AI is the smallest, biggest word
that I hear used all the time.
The one bit of advice that I have
take a minute to just understand
the difference in architecture,
necessary for autonomous agents,
where you’ve been experimenting
with copilots or chatbots.
My name is Ivy Wright with Salesforce,
from Fortune Brainstorm Tech
in sunny Park City, Utah.
SVP, Enterprise IT Strategy
Thank you so much for being here
We’ve sat in on a few panels,
lots of great sessions so far,
but I want to hear from you.
From what you’ve sat in on so far,
do you have any big takeaways?
that you’re like (gasps),
I haven’t thought about that.
I was on a panel yesterday,
and it was all about ROI.
And I loved the conversation
about how different organizations
Just the definition of it.
Traditionally, we think about
cost-cutting, capacity creation.
But folks were looking at ROI
higher quality data being
the return on investment,
that can now audit their space,
So I thought that was really great.
So I was in the session too,
and I was, of course, taking notes.
pay our employees faster.
You talked about auditing.
You talked about this capability
for AI agents to actually look
in your background and audit.
Do you want to tell us about that?
Agentforce on help.salesforce.com,
in the earlier implementation,
the agent was hallucinating.
information that we had available
And so the agent actually
helped us surface the fact
that we’ve got knowledge articles
out there that have different answers.
So we turned that agent internally.
to clean up our underlying data.
And then when we pointed it back out,
I mean, see right there, guys.
Salesforce on Salesforce.
We drink our own champagne.
whole conversation around
different ways to find ROI.
And they were also saying
on that panel that we almost
redefine how we’re thinking about AI,
and even use new metrics.
We’ve actually talked about
a framework to say you can
look at ROI in the context of
efficiency, effectiveness,
And because I was an ex-banker,
always got its own little section.
That’s come up a lot, though.
has been topic of the day.
auditability, traceability.
And I loved actually in our breakfast
that we just had right now,
Tell me more about what that is,
how people can set this up,
what its function looks like.
This idea of Guardian Agents
that are performing the actions,
agents that are overseeing the agents
that are performing the actions,
that there's integrity in
how these agents are performing.
Okay, one more thing I loved about,
thinking about agents in a different way.
You said something that was
such an “aha” moment for me.
Okay, so you were talking about how,
But then you also talked about,
when we’re thinking about agents
then there’s kind of like
and they report to this person.
Okay, talk me through this
whole idea of how we should be
my origin story to Salesforce.
how I sort of taught myself about,
what is this agenetic architecture,
and I had heard about Agentforce
at that time, because, you know,
Salesforce is a marketing engine
when I heard Agentforce, I thought,
Agentforce, it’s like a desktop
for my contact center agents,
because at my previous organization,
the contact center agents.
and it’s really got a little thing
That’s probably the Einstein
And it was an “aha” moment
We need to actually describe
I went, I want my own billboard
And I started to think about this
notion that there is a hologram of
an agent that is sitting next to me.
So if we’ve got Agent Astro
and I started to think about
my onboarding to Salesforce
and how I would relate it
When I joined Salesforce,
there was a job description
An agent needs a job description.
When I joined Salesforce,
someone had to provision data,
the right provisioning of data,
not access to all of the data.
When I joined, I was given
or the actions that I need
to perform in the role that I’m in.
When I joined, I needed a laptop,
Maybe this is our channel
where I’m engaging customers
and it can engage with customers
and colleagues like Slack.
And then the last thing is,
I usually have my access card
and I go, when I joined Salesforce,
someone said, you can open this door
and you can’t open this door.
Agents need the parameters of
which are the doors that you are
And that’s when it started
to come to me to say, wow,
It’s more than just a question
that I ask in a text box,
and get an answer and copy-paste.
It helped me understand it so well.
Yeah, no, such a good analogy.
Shibani, you meet with a ton of CIOs.
You’re talking with them about their
with all of their roadmapping.
What is one, or a few, of the
big misconceptions they have?
What are they doing wrong?
What is the thing that you’re
hearing over and over again?
The thing that they’re doing wrong is
They should be buying a platform.
But the biggest misconception
every time Data Cloud comes up,
I can practically read their mind.
Data Cloud is not another
data lake, or data warehouse.
I know that you’re thinking that.
I don’t need another data lake,
all of my data, Salesforce.
And three, you’re probably thinking,
I don’t want to be locked in,
because once you’ve got everything,
when I first heard Data Cloud,
and I didn’t understand it.
And I’m like, I have Azure,
I already have Databricks,
I don’t need another one.
Until I started to talk to
CIOs to say, how many people
have a user ID and password
to all of your data lakes
and warehouses to extract that data
through your organisation?
because they aren’t built
for that operational performance.
And so I said, Data Cloud is like
a thin activation layer where
you can harmonize the data.
your lakes and warehouses
and you’re able to activate it
throughout your organization
And then that’s when they go,
this is what Data Cloud is.
There was a gentleman from TIAA.
He’s their chief information officer.
And he had brought up yesterday
sexy use cases for AI, right?
I love that he said that.
It literally woke me up at night.
I wrote down on my phone,
Ivy, we need to talk about
different things if that’s
what’s waking you up at night,
Those big boring problems
this is where you really make the ROI.
It’s really not the sexy use cases.
One, if you find a big boring problem
and you’re showing that through AI,
that you can address that
suddenly that becomes something
desirable for colleagues going,
did you just take away this
administrative piece of thing
would keep me up at night
and you’ve taken that away?
In our breakfast that we just had,
a little slide up on the screen.
But you walked us through
a four-stage Agentic Maturity Model.
Tell me about the different levels.
This Agentic Maturity Model
It’s been created by a number
the greatest minds coming together.
This Agentic Maturity Model
is less about the levels.
It is about what it helps
our customers understand.
get a common language for
the biggest, smallest word, AI.
People use AI so loosely,
but it can be everything from
predictive, to generative,
to autonomous, or agentic.
one, helps people understand the plane
predictive to generative to autonomous.
But it helps them understand
and where do they aspire to be,
perhaps in the next year,
to cut through all the noise.
It’s overwhelming. I’m going,
break down the attributes
Make only the tech investment
in what you need to activate
Harmonize only the data attributes
that you need into Data Cloud
to activate that singular use case.
Validate that you’re getting the returns,
and see that the value you are getting
might’ve been fearing before.
And then move to Level 2,
where you’re incrementally
adding that architecture,
and then Level 3, and Level 4.
Thank you for explaining that.
Where do you think most CIOs
are landing on that model today?
I’m like, Level 4 doesn’t exist yet.
A lot of CIOs would like to think
they’re really looking at,
what they’re describing is a copilot.
And so it’s very important
that when you’re in the room
with CIOs, that you really
that describes what their maturity is.
when you’re in this meeting,
what’s the implementation that
you’ve had within your organization?
Or are you at autonomous?
And that in itself strikes up
the right conversation to say,
well, actually we’re really looking
So let’s talk about agentic architecture,
because the architecture that you need
for agentic agents to traverse
the virtual halls of your organization
what you’re doing for a copilot.
Okay, so speaking of CIOs
not knowing exactly where they’re at,
One thing that came up a lot
was this idea of failure.
And we’ve heard in the past,
And it kind of felt like,
at Fortune Brainstorm Tech,
that that is not the case.
long failures where you learn more,
longer failures turn into successes.
So tell me a little bit about
how much time should we be
the notion fail fast, fail often.
the time that you spend in the failure.
as long as you can extract
We think about what we talked about
from our own implementation
where it helped us identify anomalies
in what we had in the underlying data
that was always on our website.
Sure, immediately turn off that agent
so that it’s not continuing
to give the wrong results, but then
sit in that failure to say,
value from this learning?
And you stay in that failure long enough
to realize that maybe we need an agent
that’s going to look at our data,
and help us identify those anomalies.
Fail as long as it takes you to learn.
Okay, Sam Altman recently called
What is your gut feeling here?
Where do you see the SaaS industry
That may not be very sexy,
where you’ve got platforms
like Salesforce on a single code base,
that is now creating the infrastructure
for people to build an agentic
and autonomous architecture.
does a customer really want
to build everything that is necessary
Or should they be looking at a partner
that has a platform that enables it,
and maintains it, and upkeeps it
horizontal SaaS is very well alive.
Maybe vertical SaaS is taking
You were just on a panel this morning,
They asked a question about
where do you see technology going
I want to ask you that same question,
because I absolutely loved your answer.
what do you see happening
in the next year in the AI world?
I was in Sydney, not too long ago,
and I’m sitting there with the CIO,
where do you think technology is going
Technology is moving so fast,
where technology is going.
Those are really well-known.
Your adaptability quotient.
And that adaptability quotient
how are you adapting to the world
And how technology is going
But the adaptability quotient
how interoperable, how open,
play nicely with the new emerging
technologies that are coming?
And I think of that in the context
of Salesforce where, yes, we’ve got
a very comprehensive platform,
but that platform plays nicely
So the adaptability quotient
of your architecture is where
I think people need to focus more.
I’ve got one more question for you,
any advice you have for leaders
that are starting out with AI,
they’re maybe mid-journey?
What’s your best advice for them
to move that up to the next level
AI is the smallest, biggest word
that I hear used all the time.
that I have for our customers,
or for prospects, is take a beat.
Take a minute to just understand
the difference in architecture,
necessary for agentic architecture,
for agents, for autonomous agents,
where you’ve been experimenting
with copilots or chatbots.
