.
Wherever you are, do
good in the world.
And we also
give our product
So all those nonprofits
that raise their hands,
56,000 nonprofits are
using our product to do
fundraising to take
care of others.
And we also want
many other companies
So we have this
pledge1percent.org.
As you're building
your companies,
if you're entrepreneur's
in the room, don't wait.
Do it as you're
building the company
because it makes for
better companies.
I also want to call out
we have the Salesforce AI
We're putting money into
these nonprofits that
We have an incredible
company here
Groundswell is doing
some really cool stuff
They're one of our
recipients, so congrats.
And you want to know
more, just go corner them
You'll learn a lot
more from them.
So 25 years ago, we
started the company.
Our vision was connect
with your customers
And together with you, we
have become the number one
We like that scale of that
number, by far the number
And it's been incredible.
But we are in a totally
new moment right now,
And we know what
that moment is.
In 2014, Salesforce
started its journey in AI.
We started our
research group.
We had PhDs, and
mathematicians,
and trying to figure
out the future.
In 2016, we
launched Einstein.
And at that time,
Einstein was
all about predictive
machine learning.
Help me understand,
which lead
should I call to
close that deal?
What's the best one
that I should call?
Who should
handle this case?
When should I
send this email?
Use machine learning and
statistics to basically
That was state of the
art at the time in 2016,
and it's still incredible.
We will see in our
demos Predictive
is still very meaningful.
But as you all know, we
have hit a tipping point.
A year and a half
ago, generative AI
really came into
fruition with OpenAI.
And we were all shocked,
including Salesforce.
Our researchers
had been involved.
We've been building stuff.
But something
happened there.
And then we're going to
talk about what happened.
Why did it hit
that tipping point?
So it's about
generative AI
and this world of
autonomous agents
that we're moving into,
that world of autonomy
where maybe the AI
is there beside you
in the enterprise,
always helping you,
And maybe at
times, we're going
to let it do stuff for us.
It's going to
say, yeah, sure.
And if anyone
responds, let
me know, and I'll
follow up with them.
That would be an example
of, do something for me.
And then we're moving
into this world
of artificial
general intelligence.
And we really do
believe that AI
is going to augment
every single enterprise.
It's going to improve
your productivity.
It's going to
improve your margins.
You're going to
make more money
and maybe that should
be the highest priority,
actually, is build better
customer relationships
because that's what
we're all about,
is helping you build
better customer
And 84% of leaders
agree that AI
will serve customers
in a better way.
That's about
the enterprise.
But let's go back
to how we got here.
What happened a
year and a half ago,
we saw this
generative AI happen.
And it really is about
these three layers.
You go to an Anthropic
or an OpenAI.
And there's a UI for
it, and each of them
We thought-- I
thought a year
and a half ago,
well, I guess
there's only one model
in the world that's
going to be great,
and that was OpenAI.
And everybody
needs to use it.
But there's so many more.
But how do those
models get created?
They trained on a
whole bunch of data.
The more data--
and that's why we
It's the massive
amounts of data
that we use to train these
models, all of a sudden,
created these billion
parameter models that
So it's these three
layers of the stack.
And in the consumer
space, what
we saw is go get all
the data you can.
The more data, the better.
Go get every
website, every book
that you could get access
to in the public domain.
Go to the New York
times, which is not
the public domain
and a little bit
But as much data
as possible,
let's just
voraciously consume it
And so we have all
these different models
and all these different
user experiences.
But in the enterprise, are
you going to go and grab
all the data on the
internet for relevancy
in the enterprise
for your customers?
What you need is
your enterprise data.
You need to get all
that enterprise data.
But you don't
have an internet
in your enterprise
where you can go
and, oh, let me just
go surf the internet
And I'm going to
get all the data.
No, you don't
have that because,
in the enterprise,
it's all siloed.
We all have this problem.
The data is all
over the place.
No matter how hard we try,
it seems like, oh my gosh,
I've got data
in a Databricks
and a Snowflake database.
I've got my SAP or
Oracle ERP system.
I'm using multiple
SaaS providers.
I've got maybe some
legacy systems.
I'm sure there's
someone here
who has mainframes
in their company.
I know a lot of banks--
are there any bankers
You have mainframes,
guaranteed.
If you're an
insurance company,
That is data, and it's
all over the place.
72% of companies'
applications
So that's at
the data layer.
How are you going
to move forward
in this world
of generative AI
if you can't
get to the data?
And then if you get
to the model layer--
You get to the
model laye, there's
also a ton of issues
you're experiencing.
Of course, we talked
about the data silo
But the model layer also
security and privacy.
These models can be toxic.
Or they're not
deterministic.
So hallucinations
can happen.
And they can be very
confident liars.
You can actually ask them,
when it's hallucinating,
And it'd be like,
I am very sure.
But it's actually
hallucinating.
And it's disconnected
from your CRM.
So at Salesforce, we want
to solve these problems
We want to solve the
problems to get to the AI
We want to help you
understand how to build
That has been our
mission for 25 years.
We want you to be able
to harmonize and unify
all of your data
with Data Cloud.
We want you to be able
to collaborate with AI.
And what better way
to collaborate with AI
than through a
conversational interface
We want you to be able
to deliver AI analytics
And finally, we want
to be able to deploy
that AI because you need
to get it to everyone.
You don't want it
to be locked up.
We want you to be able
to deploy it and deploy
that Copilot everywhere
in a trusted way.
So we're going to
walk you through all
The first step, we
want to show you how
And with that, I'd like to
bring up Patrick Stokes,
EVP of product marketing.
Thank you very
much, Parker.
Thank you very
much, everybody.
OK, so your Customer 360
is your single source
It is your
operating system
for driving growth,
for driving innovation,
and ultimately for driving
deeper relationships
with all of
your customers.
The Customer 360 is
the most robust set
of CRM capabilities
on the planet.
No other platform goes
as deep across all
of the different
customer touchpoints
that you might have
with your customer
And what makes
all of this work
is our Einstein
1 Platform.
And the Einstein
1 Platform
is the foundation for
everything at Salesforce.
It's what everything
is built on.
It's the platform that
connects everything.
It's your trusted platform
for driving growth.
It's your trusted
platform for transforming
your business with AI,
just like it helped
you transform your
business with the cloud,
with social and
mobile before it.
It's what will bring
all of your data
together with AI
and, ultimately,
all of the different
interactions
that you have with
your customers.
Now, it's integrated
with Salesforce metadata.
It's intelligent
and conversational
It's automated with flow.
And it's low
code, and no code,
and open so that you can
customize it and extend
it to meet the unique
needs of your business.
And every business
in this room
is a little bit different.
Einstein 1 is what brings
all of this together.
But at the heart
of Einstein 1,
in fact, at the
heart of almost
any of these
transformations
and especially the AI
transformation that we
need to make,
is data, which
brings us to step
2 in our five steps
to becoming an
AI enterprise.
In order to become
an AI enterprise,
we really need to get
all of our data together.
And we can see this
in our own experience.
Parker talked about
it a moment ago.
If we go ask
ChatGPT a question
about our
business today, it
isn't going to give
us a very good answer
because it doesn't
have data and context.
So we need to bring all
of that data together.
And therein lies a
really important tension,
a tension that really
has been around
But we're really
seeing it take shape.
And it's becoming
more and more tense
And it's a tension
that many in this room
It's a tension between
our business, our business
that is building all
of these customer
And they need
access to data.
They need the data
that they can trust.
And then the other
side of the tension
is with the folks in the
room that are developers,
that are admins that work
in IT, whose job it is
to go and bring all
of that data together,
to connect that data
and harmonize it.
This is an incredibly
difficult thing to do.
And it's difficult,
as Parker said,
because we have all
of these islands
We have different systems.
And we've been adding
more and more and more
systems over the
last 20 years.
And that data, it exists
in different formats
and different structures.
Some of it is structured
data, like databases.
In other cases, it's
unstructured data,
like our emails, or
conversations in Slack,
or our knowledge articles.
Sometimes we can get
at that data only
Sometimes we
need to use APIs.
Sometimes it's streaming.
It's really difficult
to bring all of this
And that's why Salesforce
built Data Cloud.
Data Cloud is your trusted
hyperscale data engine.
And it's built right
inside of Salesforce.
And Data Cloud does
something really special.
See, data platforms, data
warehouses, data lakes,
they bring data together.
They're really good at
bringing data together
And Data Cloud does
the same thing there.
But Data Cloud takes it
even one step further.
You see, with Data
Cloud, what we really
We want to help you
action all of that data.
And that's why
Data Cloud is
It's integrated
with metadata
so that we can use
all of the data
that we connect into
Data Cloud across all
Data Cloud is how
customers are building
entirely new experiences.
For example, you can bring
product telemetry data
into Data Cloud now,
all of the data that's
burning off of your
digital products.
And now we can do
real-time proactive
So your service
agents can reach out
to your customers
if there's an outage
before the
customer even knows
It's how sales
organizations are bringing
in website data
in real time
so that they can give
their sales development
leaders the information
that their prospect is
actually on their
website right now.
This is the power of
not only unified data
but making that
data actionable
Now, what makes this
possible is something
called metadata,
which we'll
talk about in a moment
because I'm a slide ahead.
But let's talk about how
Data Cloud works first.
So the way Data
Cloud works
is really three key steps.
We start by
connecting your data.
We can connect data
from Salesforce orgs
and applications, from
data warehouses and data
lakes, like Snowflake, but
really from any system.
And it works on
structured data,
semi-structured data,
or unstructured data.
From there, we
want to harmonize
all of that data, which is
just a fancy way of saying
that we're going to build
a data model out of it.
So we're going
to work with you
to-- or the product works
with you to define how
that data exists,
what it's related to,
what other data
it's related
This gives us a sense
of how the data is used.
And then finally, we can
activate all of that data.
We can drive insights
from it, of course.
We can discover new pieces
of data by looking at it.
But we can also action
it across sales, service,
commerce, marketing, flow.
We can build automations
and workflows,
Now, what makes all of
this possible is metadata.
The entire
Einstein 1 Platform
is built on this
concept of metadata.
It's something that we
pioneered 20 years ago.
And it's even more
important today.
And it's worth
taking a moment
to describe what
metadata is.
Metadata is just
context about your data.
It's a description of
how your data is used.
And because of
that description,
it becomes a language that
the rest of the platform
This is how we're able
to provide sharing rules.
This is how we're able
to look at data in sales
And it's usable no matter
what cloud we're in.
But what really
is metadata?
Well, here on
the screen, we
have some data,
some numerical data.
And it looks, as human
beings, fairly useless.
It's a collection
of numbers.
It's hard to tell what
these numbers are.
Are they some
sort of metric?
Are they some sort of ID?
The reason we
can't figure it out
is because we don't
have the context.
We don't have the
metadata about this data.
But if we add
the metadata,
suddenly that data
becomes much, much more
clear to us as
human beings.
We can see that the 57263
is an account value.
That long 555, that's
a phone number.
The 10708, we can see
that that's a zip code.
In fact, that's
my zip code,
where I live, about 10
miles north of here.
And then we have
a Salesforce ID.
Suddenly, as
humans now, we
can understand this data.
We're able to intuit the
way that this data might
And this metadata is used
in the exact same way
This is how our platform
and, ultimately, AI
will use all of
this metadata
as well, which brings
us to Einstein.
You see, what we've
done with Data Cloud is
we've built it so
that all of that data
and all of that metadata
can now be used inside
of your AI inside
of your enterprise.
Parker mentioned
that we need
the AI to be able to
understand context
So we do this
with Data Cloud.
We take all of that
data, and we connect it
You want to ask
an LLM a question?
If you provide more
data, if you provide
more insight into
that question,
it's going to do
a much better job
This is done through
a technique called
retrieval augmented
generation, which
It's a really
important term.
All we do is we take
the question, which
is the prompt, and we need
to add some more context
So Salesforce
goes out, and it
And it brings it back in,
and it augments something.
So in other words,
all we're doing
is adding some hints
to your question,
giving the LLM a
few hints as to what
And then we send
that off to the LLM.
We do that
safely, of course.
Claire is going
to show you
what that looks like
in a little bit.
And we get our
answer back.
So that's how we bring
trusted data to our AI.
Now, Data Cloud has been
an incredible product
It is growing like crazy.
We are innovating
on it like crazy.
In fact, just a few weeks
ago in our spring release,
we announced an incredible
new capability called
Data Spaces, which allows
you to logically partition
your data across
different departments,
across different
functions or geographies,
Our customers are
adopting it like crazy.
And you can see
the growth numbers.
We're also incredibly
excited to announce
that Gartner
has just named
us a leader in their 2024
Gartner Magic Quadrant
for customer
data platforms.
But the innovation
doesn't stop there.
We're also incredibly
excited today
to announce a New Zero
Copy Partner Network.
And what this does is this
is an extension of what
the partnerships we've
been working on with AWS,
and Databricks,
and Snowflake,
enabling you to mount
to virtually bring data
to Data Cloud without
having to create
You can now virtually
mount these tables inside
Why would you
want to do that?
Well, you've already
invested so much
But remember, what
we care most about
is helping you
activate that data.
So keep that data
in Snowflake.
But connect it through
our Zero Copy Network.
And we can help you start
activating that data
and bringing that data to
where the business needs
We're also super
excited about announcing
our new data
ecosystem partners
that are bringing
net new data,
enrichment data as well,
partners like Moody's,
and ZoomInfo, Dun &
Bradstreet, and Workday,
Data Cloud, our
Einstein 1 platform,
it's all coming together
to help companies
transform, to help them
become an AI Enterprise.
Now, we're going to take
a look at Turtle Bay.
Turtle Bay is an
AI enterprise,
and we're actually
incredibly lucky.
We have Robert Marucci
here with us today,
the gentleman
on the right.
He happens to be right
here on my right as well.
He took a break
from surfing.
If you don't
know Turtle Bay,
Turtle Bay is an
incredible resort
If you're like me,
you don't get out
to Oahu much from here
on the East Coast.
But if you ever do, you
should and check out
It's an incredible resort.
Robert, I'm told today
was also your 32 wedding
I haven't been married
as long as you,
but I might have some
advice for you later.
So let's take
a look at how
Turtle Bay is
transforming and becoming
- Change is
not the hurdle.
Change is the
remedy that allows
And Salesforce is
giving us the ability
Turtle Bay is a beautiful,
magnificent resort that
sits on 1,300 acres
of dream landscape
in the North
Shore of Oahu.
- For over 50 years,
Turtle Bay Resort
has been the largest
employer here
And so I take
incredible pride
in being able to
tell that story.
- We're in the
luxury environment.
But to say luxury
and to really
communicate
what luxury is,
that's very difficult
because all of us
look at luxury
differently.
- Travelers today expect
us to know who they are.
And so making their
experience here more
personalized is
really critical.
- How do we make an
easy shopping experience
in merchandise that,
based on what their likes
Trust was the most
important thing.
I needed a trusted
source to secure my data,
and Data Cloud was
the differentiator
and the perfect product to
take that journey with me.
CRM with AI and data,
powered by trust,
that's the way
forward for us.
When sales is talking
to service, that's
giving the steward
the ability to say,
wow, this is really cool.
Like, I'm actually
having fun solving cases
- I love using the
Einstein 1 platform
because it gives me
everything I need
and all the guest details
right at my fingertips.
We have all of
these activities
that we can see
that they booked.
What the generative
AI can now do
is they can take
these activities
and then automatically
recommend other activities
that they know
these guests will
So that way,
our associates
have all the tools
to really sell
the guests on what
experience they're
- The Einstein 1
platform is really
redefining how
hospitality can
For me, to see where the
customer journey happened
prior to even being here,
to their journey on site,
to getting AI to tell
me what the next best
experience is that they
should buy, that's luxury.
And the return on
investment happens day 1.
We've quadrupled
our visitation
to our website,
triple-digit increase
in conversion
and acquisition,
giving us 40% lift
in top line revenue
Magic has happened along
the way far greater
The aloha here is
so deep and so real.
We're only as good
as our culture.
We're only as good
as our people.
Einstein 1
platform is helping
us augment the
processes so
that we can allow
the employee
We're giving them the time
to speak about their place
It's our greatest
currency here as a hotel.
And people leave here
saying, I will be back.
So as you can
see, Turtle Bay
is becoming an
AI Enterprise.
And it's really
it's so incredible
to see how they're
delivering these highly
personalized experiences.
And it couldn't be more
important than when
It's the last
thing you want
to think about is, what
do I need to go do?
So it's awesome
to see this.
And we can see exactly
why so many Turtle Bay
customers are
deciding to come back.
But as awesome as that is,
as inspiring as that is,
what I always want to know
is, how do they actually
How are they
actually using
our set of tools,
Salesforce's tools,
So we're going to
spend a few minutes
and show you
how to do that.
And so first, I want to
welcome for the first time
today our incredible
demo team right here
OK, so let's
go to the demo.
They always come up
with something new.
All right, so here
is Turtle Bay,
and we're looking at
Salesforce and Turtle Bay
right here inside
of Salesforce.
And what we're
actually looking at
Or we'll call her
Jackie for short.
Jackie is a customer
of Turtle Bay.
And we can see a little
bit of information
We can see that she
lives in New York, which
We have her address, some
kind of standard contact
information that we
would expect to have.
In fact, we have a little
bit more than that.
We have some
reservation details.
In fact, we
can see that it
looks like Jackie
happens to be staying
But if we look kind
of around the rest
of this screen, this is
maybe a little bit anemic.
This isn't a complete view
of Jackie and everything
I think we can do a
lot better than that.
But to do better
than that,
we're going to
need more data.
We're going to need
probably a lot more data.
And what we
don't want to do
is just go ask somebody
to manually type
all that data
into Salesforce.
We can do quite a
bit better than that.
So to achieve that, we're
going to use Data Cloud.
So let's jump over
to Data Cloud.
So here we are
inside of Data Cloud.
And what we're
looking at here
is a list of all of the
different streams that are
And it's not a
very big list.
We only have our
one Salesforce org.
We could connect multiple
Salesforce orgs and clouds
But right now, we've got
our one Salesforce org.
And what I
really want to do
is I want to add more
data to that view.
One of the simplest
things that I would
like to know
about my customer
when they're
staying at my resort
is, what reservations,
what experiences
What restaurant
reservations do they have?
And so to do that, we're
going to click New.
We're going to add
some new data sources.
And you can see
here that there
is a whole host of
different data sources
Of course, we can add
Salesforce data sources,
we can add other data
lakes and data warehouses.
And the list
goes on and on.
As we look down through
the bottom here,
we can see that
MuleSoft provides
a million more data
sources that we can add.
And this is
really important.
Customers have so many
different sets of data
that they might
need to connect.
But what I want to do is I
want to connect Snowflake.
In fact, I want to
connect a Snowflake Table
because, at Turtle
Bay, what they've done
is they've taken all of
their reservation data
from their restaurant
reservations.
And that actually ends
up inside of Snowflake.
And I'd like to
activate that.
I'd like to increase
that investment that I've
made in Snowflake
so that I
can activate on that data
inside of Salesforce.
Let's go ahead and
click Next on that.
We're going to
add to Snowflake.
Now, I mentioned earlier
this idea of harmonizing.
So the next step is this
harmonization process,
which looks
like a fancy UI.
And it kind of is a
fancy UI, actually.
This is what helps you
map the data that's
sitting in Snowflake
to the data model
that we have inside
of Salesforce, which,
of course, is
completely customizable.
This is how we're able to
harmonize and, ultimately,
unify data so
that we can see
that the customer attached
to the reservation
in Snowflake is
the same customer
and the identifier that we
have inside of Salesforce.
So we've done that
mapping there.
So that step is now done.
And through the
power of a demo,
we're going to go back
over to our data streams.
And we can see that
some time has passed,
and we've added a whole
host of additional data
We have streams from
Snowflake, from Oracle,
from Salesforce, from
a few different APIs.
We can see our restaurant
reservation table
So we have a tremendous
amount of additional data
So let's go back
over to Jackie
and take a look at
her profile now.
So this is suddenly
no longer anemic.
This is now a much,
much, much more
This has made Salesforce
immensely more capable
and better by bringing
all of that data in.
We can see we still
have Jackie there
We've got some calculated
insights, which is just
a fancy way of saying,
we're looking over all
of that data that
we've just connected,
and bringing in
insights, and adding it
right here into the
profile with a Lightning
We've got our restaurant
bookings up there
We can see she has
a booking the 27th.
She's got a
booking at Alaia.
We can see her
booked experiences.
She's going to go on
a birdwatching tour.
Over in the top right,
we can see her status.
We can see that she's
currently at the resort.
We can also see
something called
This is using
our model builder
to bring in a model that--
an AI model
that Turtle Bay
has built to look at their
propensity to rebook.
And this is based
on all of this data
A customer that takes
all of these experiences
is probably much more
likely to rebook.
So we're able to
bring that in as well.
So we now have this
much, much, much more
thorough view of Jackie,
and this is incredible.
But remember, this
is all about action.
What we really want to do
is activate on this data.
So let's click
over and look
at what this might
look like from Jackie's
So Jackie is on
vacation right now.
She's probably
sitting at the pool.
And she gets this highly
personalized email.
So your personalized
Turtle Bay getaway, and we
can see that it
knows who Jackie is.
It knows how long
she's staying.
But if we go
down, we can see
that it's suggesting some
experiences that Jackie
So with one click,
Jackie could click that.
And what we've
done is we've
activated on all of
that data in real time.
We can see that
Jackie's at the resort,
and we're able to push
her this notification
in real time, all through
the power of the Einstein
1 platform and the
power of Data Cloud
to bring all of
this data in.
Now, we want you
all to get started
It is an incredible tool.
There are so many
different ways
that you can implement it
and bring new capability
If you follow
that QR code,
we can walk you through
some of those ways.
You can get
started yourself.
You can go to Trailhead,
and get an org,
and get started with
Data Cloud today.
And we're excited to
see how you use it
and to see how you
use it to transform
your business into
an action-oriented AI
And so with that, I'm
going to hand it back over
Incredible demonstration.
Thank you to the
demo people here.
You guys did a great job.
So that was a
demonstration
of building that Customer
360 and a real deep dive
on data cloud,
which, really,
for me, is the heart
of our architecture,
is the heart of our
future because it's
But now that we have all
that data harmonized--
and I did shift my
role in January.
I'm now the CTO of
Slack, actually.
So this next section--
yeah, I love slack.
And what better way
to interact with AI
than a conversational
interface like Slack.
And so with that,
we want to talk
about collaborating
with AI.
I'd like to bring
up Claire Shih,
And thank you, all of
us, for joining us today.
I'm so thrilled to be
back in New York with all
of you to talk about AI
and the AI Enterprise.
With everything
that's going on
and this tremendous
opportunity
to drive the next level
of customer experience,
productivity,
and efficiency,
it's no surprise
that everyone
in this room and the
majority of business
leaders wants to become
an AI Enterprise.
And we've learned
firsthand together
how to do this already
on the predictive side.
Just as you heard
from Parker,
we pioneered AI for CRM
together 10 years ago.
And now, across
self-service bots,
across sales forecasting,
across data stories,
across so many amazing
predictive innovations,
we're now delivering over
1 trillion predictions
across every
Salesforce application.
And it's all thanks
to all of you.
And so building on this
tremendous foundation,
we're going to take
it to the next level.
And I'm so thrilled
today to be announcing
the general availability
of Einstein Copilot.
Einstein Copilot is
your one unified AI
conversational
assistant across
every Salesforce
application--
sales, service, marketing,
MuleSoft, Tableau, Slack.
And just as you
heard from Patrick,
Einstein Copilot
out of the box
is automatically
aware of and grounded
in your organization's
data and metadata,
in your organization's
business logic,
whether those are
flows, apex code,
That's what makes
it so smart.
And so other AI in the
market, they're all talk.
Einstein Copilot
takes action
for you and your
employees to drive
that next level
of productivity
Now, this is why we're
seeing tremendous business
outcomes from deploying
generative and predictive
Just as you saw
from the video
just now, Robert
and his team,
they're driving an
uplift in sales.
We're seeing companies
like Grubhub increase
sales team member
productivity by 20%.
We're seeing companies
like AAA Insurance
reduce their response
time by 10%, increasing
We're seeing companies
like General Mills
increase the number of
customer engagements by 3x
and so on and so forth
across every department,
every industry, every
workflow in your company.
Now, every Salesforce
product manager,
every cloud,
every industry now
wants to make
it easy for you.
And so they're building
out-of-the-box, turnkey,
copilot actions and
prompt templates,
whether it's sales
account summaries so that
your sales teams can walk
into customer meetings
fully prepared and up to
speed on their Customer
Or it's customer service
with automated reply
recommendation suggestions
and case summaries.
Or it's actions in Tableau
or marketing and commerce
cloud, product
line generation
and subject line
generation, on and on.
Every cloud is supporting
your easy deployment of AI
in a secure and
trusted way.
Now, nothing is more
important to making
this work, of course,
than trusted data.
And just to talk for
a moment about this,
I'm going to turn it over
to my colleague, Matthew
- If AI's is
the Wild West,
does that make
data the new gold?
Data is the new
gold, and it's
central to our
Einstein Trust Layer
that powers
everything that we
do in AI, from Einstein
Copilot to Slack AI,
to Tableau
Pulse, and more.
You can see it
right there,
the secure data retrieval.
Having that trusted
data and metadata
about who has
access to what data
and what business
logic is what
reduces hallucinations
and drives accuracy,
relevance, and
performance.
The Einstein
Trust Layer also
has data
security, elements
like data masking, and
zero retention prompts,
We have ethical guardrails
like toxicity detection,
and we keep an audit trail
so that you can understand
at every step of the way
how the AI is performing
Now, I said earlier,
Einstein Copilot
is one unified Copilot
across every Salesforce
And that includes
Slack and Tableau.
And so you're already
having your employees
conversing and
collaborating
with their
teammates in Slack.
Now they have
a new coworker
they can collaborate with,
and it's Einstein Copilot.
In fact, Slack has a
slew of AI innovations
to make it even easier
to drive productivity
and connectivity
with CRM right
from within your favorite
collaborative workspace.
We have record channels,
the new chatter,
where you can
have conversations
about any CRM record,
whether that's
a sales opportunity,
or a service case,
We have Sales Elevate that
brings all of your Sales
Cloud data and KPIs right
into Slack, where you can
also update any of these
records in real time
And then last
but not least,
Slack AI, which allows you
to get quickly up to speed
with amazing new features,
like thread summaries,
AI recaps on
any conversation
Now, the fourth step to
becoming an AI Enterprise
is about delivering
AI analytics
and empowering
every employee
in your organization to
become a Data Explorer
And that's exactly
what we're doing, first
Tableau Pulse proactively
delivers AI-driven data
insights to every employee
in your organization.
I love getting
my Tableau Pulse.
I get it in my email
as well as in Slack.
And it identifies metrics
that I may not have even
known to ask
about and empowers
me to make better
decisions right
in the flow of work,
wherever I might
We're also thrilled to
bring Einstein Copilot
to Tableau so that you
can go deeper and ask
more questions
of your data
and have visualizations,
calculations done, simply
using natural
language, the language
And so I want to show
you how all of this looks
and bring back our
demo team, [? Rusha ?]
and Maximo, and
bring us back to Oahu
to see the Turtle Bay
demo organization.
We've got some snorkeling
going on there, too.
And we're going to walk
through two personas.
We're going to see how
the marketing team uses
And then we're going
to see how the sales
team uses it across both
Slack as well as CRM
Let's go to Oahu together.
We're going to start here
as the marketing team.
And right away, we see
this brand new feature.
It's called the
Slack AI recap.
And it's bringing
my attention
to occupancy insights,
very important
if you're
managing a resort.
So we're going to
click into that
and see what's going on
with occupancy insights.
And right away, Robert
and his team, they're
able to see this
Tableau Pulse showing
that, unfortunately,
occupancy rates are
Now, as the
marketing team,
we have to do
something about this.
And so we start
collaborating
We've got our
coworkers here.
We're deciding
together to focus
on the corporate segment.
We want to have more
corporate events
And now I'm going to
bring in a new coworker
to help us to take
it to the next step.
And that is
Einstein Copilot.
So I'm going to ask
Einstein Copilot to help
me figure out
what will resonate
with this corporate
event segment.
Now, behind the scenes,
Einstein Copilot
is referencing
everything that you just
In Data Cloud,
it's looking
at third-party
review sites.
It's scanning through
all the customer survey
It's looking at
bookings data
from these third-party
systems, these trapped
islands of data
in Snowflake
that we've now brought
into Data Cloud
And in an instant,
Einstein Copilot
is able to tell
me that Lu'aus
are what's most popular
with this corporate event
And I'm going to share
this insight back
with the rest of
my marketing team
And now, the content
and creative team
is going to get cracking.
They're going to flip over
to Salesforce Marketing
Cloud and build a campaign
for the corporate event
But they're not going
to do it from scratch.
They're going to rely on
help from their coworker,
This is the same Copilot
we've been interacting
And it's able to,
in a split second,
generate this landing
page and email.
Einstein Copilot
is grounded
in all of Turtle Bay's
data and metadata.
It understands our
brand, our images,
what's on message,
our brand voice.
And it's looking
pretty good.
I've even asked
it to create
a section for
Lu'aus, given
that insight we
were given earlier,
as well as for
sales contacts
so that we can
really drive leads
And in just an instant,
I'm able to click Publish.
So before we
move on, I just
want to take a
step back and think
In the past,
what we just saw
would have taken
days, if not weeks.
Someone would have had to
run a report on occupancy
Maybe that report would
be reviewed once a week
or once every other week.
Then someone
else would have
to run data pulls on
these different systems
and a pivot table
to figure out
which segment to target
and what resonates
Then to build a
campaign from scratch,
think about the creating
images from scratch
or creating copy
from scratch.
We did all of that
in just three minutes
together in
this live demo.
OK, so we're generating
a ton of leads
Now let's flip over
to one of the sales
reps views on
Robert's team.
Our sales rep,
John, has logged
He can see his
typical set of KPIs,
what are the group
reservations looking like.
Well, how is he tracking
against his quota
Unfortunately, he's
a little light.
So he's going to ask
Einstein Copilot to help
And instead of having
to call every customer
and getting a lot
of rejections,
he wants to know
who to focus on.
And so Einstein
Copilot, again,
is crunching all of this
data across Data Cloud
to figure out who is
highly qualified, who
has a high propensity
to convert and to want
And in this case,
no surprise.
Einstein Copilot is
suggesting that the sales
Jackie is the same
customer whose profile
that we enriched
and unified earlier
And Einstein Copilot
even explains
why it identified Jackie.
It's because she just took
her family on a vacation
She clearly has an
affinity for the property.
She's given it a high
customer satisfaction
Again, that's data from
a third-party system that
was pulled in through the
Zero Copy Partner Network.
And she doesn't have any
open customer support
So there should be no
sensitivities and reason
for the sales team
not to reach out.
And so at this point,
John, our sales person,
is going to actually ask
Copilot to help him figure
out what the
next steps are
to get an opportunity
going with Jackie.
And so Einstein Copilot
is going across all
of the sales policies,
the best practices, what's
worked in the past to
generate this action
John can even ask
Copilot to automate some
of these actions for him.
And that's exactly
what he's doing.
He's saying, write
that email for me.
Personalize it for
Jackie based on what we
know her preferences are.
And just like
that, that email
is generated,
saving John hours
of time of researching,
and writing, and editing.
He can go through,
make any edits,
And so that email gets
Jackie interested.
Fast forward a
couple of weeks,
and now John's pipeline
is looking really
And he's able to
transition from sales
planning and prospecting
to sales execution
He's meeting
with customers.
He's in slack,
collaborating
with all of the other
team members at Turtle Bay
Resort to help get these
deals to a closure.
And now, thanks to
Slack Sales Elevate,
he can see all of
his critical sales
KPIs right from
within Slack.
He can see his
quota, his pipeline,
his revenue
closed to date.
He also gets
a notification
that Jackie, his prospect,
is actually coming on site
So he's going to click in.
And he can see there's a
number of his coworkers
across the resort
who've been busy at work
to plan the perfect
visit for Jackie
Now, there's 20
unread messages.
And John's a busy
guy, so he's just
going to ask for
a thread summary
so that he doesn't have to
read every single message.
And right away, Slack AI
summarizes for him exactly
which of his coworkers
is doing what
so they can
stay coordinated
for the perfect
prospect visit.
Now, not only can you view
information thanks to--
I'm going to go back
into this channel.
You may have noticed
it's a little bit unique.
And it's because this
is a record channel that
corresponds to this sales
opportunity in Sales
So we can view
this information.
They can have
conversations.
He can even update the
records in Salesforce
He's going to actually
change the stage
for this
opportunity, given
Jackie is coming on site.
And as soon as
he hits Save,
it automatically
kicks off a workflow
to create a new external
channel for John
to collaborate with
Jackie, with his prospect,
to co-create that
sales proposal.
Just think about how much
more higher conversion
we can achieve when
the customer is part
of the proposal creation.
And right away,
there's a Canvas
and a welcome message
that are automatically
generated based
off of a template.
And as she goes
through her visit,
Jackie can help update
what activities, what
restaurants, what
bookings, what the flow
And because of
her co-creation
in this process
and her buy-in,
John closes the
deal in record time.
And so this is how Slack,
and Tableau, and CRM come
together, powered by
AI data and trust,
to break down
organization silos,
and drive business
outcomes, and take action.
All right, so we built
our Customer 360.
We've harmonized the
data, love those demos,
collaborating with AI,
the Copilot, Slack,
Those are awesome--
and the analytics.
But now we want to
geek out a little bit.
And the best person to
geek out with right now
to talk about
deploying trusted
AI and Copilot is my good
friend, Leah McGowan-Hare,
SVP of the
Trailblazer community.
Thank you so much
for hanging out.
We all know artificial
intelligence is not
It is changing how we
move through our lives.
It's impacting how
we work, how we live.
It even is putting
an end to busy work.
There was a study done
that said 62% of our time
is lost to
repetitive tasks.
Now, I don't
know about you,
but I want to
reclaim my time.
I could use that
62% time back
because, like
you, I'm being
tasked, like all of us,
to do more with less.
So we need to make
every minute count
and really supercharge
our productivity.
That's why we've
built automation
into the Einstein
1 Platform
so you can work
smarter, not harder.
And when I say
automation, only one thing
comes to mind,
and that's flow.
Oh, they're way
in the back seat.
OK, you're going to have
to do a better flow.
Flow helps us create
and deploy automation
And now, with
workflow engine,
we can bring workflows
to every part
But get this Now with
AI, an automation
It's going to be
amazing thing.
With Einstein
Copilot, we can
create dynamic
plans that are
How does all
this work, you
ask, because I
can hear you.
How does this work, Leah?
Well, it starts basic
with natural language.
You ask Einstein
a simple question.
Hey, in this case, can you
send a message to Lucy?
Immediately,
immediately, Einstein
gets to work
creating a plan.
Now, this is not
just any plan.
This is a plan that's
unique to your business.
You have trained
Einstein on this plan.
Now, here's the
differentiator.
It doesn't just
come up with a plan.
You heard Claire
talk about it.
Our Einstein doesn't
just talk about it.
You know those folks,
you guys have seen them.
You've worked with them,
who can talk about things
and come up with
great plans.
That's the differentiator.
Our AI takes action,
freeing you up
to do the things that
are important to you,
like creating amazing
customer experiences.
And you don't have
to be a developer
to build these dynamic
plans because Einstein
1 is a low-code,
no-code platform.
You can build custom apps
and workflows with clicks.
You can customize
and extend Copilot
to meet your business
needs with custom
And what this means
on a larger scale,
we've democratized
development
so that you can join our
21 million Trailblazers
out there innovating
on our platform.
That's my one
Flownatic back there
we know that everybody
is at a different place
And we're not just
giving you the technology
We're giving
you the people
because we have such
a vibrant ecosystem
of partners, of
our ISV partners,
sharing their innovations
on AppExchange.
You heard Patrick
talk about it earlier.
If you already have a
data lake in Snowflake
or databricks, we have
partnerships there as
And you want to use
a third-party AI?
We've got partnerships
with OpenAI, Cohere,
We will meet
you wherever you
And that's why we're
so excited to announce
Einstein 1 Studio
that lets you bring AI
to all parts of
your business.
With prompt
builder, you can
create reusable prompts
grounded in your data.
And we're going to
see this in action.
Copilot Builder
allows you to create
those dynamic
action plans that I
talked about earlier
with custom and standard
And model builder-- you
want to use your own LLM?
You want to use
a third party?
But now I talked about
actions, so let's
actually be about
it and see it
in a live demo with our
amazing demo drivers,
this is we're looking at
the concierge dashboard.
And I want you to note
this is a live Tableau
dashboard that
is really live.
And to the
right of it, you
can see Einstein Copilot
is riding shotgun,
helping us create
incredible guest
Now, when the concierge
goes in there,
they ask, hey, who are my
high-value guests arriving
Now, I know what
you're thinking,
how do they know
what is high value?
Well, once again, this
is unique to Turtle Bay.
So that business logic
Einstein has been
It could be spend
amount Just get the list
Remember, she was coming
back to the property.
And it looks like she
missed her flight.
Now, as we heard
earlier, Turtle Bay
wants to know what's
happening to their guest
even before they arrive
because their experience
And we can see she
missed her flight.
You're not that
happy because you
So we want to go
ahead and give her
So we're going
to ask Einstein,
grant her some
resort credit.
Now, I want you
to note here.
Einstein comes
back and says,
sorry, I'm unable
to do that.
Well, that's
anticlimactic.
But here, really, what
he should have said is,
I'm not able
to do that yet.
That's what I tell
my kids all the time.
You're not able
to do that yet.
So we are going to
train an Einstein
on how to give resort
credit within Turtle Bay's
But then Einstein
also offers,
hey, we're going to send
Jackie this Welcome text.
But that little
welcome text
does not scream
high value.
So listen, we're going
to do two things,
and I need you to hang out
with me for two things.
We're going to
give a makeover
We're going to really
personalize it.
And we're going to
teach Einstein Copilot
the business of
giving resort credit.
I'm not doing this alone.
So in order to
do this, we're
going to jump on
over into Einstein 1
Studio, where we can bring
AI to all parts of Turtle
And the first stop
we're going to make
We're going to use
generative AI to create
Now, how many people here
have been in ChatGPT?
OK, so you all have
written a prompt.
A prompt is the
instructions
we give to the LLM to
get a response back.
Well, what we're
going to do here,
we're going to
create a prompt that
is going to be reusable
by all concierges
and is grounded in
our trusted data.
We're going to go
up here and say,
we want to write
a prompt that's
going to personalize
this text message.
Now, earlier we saw
Patrick harmonize
We're going to leverage
that data in this prompt.
We're going to go to
that data graph, which
is basically the
unified profile.
We have access to more
than just their name.
We know dietary
constraints, the things
And we're going to pull
that data into our prompt
So this is not
merge fields
This is much
better than that.
And so then--
now get this.
I get super excited
about this, super--
because, like Parker
says, I geek out.
We are not just bringing
in data to this prompt.
We have access to
actions, like flows.
Our prompt not only
has data but has access
So this is going to
be a very personalized
message because
here we're going
to recommend activities
for this particular guest.
And then the
bow that we're
going to wrap around it
is the Turtle Bay tone
So when that text
message goes out,
whoever sends it out,
whichever concierge sends
it out, it always has the
standard Turtle Bay tone
So we're going
to bring that in.
That's a pretty awesome
personalization message
So here we're going to
have the resolution.
And what you're going
to see is the JSON.
This is the
information that's
going to be sent to the
LLM in that trusted way
that Claire talked
about earlier.
This information
gets sent over.
And of course, there's
some rag in between.
Am I right there, Patrick?
So here, this is going
to be sent to our LLM,
and we're going to
get the response back.
This looks oh-so-much
better than that little
1990s merge field
text we saw earlier.
So we're going
to-- we did that.
We did a makeover
to the text message.
What was the second thing
we were going to do?
We're going to go
ahead and train
Turtle Bay's Einstein
on giving resort credit.
So let's jump on
over to Copilot
and see what
that looks like.
So here we are in
Einstein Copilot.
Now, I want you to
notice we automatically
have standard actions
available to us.
But because
there's innovation
regularly-- you heard
Clara talking about that.
We're innovating
all the time.
This list is going
to grow every month.
But we also have access
to Turtle Bay's custom
They've been doing things
long before we came along.
They've got some
apex in there.
We can leverage all of
these custom actions
to train Einstein on the
business of Turtle Bay.
I know you're
thinking, what?
So we go ahead and we
bring over these actions.
But here's what
is awesome.
We don't need to
determine the sequence
It is determining
what is the sequence
of the actions that
we bring it over.
We're going to go
ahead and do a preview.
And we're going
to see Einstein
do its magic as it's
thinking and creating
So we ask it, go ahead
and give resort credit.
And here there's that plan
that I was talking about.
And there, we see
the flow happening
from the ERP system
gets the reservation.
Then we have
some apex firing.
And it's determining
all the things
that it needs to do
to give the credit
to the appropriate guest.
So we're seeing
Einstein live.
All right, so
check, number two.
We just taught it
how to give access--
how to give
resort credits.
But now let's see it
all come together.
So let's go back, back
to the future, [SWOOSH]..
So we're going
to go back here.
And now we're going to
ask, again, Einstein,
will you please give
credit to Jackie?
And this time, Einstein
comes back and says,
So we have trained it to
do to give the credit.
This looks so much better.
And here's a preview
of the text message
that's going to
get sent to Jackie.
I want to see
the-- don't you
want to see the
actual text message?
Just shake your head yes.
So we're going to go out
here and see the text
This is what
Jackie receives.
Now, this is a
welcome text message.
This is giving
high-value customer.
We're saying, hey, here's
a gluten-free restaurant.
We know that you
are gluten free
because we know about
your dietary constraints.
And we just
don't stop there.
We say, by the
way, we also know
that your flight
was delayed,
showing a little empathy.
We're going to go ahead
and give you some resort
Now, this is a glow
up of a text message.
This, my friends,
is the power
of Einstein 1
and Data Cloud.
This is AI that
takes action.
OK, so the five steps
to the AI Enterprise.
We're going to do
the Customer 360.
We're going to get our
data together, unify it
We're going to
collaborate with Slack.
We're going to do
analytics with Tableau,
deploy it with Einstein
Copilot in Slack.
Well, there's still
a lot to learn.
If you didn't
catch all of that,
we know how you learn it.
You learn it as
a Trailblazer.
You go to Trailhead,
and you learn it.
You join our
community just
like all the trailblazers
here in the room.
It's an incredible
community.
Trailhead is an
incredible resource.
We also have these
other new communities
that are incredible,
the brand new ones,
Serviceblazer community
for service cloud
enthusiasts,
Salesblazer community
if you're focused
on sales cloud.
And the reason
that they're
joining these communities,
the reason you're
going to Trailhead, the
reason you're learning
those five steps and
all those details
is because it's
good for you.
It's why we're
all together.
11.6 million new
Salesforce jobs
And those jobs can be for
you or maybe your children
if they're coming up
into the ecosystem.
$2 trillion in net gain
of business revenue,
so that's pretty
awesome, too.
That's the end
of our keynote.
But don't go away right
away because you can come
back in here at 1:00 and
come see me and Soledad
We're going to do a
little 30 minute talk.
She can ask me anything,
so it should be fun.
Also, a whole bunch
more happening
out in the expo, more
keynotes happening.
Please also give
us feedback.
We love to make these
keynotes better, better,
Give us feedback,
and with that,
enjoy the rest of the day.